paracompactness in l topological spaces in this paper a certain fuzzy paracompactness is presented by means of the concept of locally finite family of l fuzzy sets the concept of locally finite family can be used to characterize fuzzy countable compactness this fuzzy paracompactness is a natural generalization of lowen fuzzy compactness a fuzzy countably compact l set is fuzzy paracompact if and only if it is fuzzy compact a topological space x j is paracompact if and only if its induced space x j is fuzzy paracompact when ms l the fuzzy enhanced real line r l is fuzzy paracompact the product of a fuzzy compact set and a fuzzy paracompact set is fuzzy paracompact a fuzzy strongly t2 paracompact space is strongly s regular and strongly ws normal moreover a strongly s regular lindelof space is fuzzy paracompact

detection of signals by information theoretic criteria a new approach is presented to the problem of detecting the number of signals in a multichannel time series based on the application of the information theoretic criteria for model selection introduced by akaike aic and by schwartz and rissanen mdl unlike the conventional hypothesis testing based approach the new approach does not requite any subjective threshold settings the number of signals is obtained merely by minimizing the aic or the mdl criteria simulation results that illustrate the performance of the new method for the detection of the number of signals received by a sensor array are presented

model order selection of damped sinusoids in noise by predictive densities we develop a procedure for the order selection of damped sinusoidal models based on the maximum a posteriori map criterion the proposed method merges the concept of predictive densities with bayesian inference to arrive at a complex multidimensional integral whose solution is achieved by way of the efficient monte carlo importance sampling technique the importance function a multivariate cauchy probability density is employed to produce stratified samples over the hypersurfaces support region centrality location parameters for the cauchy are resolved by exploiting the special structure of the compressed likelihood function clf and applying the fast maximum likelihood fml procedure of umesh and tufts simulation results allow for a comparison between our method and the singular value decomposition svd based information theoretic criteria of reddy and biradar see ieee trans signal processing vol 41 no 9 p 2872 81 1993

spatio temporal spectral analysis by eigenstructure methods this paper presents new algorithms for estimating the spatio temporal spectrum of the signals received by a passive array the algorithms are based on the eigenstructure of the covariance and spectral density matrices of the received signals they allow partial correlation between the sources and thus are applicable to certain kinds of multipath problems simulation results that illustrate the performance of the new algorithms are presented

multiple emitter location and signal parameter estimation processing the signals received on an array of sensors for the location of the emitter is of great enough interest to have been treated under many special case assumptions the general problem considers sensors with arbitrary locations and arbitrary directional characteristics gain phase polarization in a noise interference environment of arbitrary covariance matrix this report is concerned first with the multiple emitter aspect of this problem and second with the generality of solution a description is given of the multiple signal classification music algorithm which provides asymptotically unbiased estimates of 1 number of incident wavefronts present 2 directions of arrival doa or emitter locations 3 strengths and cross correlations among the incident waveforms 4 noise interference strength examples and comparisons with methods based on maximum likelihood ml and maximum entropy me as well as conventional beamforming are included an example of its use as a multiple frequency estimator operating on time series is included

a universal prior for integers and estimation by minimum description length of the number of bits required to write down the observed data has been reformulated to extend the classical maximum likelihood principle the principle permits estimation of the number of the parameters in statistical models in addition to their values and even of the way the parameters appear in the models i e of the model structures the principle rests on a new way to interpret and construct a universal prior distribution for the integers which makes sense even when the parameter is an individual object truncated realvalued parameters are converted to integers by dividing them by their precision and their prior is determined from the universal prior for the integers by optimizing the precision 1 introduction in this paper we study estimation based upon the principle of minimizing the total number of binary digits required to rewrite the observed data when each observation is given with some precision instead of attempting at an absolutely shortest description which would be futile we look for the optimum relative to a class of parametrically given distributions this minimum description length mdl principle which we introduced in a less comprehensive form in 25 turns out to degenerate to the more familiar maximum likelihood ml principle in case the number of parameters in the models is fixed so that the description length of the parameters themselves can be ignored in another extreme case where the parameters determine the data it similarly degenerates to jaynes s principle of maximum entropy 14 but the main power of the new criterion is that it permits estimates of the entire model its parameters their number and even the way the parameters appear in the model i e the model structure hence there will be no need to supplement the estimated parameters with a separate hypothesis test to decide whether a model is adequately parameterized or perhaps over parameterized

order selection for ar models by predictive least squares a criterion is presented for selecting the order of autoregressive models that unlike the existing criteria is amenable to online or adaptive operation it is based on the predictive least squares pls principle and is implemented in a computationally efficient way by predictive lattice filters the consistency of the criterion is proved and its performance is demonstrated by computer simulations assuming the data to be generated by an ar model of order p the order selection criterion should select the correct order p with probability that converges to 1 as the sample size grows to infinity it is proved that the pls criterion is indeed consistent thereby giving a solid justification for the criterion simulation results that demonstrate the performance of the pls criterion in comparison to h akaike s aic 1973 and the mdl criteria of j rissanen 1978 and g schwarz 1978 are given

some new results and generalizations in metric fixed point theory abstract the main purpose of this paper is the study of the generalization of some results given in m berinde v berinde on a general class of multi valued weakly picard mappings j math anal appl 326 2007 772 782 and references therein some generalizations of the mizoguchi takahashi fixed point theorem kannan s fixed point theorems and chatterjea s fixed point theorems are established by using our new fixed point theorems

a new fuzzy compactness defined by fuzzy nets compactness is one of the most important notions in topology and is thoroughly investigated in general topology but it seems that the research about this notion in the area of fuzzy topology is not so effective as in general topology in fact it would seem that there was not even a good definition of compactness in this area until recently indeed soon after the famous article written by zadeh 8 was published chang 1 introduced the notion of fuzzy topological spaces and at the same time a certain fuzzy compactness was given from then on a series of different notions of fuzzy compactness have been discussed 2 3 71 and in 5 they were compared in detail but it seems unsatisfactory that all these fuzzy compactness ideas are defined for the whole fuzzy topological space but not for an arbitrary fuzzy subset therefore they are far from the crisp compactness for example it is impossible to discuss the hereditary property with respect to closed subsets of fuzzy compactness in 1977 pu and liu introduced the notion of fuzzy nets and a new concept of so called q neighborhood was given which could reflect the features of neighborhood structure in fuzzy topological spaces and by this new neighborhood structure the moore smith convergence theory was established spendidly 6 it furnishes us a basic tool to investigate the fuzzy compactness in a more general way to investigate the compactness of arbitrary fuzzy subsets in this paper a new fuzzy compactness defined by fuzzy nets we shall call it n compactness is given but we introduce the notion of r neighborhood see section 2 instead of qneighborhood to establish the moore smith convergence theory for it is perhaps more convennient to use n compactness possesses the following properties 1 n compactness is defined for arbitrary fuzzy subsets 2 for n compactness the hereditary property with respect to closed subsets holds 3 n compactness is a good extension 5 4 the continuous images of ncompact sets are n compact 5 for n compactness the tychonoff product theorem holds 6 if an n compact fuzzy topological space is t2 6 then it will satisfy a stronger separation axiom which will be called t4 in this paper 1 0022 247x 83 3 00

the determination of optimum structures for the state space representation of multivariate stochastic processes when identifying a model for a multivariate stationary stochastic process an important problem is that of determining the structure of the state variable model several overlapping parameterizations can usually be fitted to a given process and the question arises as to which structure leads to the most accurate parameter estimates the accuracy of parameter estimates is often measured by the determinant of the fisher information matrix we show that all admissible structures will give asymptotically the same value to this criterion for finite data some structures may still be better than others and two heuristic structure estimation methods are analyzed some simulation results are also presented

common fixed points of almost generalized contractive mappings in ordered metric spaces the existence theorems of common fixed points for two weakly increasing mappings satisfying an almost generalized contractive condition in ordered metric spaces are proved some comparative example are constructed which illustrate the values of the obtained results in comparison to some of the existing ones in literature

order selection of autoregressive models the problem of determining the order of autoregressive models by bayesian predictive densities is addressed a criterion employing noninformative prior densities of the model parameters is derived simulation results which demonstrate the good performance of the criterion are presented comparisons with four popular approaches verify its superiority in many cases

paracompactness in l fuzzy topological spaces abstract in this paper we introduce a good definition of paracompactness in l fuzzy topological spaces where l is a fuzzy lattice we define paracompactness on general l fuzzy subsets and study its properties

estimating the parameters of exponentially damped sinusoids and pole zero modeling in noise we have presented techniques 1 6 based on linear prediction lp and singular value decomposition svd for accurate estimation of closely spaced frequencies of sinusoidal signals in noise in this note we extend these techniques to estimate the parameters of exponentially damped sinusoidal signals in noise the estimation procedure presented here makes use of backward prediction in addition to svd first the method is applied to data consisting of one and two exponentially damped sinusoids the choice of one and two signal components facilitates the comparison of estimation error in pole damping factors and pole frequencies to the appropriate cramer rao cr bounds and to traditional methods of linear prediction second our method is applied to an example due to steiglitz 8 in which the data consists of noisy values of the impulse response samples composed of many exponentially damped sinusoids of a linear system having both poles and zeros the poles of the system are accurately determined by our method and the zeros are obtained subsequently using shanks method

paracompactness on l fuzzy topological spaces abstract in this paper we introduce a new kind of paracompactness called paracompactness on l fuzzy topological spaces and obtain some of its properties such as that it is a good extension hereditary with respect to closed subsets and that the cartesian product of an n compaact space and a paracompact space is a paracompact space as well as that a paracompact hausdorff space is both a regular and normal space

bayesian detection and estimation of cisoids in colored noise the problem of estimating the number of cisoids in colored noise is addressed it is assumed that the noise can be modeled by an autoregression whose order has also to be estimated a new criterion is proposed for estimating the number of cisoids and the autoregressive model order as well as a new algorithm for estimating the cisoidal frequencies in the derivation a bayesian methodology and subspace decomposition are employed the proposed criterion significantly outperforms the popular mdl and aic as applied in a paper by nagesha and kay in addition an algorithm that reduces the computational complexity of the solution is developed computer simulations that demonstrate the performance of the criterion are included

paracompactness in fuzzy topological spaces abstract in this paper we introduce two kinds of fuzzy paracompactnesses which are defined on general fuzzy subsets each of them is a good extension of crisp paracompactness they are all hereditary with respect to closed subsets and take n compactness and some other compactnesses in fuzzy topological spaces as special cases of them furthermore in a class of spaces so called weakly induced spaces which connects crisp spaces with fuzzy spaces both a fuzzy regular lindeloff property and a fuzzy pseudo metric property imply these two kinds of paracompactnesses

common fixed point of mappings satisfying almost generalized s t contractive condition in partially ordered partial metric spaces in this paper we present the concept of almost generalized s t contractive condition and combine this idea with the concept of partial metric and prove some common fixed point results in such spaces an example is presented to verify the effectiveness and applicability of our main result

some good l fuzzy compactness related concepts and their properties i the aim of this paper is to introduce good definitions of almost light and near compactness in l fuzzy topological spaces where l is a fuzzy lattice these weak compactnesses are defined for arbitrary l fuzzy sets and their properties studied

a note on the compactness in l fuzzy topological spaces abstract the purpose of this note is to correct an erroneous conclusion given in a paper by kudri and warner fuzzy sets and systems 86 1997 241 248 we shall show that lowen fuzzy compactness and xu fuzzy compactness are equivalent

pcf extended with real numbers we extend the programming language pcf with a type for total and partial real numbers by a partial real number we mean an element of a cpo of intervals whose subspace of maximal elements single point intervals is homeomorphic to the euclidean real line we show that partial real numbers can be considered as continuous words concatenation of continuous words corresponds to refinement of partial information the usual basic operations cons head and tail used to explicitly or recursively define functions on words generalize to partial real numbers we use this fact to give an operational semantics to the above referred extension of pcf we prove that the operational semantics is sound and complete with respect to the denotational semantics a program of real number type evaluates to a head normal form iff its value is different from b if its value is different from b then it successively evaluates to head normal forms giving better and better partial results converging to its value author s abstract

supremum metric on the space of fuzzy sets and common fixed point theorems for fuzzy mappings this paper generalizes a classical result about the space of bounded closed sets with the hausdorff metric and establishes the completeness of cb x with respect to the completeness of the metric space x where cb x is the class of fuzzy sets with nonempty bounded closed a cut sets equipped with the supremum metric d which takes the supremum on the hausdorff distances between the corresponding a cut sets in addition some common fixed point theorems for fuzzy mappings are proved and two examples are given to illustrate the validity of the main results in fixed point theory

common fixed point results for four mappings satisfying almost generalized s t contractive condition in partially ordered metric spaces abstract in this paper we define the concept of almost generalized s t contractive condition and prove some common fixed point results for four mappings satisfying almost generalized s t contractive condition in partially ordered metric space an example is given to support the usability of our results

semicompactness and s closedness in n fuzzy topological spaces in this paper we introduce semicompactness and s closedness in l fuzzy topological spaces we define s closedness and semicompactness on arbitrary l fuzzy sets prove their goodness and set up some of their properties

a categorical accommodation of various notions of fuzzy topology different definitions of fuzzy topology have been stated and developed in the literature but have not been satisfactorily related to each other and to ordinary topology to remedy this a new fuzzy topological category fuzz is defined it is a significant generalization of previous definitions it is the simplest setting yet constructed into which ordinary topology and these previous definitions may be placed by identifying each with a different subcategory of fuzz it therefore allows us to conveniently analyze the relative merits of previous definitions give coherence to known results and indicate appropriate directions for future development and it generates and may be viewed as both including and included in categories of fuzzy topological spaces which exhibit higher order fuzziness