the q deformed boson realization of representations of quantum universal enveloping algebras for q a root of unity i the case of uqsl l the properties of q deformed boson operators with non generic q q is a root of unity are analysed by using the representation theory method and their finite dimensional representations are thereby obtained based on this discussion reducibilities and decompositions of q deformed boson realized representations of quantum universal enveloping algebra uqsl l are studied for non generic cases the explicit matrix elements of some indecomposable representations are obtained on the q deformed fock spaces necessary details are provided for uqsl 2 and uqsl 3 in particular the lusztig operator extension of uqsl 2 is discussed in an explicit form

cyclic boson algebra and q boson realizations of cyclic representations of the quantum algebra slq 3 the authors introduce the concept of cyclic boson algebra and study its representations using this algebra to realize slq 3 they construct the cyclic representation of the quantum universal enveloping algebra uq sl 3 identical to slq 3 on the q fock space restricting this representation to the subalgebra slq 2 slq 3 they naturally obtain the irreducible cyclic representations of slq 2

adaptive probability based latin hypercube designs adaptive sampling is an effective method developed mainly for regular regions however experimental regions in irregular shapes are commonly observed in practice motivated by a data center thermal management study a new class of adaptive designs is proposed to accommodate a specific type of irregular region because the adaptive procedure introduces biases into conventional estimators several design unbiased estimators are given for estimating the population mean efficient and easy to compute unbiased estimators are also introduced the proposed method is applied to obtain an adaptive sensor placement plan to monitor and study the thermal distribution in a data center all of the supplemental materials used in this work are available online

capacity and performance of mimo bicm with zero forcing receivers this work considers multiple input multiple output bit interleaved coded modulation mimo bicm with linear zero forcing zf receivers we derive the link level capacity llc under ideal fast fading conditions and show that it approaches the maximum likelihood ml llc as the number of receive antennas approach infinity we also derive tight analytical bounds on the coded bit error rate and prove that with n sub t transmit and n sub r receive antennas the diversity order is n sub r n sub t 1 multiplied by the free hamming distance of the convolutional code for the case of a ml receiver we show that a tight bound is not possible in general our analysis provides insights to explain the relative performance of the zf and ml receivers finally we validate the analytical results and assess the performance in a practical environment with orthogonal frequency division multiplexing and channel estimation

multilevel codes based on partitioning following v v ginzburg 1984 a hierarchy of codes is proposed to match the geometric partitioning of a signal set the authors show that coset codes including ungerboeck lattice and binary codes and indeed any codes which rely on partitioning of the signal set are all subclasses of the proposed coding scheme the combination of such codes in a multilevel scheme often leads to reduced complexity in comparison with previously published schemes a variety of decoder structures is discussed

indecomposable generalisations of the standard angular momentum representations of so 3 indecomposable representations of the lie algebra of the rotation group so 3 are studied on the heisenberg weyl basis which is the basis for a subspace of a quotient space of the space of the universal enveloping algebra of the heisenberg weyl algebra the author obtains an infinite dimensional indecomposable representation which induces the finite dimensional representation on certain quotient spaces and subduces the infinite dimensional indecomposable representations on invariant subspaces the standard angular momentum representations of so 3 are given as special cases

asymptotic performance of linear receivers in mimo fading channels linear receivers are an attractive low complexity alternative to optimal processing for multiple antenna multiple input multiple output mimo communications in this paper we characterize the information theoretic performance of mimo linear receivers in two different asymptotic regimes for fixed number of antennas we investigate the limit of error probability in the high signal to noise ratio snr regime in terms of the diversity multiplexing tradeoff dmt following this we characterize the error probability for fixed snr in the regime of large but finite number of antennas as far as the dmt is concerned we report a negative result we show that both linear zero forcing zf and linear minimum mean square error mmse receivers achieve the same dmt which is largely suboptimal even in the case where outer coding and deacircnot coding is performed across the antennas we also provide an apacircnot proximate quantitative analysis of the markedly different behavior of the mmse and zf receivers at finite rate and nonasymptotic snr and show that while the zf receiver achieves poor diversity at any finite rate the mmse receiver error curve slope flattens out progressively as the coding rate increases when snr is fixed and the number of antennas becomes large we show that the mutual information at the output of an mmse or zf linear receiver has fluctuations that converge in distribution to a gaussian random variable whose mean and variance can be characterized in closed form this analysis extends to the linear reacircnot ceiver case a well known result previously obtained for the optimal receiver simulations reveal that the asymptotic analysis captures accurately the outage behavior of systems even with a moderate number of antennas

on the complexity of sphere decoding in digital communications sphere decoding has been suggested by a number of authors as an efficient algorithm to solve various detection problems in digital communications in some cases the algorithm is referred to as an algorithm of polynomial complexity without clearly specifying what assumptions are made about the problem structure another claim is that although worst case complexity is exponential the expected complexity of the algorithm is polynomial herein we study the expected complexity where the problem size is defined to be the number of symbols jointly detected and our main result is that the expected complexity is exponential for fixed signal to noise ratio snr contrary to previous claims the sphere radius which is a parameter of the algorithm must be chosen to ensure a nonvanishing probability of solving the detection problem this causes the exponential complexity since the squared radius must grow linearly with problem size the rate of linear increase is however dependent on the noise variance and thus the rate of the exponential function is strongly dependent on the snr therefore sphere decoding can be efficient for some snr and problems of moderate size even though the number of operations required by the algorithm strictly speaking always grows as an exponential function of the problem size

completeness and unbiased estimation for sum quota sampling abstract most statistical methodology in use today is designed for sampling schemes or experimental designs in which the sample size or number of data points is regarded as a fixed preset parameter this is in part for mathematical convenience but is also suggested by the intuition that sampling is restricted by a total cost of data collection and that the cost of sampling remains the same from unit to unit the cost of sampling however may vary from unit to unit and the costs may be unknown before the sample is taken if so the objective of taking a sample of preset cost may force one to sample sequentially until achieving the preset cost and then stop that is the objective of taking a sample of fixed size may be turned against itself if the cost of sampling varies from unit to unit a cost may be monetary or general in character motivated by the possibility of a quota for costs consider the sampling scheme in which random variables xi are sampled sequentially until the sum of the associated non

detectability in conventional and adaptive sampling in this paper a simple but very general method is given for estimating a population total with any sampling design when objects in sampled units are observed with imperfect detectability a problem characteristic of many surveys of natural and human populations in the most general case the method consists of dividing the value of the variable of interest associated with each detected object by the detection probability for that object and then proceeding to use the estimation method that would ordinarily be used under the design if there were no detectability problems examples illustrating the method include simple random sampling conventional unequal probability sampling and adaptive cluster sampling

perpendicular distance models for line transect sampling summary perpendicular distance line transect models are examined to assess whether any single model can provide a general procedure for analysing line transect data of the two parameter models considered the hazard rate model appears promising whereas the exponential power series and exponential quadratic models do not of the nonparametric models the fourier series is the best developed and is favoured by many researchers as a general model however for a given data set the fourier series estimate may be highly dependent on the number of terms selected and so the model is not a clear improvement over the hazard rate model a similar variable term model using hermite polynomials is considered and is shown to be less dependent on the number of terms selected there has been some debate about whether the derivative of the density function of perpendicular distances evaluated at 0 should be 0 so that the function has a shoulder the problem is examined in detail and it is argued that reliable estimation is not possible from line transect data unless a shoulder exists many data sets appear to exhibit no shoulder possible reasons are examined

an adaptive procedure for sampling animal populations summary we consider an adaptive stratified sampling procedure for animal populations in which the sample size in a given stratum or primary unit depends on the observations obtained in previous strata or primary units this method provides a more efficient way of sampling sparse but highly clustered populations two sampling approaches are considered the first is a design unbiased strategy as the estimate of population density is unbiased through design induced factors such as the random selection of sites in each stratum the second is called a model unbiased strategy as the density estimate is unbiased under the model assumed for the spatial distribution of the population the theory is demonstrated by reference to sampling from a shrimp population

approximating the llr distribution for a class of soft output mimo detectors we present approximations of the llr distribution for a class of fixed complexity soft output mimo detectors such as the optimal soft detector and the soft output via partial marginalization detector more specifically in a mimo awgn setting we approximate the llr distribution conditioned on the transmitted signal and the channel matrix with a gaussian mixture model gmm our main results consist of an analytical expression of the gmm model including the number of modes and their corresponding parameters and a proof that in the limit of high snr this llr distribution converges in probability towards a unique gaussian distribution

the q deformed boson realization of representation of quantum universal enveloping algebras for q a root of unity ii the subalgebra chain of uq cl for pt i see ibid vol 24 p 3265 1991 applying the method of the q deformed boson realization for the quantum group to the case where q is a root of unity the authors establish a set of standard basis for the representation space of the quantum universal enveloping algebra uq cl associated with a typical subalgebra chain of uq cl on this basis they systematically obtain irreducible and indecomposable representations of uq cl and its subalgebras they discuss uq c2 in detail

inverse adaptive cluster sampling summary consider a population in which the variable of interest tends to be at or near zero for many of the population units but a subgroup exhibits values distinctly different from zero such a population can be described as rare in the sense that the proportion of elements having nonzero values is very small obtaining an estimate of a population parameter such as the mean or total that is nonzero is difficult under classical fixed sample size designs since there is a reasonable probability that a fixed sample size will yield all zeroes we consider inverse sampling designs that use stopping rules based on the number of rare units observed in the sample we look at two stopping rules in detail and derive unbiased estimators of the population total the estimators do not rely on knowing what proportion of the population exhibit the rare trait but instead use an estimated value hence the estimators are similar to those developed for poststratification sampling designs we also incorporate adaptive cluster sampling into the sampling design to allow for the case where the rare elements tend to cluster within the population in some manner the formulas for the variances of the estimators do not allow direct analytic comparison of the efficiency of the various designs and stopping rules so we provide the results of a small simulation study to obtain some insight into the differences among the stopping rules and sampling approaches the results indicate that a modified stopping rule that incorporates an adaptive sampling component and utilizes an initial random sample of fixed size is the best in the sense of having the smallest variance

mimo detection by lagrangian dual maximum likelihood relaxation reinterpreting regularized lattice decoding this paper considers lattice decoding for multi input multi output mimo detection under pam constellations a key aspect of lattice decoding is that it relaxes the symbol bound constraints in the optimal maximum likelihood ml detector for faster implementations it is known that such a symbol bound relaxation may lead to a damaging effect on the system performance for this reason regularization was proposed to mitigate the out of bound symbol effects in lattice decoding however minimum mean square error mmse regularization is the only method of choice for regularization in the present literature we propose a systematic regularization optimization approach considering a lagrangian dual relaxation ldr of the ml detection problem as it turns out the proposed ldr formulation is to find the best diagonally regularized lattice decoder to approximate the ml detector and all diagonal regularizations including the mmse regularization can be subsumed under the ldr formalism we show that for the 2 pam case strong duality holds between the ldr and ml problems also for general pam we prove that the ldr problem yields a duality gap no worse than that of the well known semidefinite relaxation method to physically realize the proposed ldr the projected subgradient method is employed to handle the ldr problem so that the best regularization can be found the resultant method can physically be viewed as an adaptive symbol bound control wherein regularized lattice decoding is recursively performed to correct the decision simulation results show that the proposed ldr approach can outperform the conventional mmse based lattice decoding approach

adaptive cluster sampling designs with primary and secondary units summary in adaptive cluster sampling designs an initial probability sample is selected and whenever the observed value of the variable of interest satisfies a given condition units in the neighborhood of that observation are added to the sample in this paper the initial design is selected in terms of primary units while subsequent sampling is in terms of secondary units such initial designs include systematic sampling strip sampling and other forms of classical cluster sampling but because of the subsequent addition to the sample of secondary units in the neighborhood of any secondary unit that satisfies the condition of interest the final clusters of units obtained through the procedure may be quite different in shape from the initial primary units the methods described in this paper apply to such sampling situations as whale surveys in which the research vessel temporarily leaves the selected transect to close in on sighted whales surveys of rare bird species in which initial observations are made at systematically selected sites and additional observations are made in the vicinity of any site at which sufficiently high abundance is observed and aerial walrus surveys in which the aircraft searches to either side of the preselected transect line whenever a congregation of animals is encountered because conventional estimators of the population mean and total are biased with such a procedure estimators that are unbiased under the adaptive designs are presented in this paper variance formulae and unbiased estimators of variance are also given the designs are illustrated using a point pattern representing locations of individuals or objects in a spatially aggregated population for such a population the adaptive designs can be substantially more efficient than their conventional counterparts

on maximum likelihood detection and the search for the closest lattice point maximum likelihood ml decoding algorithms for gaussian multiple input multiple output mimo linear channels are considered linearity over the field of real numbers facilitates the design of ml decoders using number theoretic tools for searching the closest lattice point these decoders are collectively referred to as sphere decoders in the literature in this paper a fresh look at this class of decoding algorithms is taken in particular two novel algorithms are developed the first algorithm is inspired by the pohst enumeration strategy and is shown to offer a significant reduction in complexity compared to the viterbo boutros sphere decoder the connection between the proposed algorithm and the stack sequential decoding algorithm is then established this connection is utilized to construct the second algorithm which can also be viewed as an application of the schnorr euchner strategy to ml decoding aided with a detailed study of preprocessing algorithms a variant of the second algorithm is developed and shown to offer significant reductions in the computational complexity compared to all previously proposed sphere decoders with a near ml detection performance this claim is supported by intuitive arguments and simulation results in many relevant scenarios

on the capacity of the gaussian channel with a finite number of input levels an analytic confirmation of an observation made by g ungerboeck 1965 that approximately optimal performance on a gaussian channel with capacity c can be obtained with about 2 sup c 1 levels is given in particular the results imply that by using about 2 sup c 1 levels a rate of nearly c 1 bit can be achieved and that by using 2 sup c 1 levels a rate of about c 0 4 bits can be achieved

multilevel codes theoretical concepts and practical design rules this paper deals with 2 sup l ary transmission using multilevel coding mlc and multistage decoding msd the known result that mlc and msd suffice to approach capacity if the rates at each level are appropriately chosen is reviewed using multiuser information theory it is shown that there is a large space of rate combinations such that mlc and full maximum likelihood decoding mld can approach capacity it is noted that multilevel codes designed according to the traditional balanced distance rule tend to fall in the latter category and therefore require the huge complexity of mld the capacity rule the balanced distances rules and two other rules based on the random coding exponent and cutoff rate are compared and contrasted for practical design simulation results using multilevel binary turbo codes show that capacity can in fact be closely approached at high bandwidth efficiencies moreover topics relevant in practical applications such as signal set labeling dimensionality of the constituent constellation and hard decision decoding are emphasized bit interleaved coded modulation proposed by caire et al see ibid vol 44 p 927 46 1998 is reviewed in the context of mlc finally the combination of signal shaping and coding is discussed significant shaping gains are achievable in practice only if these design rules are taken into account

an investigation of some estimators of variance for systematic sampling abstract this article provides to the survey practitioner some guidance about the problem of variance estimation for equal probability single start systematic samples an investigation of eight alternative estimators of the variance of the sample mean is presented in the first half of the investigation the theoretical properties of the estimators are compared using several superpopulation models in the second half the comparison is empirical based on several real populations recommendations are made about the appropriateness of the various estimators

adaptive cluster sampling with networks selected without replacement summary in the adaptive cluster design introduced by thompson 1990 a finite population of units under investigation is partitioned into networks on the basis of a specified condition for adding neighbourhoods to a sampled unit an initial sample of units is taken and a network may be sampled more than once in this paper we introduce a modification of the design in which networks are sampled only once two unbiased estimators are considered and the rao blackwell theorem is used to improve them in terms of efficiency the various estimators are compared using two examples

adaptive cluster double sampling summary we present a multi phase variant of adaptive cluster sampling which allows the sampler to control the number of measurements of the variable of interest a first phase sample is selected using an adaptive cluster sampling design based on an inexpensive auxiliary variable associated with the survey variable then the network structure of the adaptive cluster sample is used to select an ordinary one phase or two phase subsample of units and the values of the survey variable associated with those units are recorded the population mean is estimated by either a regression type estimator or a horvitz thompson type estimator the results of a simulation study show good performance of the proposed design and suggest that in many real situations this design might be preferred to the ordinary adaptive cluster sampling design

a characterization of functional realizations of three dimensional quantum groups the authors study in an exhaustive and systematic way the functional realizations of quantum and classical algebras related with su 2 su 1 1 and the oscillator group os 1 in order to achieve this purpose they have adopted a mapping that is a generalization of an algebra expansion procedure they have not transformed the algebras themselves but their representations this method enables them not only to relate classical algebras and their q analogues but also different type algebras whether they are quantum or not they have obtained and classified all possible q realizations including as particular cases all those already known in the literature

variance estimation for systematic designs in spatial surveys summary in spatial surveys for estimating the density of objects in a survey region systematic designs will generally yield lower variance than random designs however estimating the systematic variance is well known to be a difficult problem existing methods tend to overestimate the variance so although the variance is genuinely reduced it is over reported and the gain from the more efficient design is lost the current approaches to estimating a systematic variance for spatial surveys are to approximate the systematic design by a random design or approximate it by a stratified design previous work has shown that approximation by a random design can perform very poorly while approximation by a stratified design is an improvement but can still be severely biased in some situations we develop a new estimator based on modeling the encounter process over space the new striplet estimator has negligible bias and excellent precision in a wide range of simulation scenarios including strip sampling distance sampling and quadrat sampling surveys and including populations that are highly trended or have strong aggregation of objects we apply the new estimator to survey data for the spotted hyena crocuta crocuta in the serengeti national park tanzania and find that the reported coefficient of variation for estimated density is 20 using approximation by a random design 17 using approximation by a stratified design and 11 using the new striplet estimator this large reduction in reported variance is verified by simulation

soft input soft output single tree search sphere decoding soft input soft output siso detection algorithms form the basis for iterative decoding the computational complexity of siso detection often poses significant challenges for practical receiver implementations in particular in the context of multiple input multiple output mimo wireless communication systems in this paper we present a low complexity siso sphere decoding algorithm based on the single tree search paradigm proposed originally for soft output mimo detection in studer soft output sphere decoding algorithms and vlsi implementation ieee j sel areas commun vol 26 no 2 pp 290 300 feb 2008 the new algorithm incorporates clipping of the extrinsic log likelihood ratios llrs into the tree search which results in significant complexity savings and allows to cover a large performance complexity tradeoff region by adjusting a single parameter furthermore we propose a new method for correcting approximate llrs resulting from sub optimal detectors which often significantly improves detection performance at low additional computational complexity

adjusted two stage adaptive cluster sampling an adjusted two stage sampling procedure is discussed for adaptive cluster sampling where some networks are large and others are small a two stage sample is drawn from the large networks and a single stage sample is drawn from the rest the simple random sampling srs procedure is used at the second stage an estimator for the population mean along with its properties is discussed

training based mimo channel estimation a study of estimator tradeoffs and optimal training signals in this paper we study the performance of multiple input multiple output channel estimation methods using training sequences we consider the popular linear least squares ls and minimum mean square error mmse approaches and propose new scaled ls sls and relaxed mmse techniques which require less knowledge of the channel second order statistics and or have better performance than the conventional ls and mmse channel estimators the optimal choice of training signals is investigated for the aforementioned techniques in the case of multiple ls channel estimates the best linear unbiased estimation blue scheme for their linear combining is developed and studied

reporting bias and sampling errors in a survey of a rare population using multiplicity counting rules abstract this article examines a methodology to improve the efficiency of surveys to locate and estimate characteristics of rare populations two multiplicity counting rules are compared with a conventional rule in terms of reporting errors sample variances and survey yields the analysis is based on data from two survey field experiments with diagnosed cancer patients and a subsample of their siblings or children who reside outside their households the article concludes with a brief discussion of the circumstances in which a multiplicity counting rule is the preferred methodology and those in which other approaches should be pursued

the line transect method a nonparametric estimator based on shape restrictions summary a new estimator for population density based on line transect surveys is presented its sampling behaviour is investigated through simulation studies advantages of the proposed estimator include its simple intuitive base its stable behaviour over a wide variety of detection curves the ease with which it can be computed and the availability of reliable confidence limits the simulation results point to a general improvement in efficiency over existing estimators

semidefinite relaxation approaches to soft mimo demodulation for higher order qam signaling the soft demodulator is a key component of receivers that employ iterative demodulation and decoding for multiple input multiple output systems with binary or qpsk signaling the semidefinite relaxation sdr approach to list based soft demodulation provides a desirable balance between the performance and computational cost in this paper that approach is extended to systems with higher order qam signaling for the class of list sdr demodulators the key to the extension is a quadratic approximation of the a priori information and for the more computationally efficient class of single sdr demodulators the key to the extension is an algebraic expression derived herein for the probability that the sdr randomization procedure generates each candidate symbol to implement these demodulators customized primal dual and dual scaling algorithms are developed to solve the underlying semidefinite programs the performance of the proposed demodulators is compared with that of some existing demodulators by using error rate simulations the empirical distribution of the computational cost and exit chart analyses in our comparisons the proposed single sdr demodulator provides performance that comes close to that of the list sequential demodulator at a computational cost that is close to that of the minimum mean square error parallel soft interference canceller

factoring polynomials with rational coefficients in this paper we present a polynomial time algorithm to solve the following problem given a non zero polynomial fe q x in one variable with rational coefficients find the decomposition of f into irreducible factors in q x it is well known that this is equivalent to factoring primitive polynomials fez x into irreducible factors in z x here we call f z x primitive if the greatest common divisor of its coefficients the content of f is 1 our algorithm performs well in practice cf 8 its running time measured in bit operations is o nl2 n9 log fd3

branching processes in the annni model the mean field equations of the simple cubic annni model are studied on finite lattices the results are consistent with the sequence of distinct commensurate phases 2k 13 k 1 2 3 springing from the multiphase point found using low temperature series expansions moreover evidence for new structure combination branching processes is presented which generate phases of type 2l3 m 2l 13 n or 23l m 23l 1 n where l m and n are integers

boson realisation of virasoro and kac moody algebras and their indecomposable representations in this letter we give the boson realisation of virasoro and kac moody algebras without central terms and construct their indecomposable representations from some representations of the heisenberg weyl algebra the boson realisation of the kac moody algebra a 2 associated to the lie algebra su 2 is discussed in detail

randomization inference with natural experiments an analysis of ballot effects in the 2003 california recall election since the 2000 u s presidential election social scientists have rediscovered a long tradition of research examining the effects of ballot format on voting using a new dataset collected by the new york times we investigate the causal effect of being listed on the first ballot page in the 2003 california gubernatorial recall election california law mandates a unique randomization procedure of ballot order that when appropriately modeled can be used to approximate a classical randomized experiment in a real world setting we apply randomization inference based on fisher s exact test which directly incorporates the exact randomization procedure and yields accurate nonparametric confidence intervals our results suggest that being listed on the first ballot page causes a statistically significant increase in vote shares for more than 40 of the minor candidates whereas there is no significant effect for the top two candidates we also investigate how randomization inference differs from conventional e

bit interleaved coded modulation with mismatched decoding metrics bit interleaved coded modulation bicm has become the de facto coding standard for communication systems recently bicm has been cast as a mismatched decoding scheme due to the assumption of independent bit metrics in addition to this inherent mismatch practical demodulators may produce mismatched decoding metrics because of implementation constraints such as clipping and metric approximation to reduce computational complexity in this paper we investigate bicm with such metrics in line with recent works on this topic we adopt the generalized mutual information gmi as the pertinent performance measure first we show that level dependent scaling of logarithmic bit metrics can improve the bicm gmi second we propose a uniform metric scaling which can lead to an improved performance of mismatched sum product symbol by symbol decoding even if the gmi is not changed third we investigate general metric mismatch correction methods and analyze their effects in terms of the gmi by means of three application examples we illustrate that metric mismatch correction including metric scaling can significantly increase bicm rates

biometrika centenary sample surveys summary despite karl pearson s stated aim that the evolutionist has to become in the widest sense of the words a registrar general for all forms of life the papers published in biometrika on sample surveys have been mainly theoretical and do not start to appear until the 1940s there has been little work on sampling in the life sciences with the exception of capture recapture methods the major areas have been in variable probability designs the foundations of inference for finite populations analytic surveys and the role of selection mechanisms in inference in recent years the work on survey analysis has been the outcome of an interaction between sample selection mechanisms and mainstream theory with interesting consequences for both areas

quasi maximum likelihood multiuser detection using semi definite relaxation with application to synchronous cdma the maximum likelihood ml multiuser detector is well known to exhibit better bit error rate ber performance than many other multiuser detectors unfortunately ml detection mld is a nondeterministic polynomial time hard np hard problem for which there is no known algorithm that can find the optimal solution with polynomial time complexity in the number of users in this paper a polynomial time approximation method called semi definite sd relaxation is applied to the mld problem with antipodal data transmission sd relaxation is an accurate approximation method for certain np hard problems the sd relaxation ml sdr ml detector is efficient in that its complexity is of the order of k3 5 where k is the number of users we illustrate the potential of the sdr ml detector by showing that some existing detectors such as the decorrelator and the linear minimum mean square error detector can be interpreted as degenerate forms of the sdr ml detector simulation results indicate that the ber performance of the sdr ml detector is better than that of these existing detectors and is close to that of the true ml detector even when the cross correlations between users are strong or the near far effect is significant

on the error probability of signals in additive white gaussian noise a new upper bound to the probability of error in detecting one of m equally probable signals in additive white gaussian noise is presented this bound is easy to calculate can be applied to any signal set it is always better than the union and minimum distance bounds examples demonstrate the use of the bound

detectability functions in observing spatial point processes whenever populations modelled as spatial point patterns are sampled the observational methods used influence the form of the associated delectability functions in this paper we show how the properties of estimators of population quantities depend on the delectability functions in combination with the stochastic structure of the point process giving rise to the spatial patterns criteria for optimal delectability functions indicative of the most efficient observational methods are derived for the inference objectives of i estimating expected density and ii predicting or estimating realized density within a study region detectability functions related to observational methods such as plots of various shapes line transects radial transects and aerial surveys are compared numerically for a point process with aggregation tendencies for a given effective area observed constant delectability over the study region is optimal for predicting realized density while some curious doughnut shaped functions are more efficient for estimating the expected density parameter

on punctured trellis coded modulation punctured convolutional codes result in some savings in the complexity of viterbi decoders compared to other codes of the same rate however in general use of the punctured structure in the decoder results in a performance loss for trellis codes due to difficulties in assigning metrics we provide constructions for punctured rate 2 3 codes based on decomposition of the metric into orthogonal components these show no loss in performance for trellis coded qam and psk we also provide 180 spl deg and 90 spl deg rotationally invariant punctured tcm for qam signaling

estimation in survey sampling robustness and optimality abstract it is shown how the criteria of efficiency and robustness can be integrated fruitfully in a single optimality criterion within the framework of the unified theory godambe 1955 this is achieved by extending the scope of the usual model based estimation using appropriate sampling designs some situations of common occurrence in survey practice are discussed with a numerical study

estimating the encounter rate variance in distance sampling the dominant source of variance in line transect sampling is usually the encounter rate variance systematic survey designs are often used to reduce the true variability among different realizations of the design but estimating the variance is difficult and estimators typically approximate the variance by treating the design as a simple random sample of lines we explore the properties of different encounter rate variance estimators under random and systematic designs we show that a design based variance estimator improves upon the model based estimator of buckland et al 2001 introduction to distance sampling oxford oxford university press p 79 when transects are positioned at random however if populations exhibit strong spatial trends both estimators can have substantial positive bias under systematic designs we show that poststratification is effective in reducing this bias

adaptive cluster sampling abstract in many real world sampling situations researchers would like to be able to adaptively increase sampling effort in the vicinity of observed values that are high or otherwise interesting this article describes sampling designs in which whenever an observed value of a selected unit satisfies a condition of interest additional units are added to the sample from the neighborhood of that unit if any of these additional units satisfies the condition still more units may be added sampling designs such as these in which the selection procedure is allowed to depend on observed values of the variable of interest are in contrast to conventional designs in which the entire selection of units to be included in the sample may be determined prior to making any observations because the adaptive selection procedure introduces biases into conventional estimators several estimators are given that are design unbiased for the population mean with the adaptive cluster designs of this article that is the

unbiased estimation when sampling from renewal processes the single sample and k sample random means cases summary suppose random variables are sampled sequentially until the sum of associated nonnegative random variables is greater than or equal to a predetermined constant when no distributional assumptions are made we derive uniform minimum variance unbiased estimators for functions which are u estimable in the fixed sample size case we also consider estimation for some special cases when distributional assumptions are made when estimating the mean and variance of random means it is often assumed that sample sizes are independent of populations selected for sampling and hence independent of the random means associated with the populations sampled when sampling from renewal processes sample size is dependent on the distribution of the population selected for sampling thus in addition to the single sample case we consider the k sample problem and the estimation of the expectation and variance of random means

mmse decision feedback equalizers and coding i equalization results the minimum mean squared error decision feedback equalizer mmse dfe has properties that suggest that it is a canonical equalization structure for systems that combine equalization with coded modulation the structure and performance of the mmse dfe are succinctly derived using linear estimation theoretic principles in this first part of this two part paper the front end of the mmse dfe called the mean square whitened matched filter ms wmf is preferable in some ways to a matched filter or a whitened matched filter as a canonical receiver front end in a coded system the feedback filter of the mmse dfe may be implemented in the transmitter using precoding the mmse dfe can perform significantly better than a zero forcing decision feedback equalizer particularly at moderate to low snr s and on severe isi channels the mmse dfe is biased the optimum unbiased mmse dfe is the mmse dfe with the bias removed removing bias improves error probability but reduces the snr to snr sub mmse dfe u snr sub mmse dfe 1 it is shown that this snr relationship is a particular case of a very general result and that snr sub mmse dfe u gives a more realistic estimate of snr the results are extended to partial response equalization and to equalization with correlated inputs in an appendix

strip adaptive cluster sampling probability proportional to size selection of primary units summary strip adaptive cluster sampling is extended to situations where the primary units have unequal numbers of secondary units primary units are selected with replacement and with probabilities proportional to the number of secondary units the horvitz thompson estimator of the parametric total is used as the basis for estimation two cases are considered basic strip adaptive cluster sampling and strip adaptive cluster sampling under stratification of primary units a numerical example is presented in which the goal is to estimate the number of objects on a site the sampling strategy is useful for ecological studies where a rectangular grid of secondary units is not adequate to cover the study site

soft quasi maximum likelihood detection for multiple antenna wireless channels the paper addresses soft maximum likelihood ml detection for multiple antenna wireless communication channels we propose a soft quasi ml detector that maximizes the log likelihood function by deploying a semi definite relaxation sdr given perfect channel state information at the receiver the quasi ml sdr detector closely approximates the performance of the optimal ml detector in both coded and uncoded multiple input multiple output mimo channels with quadrature phase shift keying qpsk modulation and frequency flat rayleigh fading the complexity of the quasi ml sdr detector is much less than that of the optimal ml detector thus offering more favorable performance complexity characteristics in contrast to the existing sphere decoder the new quasi ml detector enjoys guaranteed polynomial worst case complexity the two detectors exhibit quite comparable performance in a variety of ergodic qpsk mimo channels but the complexity of the quasi ml detector scales better with increasing number of transmit and receive antennas especially in the region of low signal to noise ratio snr

performance assessment of mimo bicm demodulators based on mutual information we provide a comprehensive performance comparison of soft output and hard output demodulators in the context of non iterative multiple input multiple output bit interleaved coded modulation mimo bicm coded bit error rate ber widely used in literature for demodulator comparison has the drawback of depending strongly on the error correcting code being used this motivates us to propose the mutual information of the equivalent modulation channel comprising modulator wireless channel and demodulator as a code independent performance measure we present extensive numerical results for spatially independent identically distributed i i d ergodic and quasi static fading channels under perfect and imperfect channel state information these results reveal that the performance ranking of mimo demodulators is rate dependent and provide new insights regarding mimo bicm system design i e the choice of antenna configuration symbol constellation and demodulator for a given target rate

baseband trellis codes with a spectral null at zero a method is described for modifying classical n dimensional trellis codes to provide baseband codes that combine a spectral null at dc with significant coding gain the information rate of the classical code is decreased by one bit and this extra redundancy is used to keep the running digital sum bounded equivalently if the rate is held constant then twice as many signal points are needed causing a power penalty of 6 n db baseband trellis codes are presented for several information rates together with complete spectral plots and performance comparisons a method of constructing baseband codes with multiple spectral nulls is also described

new trellis codes based on lattices and cosets a new technique is proposed for constructing trellis codes which provides an alternative to ungerboeck s method of set partitioning the new codes use a signal constellation consisting of points from an n dimensional lattice lambda with an equal number of points from each coset of a sublattice lambda one part of the input stream drives a generalized convolutional code whose outputs are cosets of lambda while the other part selects points from these cosets several of the new codes are better than those previously known

bootstrap confidence intervals for adaptive cluster sampling consider a collection of spatially clustered objects where the clusters are geographically rare of interest is estimation of the total number of objects on the site from a sample of plots of equal size under these spatial conditions adaptive cluster sampling of plots is generally useful in improving efficiency in estimation over simple random sampling without replacement srswor in adaptive cluster sampling when a sampled plot meets some predefined condition neighboring plots are added to the sample when populations are rare and clustered the usual unbiased estimators based on small samples are often highly skewed and discrete in distribution thus confidence intervals based on asymptotic normal theory may not be appropriate we investigated several nonparametric bootstrap methods for constructing confidence intervals under adaptive cluster sampling to perform bootstrapping we transformed the initial sample in order to include the information from the adaptive portion of the sample yet maintain a fixed sample size in general coverages of bootstrap percentile methods were closer to nominal coverage than the normal approximation

matrix elements for indecomposable representations of complex su 2 indecomposable representations of the simple complex lie algebra a1 are investigated in this article from a general point of view first a master representation is obtained which is defined on the space of the universal enveloping algebra of a1 then from this master representation other indecomposable representations are derived which are induced on quotient spaces or subduced on invariant subspaces finally it is shown that the familiar finite dimensional and infinite dimensional irreducible representations of su 2 and su 1 1 are closely related to certain of the indecomposable representations indecomposable representations of a1 su 2 su 1 1 have found increased applications in physical problems including the unusual finite multiplicity indecomposable representations emphasis is placed in this article on an analysis of the more unfamiliar indecomposable representations the matrix elements are obtained in explicit form for all representations which are discussed in this article th

indecomposable representations of the lorentz algebra in an angular momentum basis indecomposable i e reducible but not completely reducible representations of the complex algebra so 3 1 of the lorentz group are analysed a master representation of so 3 1 is obtained on the space of its universal enveloping algebra omega the basis chosen for so 3 1 is the angular momentum basis and for omega a natural basis with respect to the angular momentum basis of so 3 1 the master representation induces representations on a space omega which is obtained from omega as quotient space modulo certain ideals these representations have the property that rho h3 is diagonal a change of basis is made from the natural basis to the angular momentum basis and the representations on omega are analysed in this new basis the indecomposable as well as the irreducible representations which are obtained have the property that their so 3 content consists of infinite dimensional indecomposable and irreducible so 3 representations certain of the indecomposable so 3 1 representations have additional invariant subspaces which lead to quotient spaces which are of finite dimension these quotient spaces then carry the familiar finite dimensional representations of the lorentz algebra it is shown that the standard theory of representations of the lorentz algebra is contained in this analysis as a special case of representations which are induced on certain quotient spaces of the space omega

a q deformed osp 1 2 superalgebra and its two component coherent state representations a q deformed osp 1 2 superalgebra is defined by the use of a pair of q boson annihilation and creation operators a kind of two component coherent state representation of the q deformed superalgebra is found and a q differential realization of the q deformed osp 1 2 superalgebra is obtained

a deformed quantum su 2 superalgebra a quantum q deformation of the su 2 superalgebra is obtained which contains as an even part the quantum suq 2 algebra the finite dimensional irreducible representations of the deformed quantum superalgebra are found

improved unbiased estimators in adaptive cluster sampling summary the usual design unbiased estimators in adaptive cluster sampling are easy to compute but are not functions of the minimal sufficient statistic and hence can be improved improved unbiased estimators obtained by conditioning on sufficient statistics not necessarily minimal are described first estimators that are as easy to compute as the usual design unbiased estimators are given estimators obtained by conditioning on the minimal sufficient statistic which are more difficult to compute are also discussed estimators are compared in examples

tensorial structure of a q deformed sp 4 r superalgebra a supersymmetric quantum algebra is generated by irreducible tensor operators with respect to the algebra suq 2 the even generators are realized as tensor products of q boson creation and annihilation operators transforming as suq 2 spinors and acting as odd generators in this way the transformation properties of all the algebra s generators with respect to the q deformed algebra of the angular momentum are simultaneously preserved which is important in view of future applications in physics in the limit q to 1 the classical lie superalgebra sp 4 r or the algebra osp 1 mod 4 is recovered

estimation of entropy and mutual information we present some new results on the nonparametric estimation of entropy and mutual information first we use an exact local expansion of the entropy function to prove almost sure consistency and central limit theorems for three of the most commonly used discretized information estimators the setup is related to grenander s method of sieves and places no assumptions on the underlying probability measure generating the data second we prove a converse to these consistency theorems demonstrating that a misapplication of the most common estimation techniques leads to an arbitrarily poor estimate of the true information even given unlimited data this inconsistency theorem leads to an analytical approximation of the bias valid in surprisingly small sample regimes and more accurate than the usual 1 n formula of miller and madow over a large region of parameter space the two most practical implications of these results are negative 1 information estimates in a certain data regime are likely contaminated by bias even if bias corrected estimators are used and 2 confidence intervals calculated by standard techniques drastically underestimate the error of the most common estimation methods finally we note a very useful connection between the bias of entropy estimators and a certain polynomial approximation problem by casting bias calculation problems in this approximation theory framework we obtain the best possible generalization of known asymptotic bias results more interesting this framework leads to an estimator with some nice properties the estimator comes equipped with rigorous bounds on the maximum error over all possible underlying probability distributions and this maximum error turns out to be surprisingly small we demonstrate the application of this new estimator on both real and simulated data

stratified adaptive cluster sampling summary stratified adaptive cluster sampling refers to designs in which following an initial stratified sample additional units are added to the sample from the neighbourhood of any selected unit with an observed value that satisfies a condition of interest if any of the added units in turn satisfies the condition still more units are added to the sample estimation of the population mean or total with the stratified adaptive cluster designs is complicated by the possibility that a selection in one stratum may result in the addition of units from other strata to the sample so that observations in separate strata are not independent since conventional estimators such as the stratified sample mean are biased with the adaptive designs of this paper several types of estimators are developed which are unbiased for the population mean or total with stratified adaptive cluster sampling