completely bounded modules and associated extremal problems in this paper we continue our study of certain finite dimensional hilbert modules over the function algebra a cm we show that these modules are always completely bounded with the bound obtained as the matrix valued analogue of a certain scalar valued extremal problem in particular we obtain a necessary and sufficient condition for our module to be completely contractive we produce a contractive module cnm over a bm such that it is completely bounded with the complete bound equal to m that is cnm is not completely contractive

exponential parameter estimation in the presence of known components and noise in the determination of the natural modes of an electromagnetic scatterer the measured time series will contain desired information noise and quite often known transient components introduced by the excitation source or measuring equipment this paper describes a linearly constrained total least squares lctls prony method for extracting the exponential model parameters from observed transient data for such problems the tls criterion yields better parameter estimates than ls moreover the incorporation of known signal information via constraints leads to even greater improvements in performance mathematical connections between lctls prony and a tls variation of time series deflation tsd are used to derive constraints for higher order excitation poles also we use tsd concepts to derive numerically superior data transformations for lctls simulation studies involving idealized test data and synthetic scattering response data of a perfectly conducting sphere demonstrate the advantages of the method

techniques for the efficient evaluation of two dimensional autocorrelation functions the evaluation of the autocorrelation of multidimensional sequences using the fft is investigated the bidimensional case is treated in detail not only because it is of special interest for the applications but also because the reasoning used for this case can be applied to higher dimension signals the analysis confirms that the use of the proposed frequency domain techniques leads to significant computation time savings

analysis of modified smi method for adaptive array weight control the authors characterize the performance of the diagonally loaded sample matrix inverse smi algorithm versus the number k of snapshots used in the covariance matrix estimate by providing o 1 k statistics bias and variance of the array weights output powers and output power ratios such as signal to interference noise ratio sinr and inr the approach accommodates wideband signals monte carlo simulations verify the theoretical analysis

nonlinear autoregressive and nonlinear autoregressive moving average model parameter estimation by minimizing hypersurface distance the least squares ls can be used for nonlinear autoregressive nar and nonlinear autoregressive moving average narma parameter estimation however for nonlinear cases the ls results in biased parameter estimation due to its assumption that the independent variables are noise free the total least squares tls is another method that can used for nonlinear parameter estimation to increase the accuracy of the ls because it specifically accounts for the fact that the independent variables are noise corrupted tls has its own limitations however mainly because it is difficult for the method to isolate noise from the signal components we present a new method that is based on minimization of hypersurface distance for accurate parameter estimation for nar and narma models computer simulation examples show that the new method results in far more accurate nar and narma model parameter estimates than do either the ls and tls with noise that is either white or colored and retains its high accuracy even when the signal to noise ratio snr is as low as 10 db

lms like ar modeling in the case of missing observations this paper presents a new recursive algorithm for the time domain reconstruction and spectral estimation of uniformly sampled signals with missing observations an autoregressive ar modeling approach is adopted the ar parameters are estimated by optimizing a mean square error criterion the optimum is reached by means of a gradient method adapted to the nonperiodic sampling the time domain reconstruction is based on the signal prediction using the estimated model the power spectral density is obtained using the estimated ar parameters the development of the different steps of the algorithm is discussed in detail and several examples are presented to demonstrate the practical results that can be obtained the spectral estimates are compared with those obtained by known ar estimators applied to the same signals sampled periodically we note that this algorithm can also be used in the case of nonstationary signals

sinusoidal frequency estimation by signal subspace approximation an efficient fourier transform based method that avoids eigenvector computation is proposed for approximating the signal subspace the resulting signal subspace estimate can be used directly to define a music type frequency estimator or as a very good initial guess in context with adaptive or iterative eigenvector computation schemes at low signal to noise ratios the approximation yields better results than exact music it is also more robust than music against overestimating the number of sinusoids some variations of the basic method are briefly discussed

weighted least squares design and characterization of complex fir filters the paper presents two novel weighted least squares methods for the design of complex coefficient finite impulse response fir filters to attain specified arbitrary multiband magnitude and linear or arbitrary phase responses these methods are computationally efficient requiring only the solution of a toeplitz system of n linear equations for an n length filter that can be obtained in o n sup 2 operations illustrative filter design examples are presented

a spectral domain integral equation method utilizing analytically derived characteristic basis functions for the scattering from large faceted objects a novel technique based on a spectral domain integral equation method with analytically derived characteristic basis functions is introduced in this paper it enables us to treat scattering problems from electrically large faceted bodies in a numerically rigorous and computationally efficient manner in terms of both time and memory the analytically derived characteristic basis functions include certain desirable features of the asymptotic schemes and are defined on subdomains that can be electrically large not being bound to the typical discretization size of the conventional method of moments by properly weighting through a galerkin procedure the resulting electric field integral equation the problem is reduced to a matrix equation having dimensions that do not depend on the size of the scatterer but only on its shape electrically large problems can be handled in a computationally efficient manner by using the proposed method since the associated matrix size is relatively small moreover all the reduced matrix elements are calculated in the spectral domain without evaluating any convolution products

a generalized surface integral equation formulation for analysis of complex electromagnetic systems a novel method is presented to analyze the electromagnetic characteristics of systems consisting of a large number of scatterers with different shapes and materials in the method nearly located scatterers are grouped together while large bulk materials are divided into subblocks with adequate sizes a scatterer group or a subblock forms a basic block of the system and each block is contained with a virtual reference surface a generalized transition matrix defined on the reference surface is used to characterize the electromagnetic characteristics of the block the generalized transition matrix relates the rotated tangential components of the scattered fields or the equivalence sources to the rotated tangential components of the incident fields directly the generalized transition matrix can be calculated for each block independently using proper methods according to its structure and material surface integral equations are established on all the virtual reference surfaces which can be solved by moment method to get the electromagnetic characteristics of the whole system characteristic basis functions and synthetic basis functions can be applied to further reduce the unknown number while fast multipole method can be used to accelerate the evaluation of interactions two dimensional examples are provided to verify the method

surface characterization using frequency diverse scattering measurements and regularity models accurate classification and characterization of image regions is often an important goal for the users of coherent imaging systems such as synthetic aperture radar sar many surfaces measured by remote sensing systems can be stochastically described by a regularity model this parametric point process model describes a 1 d surface in terms of the mean and variance of the interscatterer distances variations of these parameters can describe scatterer distributions ranging from totally random to nearly periodic under certain conditions a closed form approximation to the mean power spectrum of finite length data intervals exists the estimation of model parameters from measured spectra can then be cast as an optimization problem in which the total squared error between the approximation and the simple periodogram is minimized we examine the general performance limitations of such an optimization procedure determining how approximation error signal to noise ratio and frequency sampling rate affect the feasibility and accuracy of parameter estimation we determine under what conditions the approximation may be used we find that parameter estimation is feasible at a frequency sampling rate that is well below that suggested by the power spectral density psd this suggests that it is possible to obtain parameter estimates by comparing sparse narrow band frequency measurements to the psd of the point process and thereby obtain information about the surface on subresolution scales

application of higher order spectral analysis to cubically nonlinear system identification in this study digital higher order spectral analysis and frequency domain volterra system models are utilized to yield a practical methodology for the identification of weakly nonlinear time invariant systems up to third order the primary focus is on consideration of random excitation of nonlinear systems and thus the approach makes extensive use of higher order spectral analysis to determine the frequency domain volterra kernels which correspond to linear quadratic and cubic transfer functions although the volterra model is nonlinear in terms of its input it is linear in terms of its unknown transfer functions thus a least squares approach is used to determine the optimal in a least squares sense set of linear quadratic and cubic transfer functions of particular practical note is the fact that the approach of this paper is valid for non gaussian as well as gaussian random excitation it may also be utilized for multitone inputs the complexity of the problem addressed in this paper arises from two principal causes 1 the necessity to work in a 3d frequency space to describe cubically nonlinear systems and 2 the necessity to characterize the non gaussian random excitation by computing higher order spectral moments up to sixth order a detailed description of the approach used to determine the nonlinear transfer functions including considerations necessary for digital implementation is presented

frequency independent scattering from a flat strip with rm te _ z polarized fields the surface current for scattering from a pec strip naturally decomposes into three slowly varying functions modulating rapidly oscillating phase factors we exploit this structure to derive a numerical solution that is error controllable and exhibits a bounded error over the full range of frequencies frequency independence is obtained by expanding the current in terms of slowly varying amplitude functions stretching coordinates in the boundary layer and employing a frequency independent quadrature rule though the total current solution is always well defined unique minimally varying amplitude functions may also be found by using the minimum norm concept

characterizing three dimensional wavefields with high resolution spectra three dimensional spectra frequency x wavenumber y wavenumber or f kx ky spectra can be used to determine the frequency content velocity and direction of waves entering an array of receivers this information is important in detecting aliasing problems understanding coherent noise designing arrays and determining parameters for coherent noise filters because of the limited spatial dimensions of most arrays the discrete fourier transform produces an estimate of the three dimensional 3 d spectrum with severe wavenumber distortion we extend a 2 d hybrid spectral estimation method to three dimensions by combining a temporal fourier transform with a spatial 2 d maximum entropy spectral estimation technique the method produces f kx ky spectra with higher wavenumber resolution and less spectral distortion than corresponding 3 d fourier spectra the 2 d maximum entropy spectral estimation algorithm uses a sequence of fourier transforms to extrapolate the estimated autocorrelation function of the data

significance of group delay functions in spectrum estimation a method of spectrum estimation using group delay functions is proposed this method exploits the additive property of the fourier transform ft phase to extract spectral information of the signal in the presence of noise the phase is generally featureless due to random polarity and wrappings but the group delay function can be processed to derive significant information such as peaks in the spectral envelope in the resulting spectral estimates obtained the resolution properties of the periodogram estimate are preserved while the variance is reduced variance caused by the sidelobe leakage due to windows and additive noise are significantly reduced even in the spectral estimate obtained using a single realization of the observation peak resolution is primarily dictated by the size of the data window the method works even for high noise levels the results of this procedure are demonstrated through two illustrative examples estimation of sinusoids in noise and estimation of the narrowband autoregressive process in noise

viscosity solutions to complex hessian equations we study viscosity solutions to complex hessian equations in the local case we consider a bounded domain in cn the standard kahler form in cn and 1 m n under some suitable conditions on f g we prove that the equation ddc m n m f x n g on admits a unique viscosity solution modulo the existence of subsolution and supersolution if moreover the datum is holder continuous then so is the solution in the global case let x be a compact hermitian homogeneous manifold where is an invariant hermitian metric not necessarily kahler we prove that the equation ddc m n m f x n has a unique viscosity solution under some natural conditions on f

characteristic basis function method for solving electromagnetic scattering problems over rough terrain profiles a computationally efficient algorithm which combines the characteristic basis function method cbfm the physical optics po approach when applicable with the forward backward method fbm is applied for the investigation of electromagnetic scattering from and propagation over large scale rough terrain problems the algorithm utilizes high level basis functions defined on macro domains blocks called the characteristic basis functions cbfs that are constructed by aggregating low level basis functions i e conventional sub domain basis functions the fbm as well as the po approach when applicable are used to construct the aforementioned cbfs the conventional cbfm is slightly modified to handle large terrain problems and is further embellished by accelerating it as well as reducing its storage requirements via the use of an extrapolation procedure numerical results for the total fields as well as for the path loss are presented and compared with either measured or previously published reference solutions to assess the efficiency and accuracy of the algorithm

correlations in the bond future market we analyze the time series of overnight returns for the bund and btp futures exchanged at liffe london the overnight returns of both assets are mapped onto a one dimensional symbolic dynamics random walk the bond walk during the considered period october 1991 january 1994 the bund future market opened earlier than the btp future one the crosscorrelations between the two bond walks as well as estimates of the conditional probability show that they are not independent however each walk can be modeled by means of a trinomial probability distribution monte carlo simulations confirm that it is necessary to take into account the bivariate dependence in order to properly reproduce the statistical properties of the real world data various investment strategies have been devised to exploit the prior information obtained by the aforementioned analysis

two dimensional multivariate parametric models for radar applications part ii maximum entropy extensions for hermitian block matrices in a series of two papers a new class of parametric models for two dimensional multivariate matrix valued space time adaptive processing is introduced this class is based on the maximum entropy extension and or completion of partially specified matrix valued hermitian covariance matrices in both the space and time dimensions this first paper considers the more restricted class of toeplitz hermitian covariance matrices that model stationary clutter if the clutter is stationary only in time then we deal with a toeplitz block matrix whereas clutter that is stationary in time and space is described by a toeplitz block toeplitz matrix we first derive exact expressions for this new class of 2 d models that act as approximations for the unknown true covariance matrix second we propose suboptimal but computationally simpler relaxed 2 d time varying autoregressive models ldquorelaxationsrdquo that directly use the non toeplitz hermitian sample covariance matrix the high efficiency of these parametric models is illustrated by simulation results using true ground clutter covariance matrices provided by the darpa kassper dataset 1 which is a trusted phenomenological airborne radar model and a complementary afrl dataset

the sobolev inequality for complex hessian equations in this paper we study the complex hessian equations by an gradient flow method we prove a sobolev inequality for k plurisubharmonic functions analogous to that for real hessian equations wang in indiana univ math j 43 25 54 1994 lecture notes in mathematics vol 1977 2009

partial pluricomplex energy and integrability exponents of plurisubharmonic functions we first prove a quantitative estimate of the volume of the sublevel sets of a plurisubharmonic function in a hyperconvex domain with boundary values 0 in a quite general sense in terms of its monge ampere mass in the domain then we deduce a sharp sufficient condition on the monge ampere mass of such a plurisubharmonic function for exp 2 to be globally integrable as well as locally integrable

parallelized characteristic basis finite element method cbfem mpi a non iterative domain decomposition algorithm for electromagnetic scattering problems in this paper we introduce a parallelized version of a novel non iterative domain decomposition algorithm called characteristic basis finite element method cbfem mpi for efficient solution of large scale electromagnetic scattering problems by utilizing a set of specially defined characteristic basis functions cbfs this approach is based on the decomposition of the computational domain into a number of non overlapping subdomains wherein the cbfs are generated by employing a novel procedure which differs from all those that have been used in the past clearly the cbfs are obtained by calculating the fields radiated by a finite number of dipole type sources which are placed hypothetically along the boundary of the conducting object the major advantages of the proposed technique are twofold i it provides a substantial reduction in the matrix size and thus makes use of direct solvers efficiently and ii it enables the utilization of parallel processing techniques that considerably decrease the overall computation time we illustrate the application of the proposed approach via several 3d electromagnetic scattering problems

a sharp lower bound for the log canonical threshold in this note we prove a sharp lower bound for the log canonical threshold of a plurisubharmonic function varphi with an isolated singularity at 0 in an open subset of mathbb c n this threshold is defined as the supremum of constants c 0 such that e 2c varphi is integrable on a neighborhood of 0 we relate c varphi to the intermediate multiplicity numbers e j varphi defined as the lelong numbers of dd c varphi j at 0 so that in particular e 0 varphi 1 our main result is that c varphi geqslant sum j 0 n 1 e j varphi e j 1 varphi this inequality is shown to be sharp it simultaneously improves the classical result c varphi geqslant 1 e 1 varphi due to skoda as well as the lower estimate c varphi geqslant n e n varphi 1 n which has received crucial applications to birational geometry in recent years the proof consists in a reduction to the toric case i e singularities arising from monomial ideals

directed enumeration method in image recognition the article is devoted to the problem of image recognition in real time applications with a large database containing hundreds of classes the directed enumeration method as an alternative to exhaustive search is examined this method has two advantages first it could be applied with measures of similarity which do not satisfy metric properties chi square distance kullback leibler information discrimination etc second the directed enumeration method increases recognition speed even in the most difficult cases which seem to be very important in practical terms in these cases many neighbors are located at very similar distances in this paper we present the results of an experimental study of the directed enumeration method with comparison of color and gradient orientation histograms in solving the problem of face recognition with well known datasets essex feret it is shown that the proposed method is characterized by increased computing efficiency of automatic image recognition 3 12 times in comparison with a conventional nearest neighbor classifier

high spectral resolution time frequency distribution kernels a new class of time frequency distribution tfd kernels is introduced members in this class satisfy the desirable tfd properties and simultaneously provide local autocorrelation functions laf that are amenable to high frequency resolution modeling techniques it is shown that members of the proposed class are product kernels fast implementation multiplication free kernels recursive kernels and optimum kernels with respect to autoterm localization

modulability and duality of certain cones in pluripotential theory let p 0 and let ep denote the cone of negative plurisubharmonic functions with finite pluricomplex p energy we prove that the vector space ep ep ep with the vector ordering induced by the cone ep is dedekind complete and equipped with a suitable quasi norm it is a non separable quasi banach space with a decomposition property with control of the quasi norm furthermore we explicitly characterize its topological dual the cone ep in the quasi normed space ep is closed generating and has empty interior

the weighted monge ampere energy of quasiplurisubharmonic functions abstract we study degenerate complex monge ampere equations on a compact kahler manifold x we show that the complex monge ampere operator d d c n is well defined on the class e x of plurisubharmonic functions with finite weighted monge ampere energy the class e x is the largest class of psh functions on which the monge ampere operator is well defined and the comparison principle is valid it contains several functions whose gradient is not square integrable we give a complete description of the range of the operator d d c n on e x as well as on some of its subclasses we also study uniqueness properties extending calabi s result to this unbounded and degenerate situation and we give applications to complex dynamics and to the existence of singular kahler einstein metrics

bounded modules extremal problems and a curvature inequality abstract in this paper we study certain finite dimensional hilbert modules over the function algebra a c n these modules appear as localizations of a cowen douglas operator we show that these modules are always bounded where the bound is related to the solution of an extremal problem in particular we obtain necessary sufficient conditions for such a module to be contractive we apply the above results to produce an example of a contractive module over a b 2 which is not completely contractive

on the family of ml spectral estimates for mixed spectrum identification a recently developed point spectrum identification procedure based on a family of ar and ml spectral estimates is exploited to arrive at a mixed spectrum identification procedure to this end a variety of properties of the ar and ml estimates as a function of model order are described these properties relate to amplitude convergence resolution and a characterization of the ar spectral artifact which is used to arrive at improved continuous spectral estimates a variety of examples are presented

bounds for estimation of complex exponentials in unknown colored noise we consider the problem of estimating the parameters of complex exponentials in the presence of complex additive gaussian noise with unknown covariance bounds are derived for the accuracy of jointly estimating the parameters of the exponentials and the noise we first present an exact cramer rao bound crb for this problem and specialize it for the cases of circular gaussian processes and autoregressive processes we also derive an approximate expression for the crb which is related to the conditional likelihood function numerical evaluation of these bounds provides some insights on the effect of various signal and noise parameters on the achievable estimation accuracy

a weighted linear prediction method for near field source localization this paper proposes a low computational cost method for the near field narrowband source localization problem which does not require multidimensional search or high order statistics the proposed method is based on the second order statistics sos of the outputs of a uniform linear array ula more precisely the range and angle parameters are estimated through a weighted linear prediction lp algorithm applied to a properly chosen array output correlation sequence detailed performance analysis and derivation of the optimal weightings are provided simulation results are finally presented to validate the theoretical analysis results and to assess the performance of the proposed method

vector spaces of delta plurisubharmonic functions and extensions of the complex monge ampere operator in this paper we shall consider two types of vector ordering on the vector space of differences of negative plurisubharmonic functions and the problem whether it is possible to construct supremum

scaling in the market of futures the price time series of the italian government bonds btp futures is studied by means of scaling concepts originally developed for random walks in statistical physics the series of overnight price differences is mapped onto a one dimensional random walk the bond walk the analysis of the root mean square fluctuation function and of the auto correlation function indicates the absence of both short and long range correlations in the bond walk a simple monte carlo simulation of a random walk with trinomial probability distribution is able to reproduce the main features of the bond walk

representations of function algebras abstract operator spaces and banach space geometry let g be the closed unit ball of some norm on cn and let a g be the closure of the polynomials in the sup norm we prove that if n 5 then there is a contractive representation of a g as operators on a hilbert space which is not completely contractive our technique involves introducing a numerical invariant x for a normed space x which measures the difference between the minimal operator space structure which can be assigned to x min x and the maximal structure max x we estimate x using banach space techniques we also prove that if x is any infinite dimensional subspace of the space of continuous functions on a compact hausdorff space then there exists a bounded linear map on x which is not completely bounded

contour fft based spectral domain mbf analysis of large printed antenna arrays a fast spectral domain method is proposed to evaluate the reaction terms between the macro basis functions in regular and non regular arrays made of identical printed antennas the presented technique first exploits the filtering capabilities of the macro basis functions in the spectral domain the method is then strongly accelerated with the help of a newly formulated fast fourier transform fft based technique which is applicable to a contour integration in the complex plane we name the method as contour fft c fft besides an effective homogeneous medium term treated with multipoles a computational complexity of order n log2 n is achieved for the tabulation of substrate related reaction terms for any possible relative positions the complexity of the proposed method is independent from the complexity of the elements numerical results obtained with the proposed method are compared with those from a pre validated reference solution based on the traditional macro basis functions technique an excellent agreement is observed

on the application of parametric models to the transient analysis of resonant and multiband antennas the transient responses of a resonant antenna and a fractal multiband antenna both formed by conducting surfaces are calculated the surfaces are modeled by planar triangular patches and the study is carried out by solving the time domain electric field integral equation td efie linear parametric modeling techniques are applied to considerably reduce the computation time numerical results are compared with experimental measurements

point process model of 1 f noise vs a sum of lorentzians we present a simple point process model of 1 f noise covering different values of the exponent the signal of the model consists of pulses or events the interpulse interevent interarrival recurrence or waiting times of the signal are described by the general langevin equation with the multiplicative noise and stochastically diffuse in some interval resulting in a power law distribution our model is free from the requirement of a wide distribution of relaxation times and from the power law forms of the pulses it contains only one relaxation rate and yields 1 f spectra in a wide range of frequencies we obtain explicit expressions for the power spectra and present numerical illustrations of the model further we analyze the relation of the point process model of 1 f noise with the bernamont surdin mcwhorter model representing the signals as a sum of the uncorrelated components we show that the point process model is complementary to the model based on the sum of signals with a wide range distribution of the relaxation times in contrast to the gaussian distribution of the signal intensity of the sum of the uncorrelated components the point process exhibits asymptotically a power law distribution of the signal intensity the developed multiplicative point process model of 1 f noise may be used for modeling and analysis of stochastic processes in different systems with the power law distribution of the intensity of pulsing signals

plurisubharmonic and holomorphic functions relative to the plurifine topology a weak and a strong concept of plurifinely plurisubharmonic and plurifinely holomorphic functions are introduced strong will imply weak the weak concept is studied further a function f is weakly plurifinely plurisubharmonic if and only if it is locally bounded from above in the plurifine topology and f h is finely subharmonic for all complex affine linear maps h as a consequence the regularization in the plurifine topology of a pointwise supremum of such functions is weakly plurifinely plurisubharmonic and it differs from the pointwise supremum at most on a pluripolar set weak plurifine plurisubharmonicity and weak plurifine holomorphy are preserved under composition with weakly plurifinely holomorphic maps

local property of the class eχ loc abstract in this paper we introduce a new weighted energy class of plurisubharmonic functions and show the local property of this class under some extra assumptions on weights

proper orthogonal decomposition and its applications part i theory abstract in view of the increasing popularity of the application of proper orthogonal decomposition pod methods in engineering fields and the loose description of connections among the pod methods the purpose of this paper is to give a summary of the pod methods and to show the connections among these methods firstly the derivation and the performance of the three pod methods karhunen loeve decomposition kld principal component analysis pca and singular value decomposition svd are summarized then the equivalence problem is discussed via a theoretical comparison among the three methods the equivalence of the matrices for processing the objective functions the optimal basis vectors the mean square errors and the asymptotic connections of the three methods are demonstrated and proved when the methods are used to handle the pod of discrete random vectors

an adaptive correlator receiver for direct sequence spread spectrum communication this paper presents a novel receiver for direct sequence spread spectrum signals over channels containing interference and multipath the receiver employs an adaptive correlator that jointly detects the transmitted data removes interference and compensates for multipath the optimum correlation vector is derived by determining the wiener vector that minimizes the mean squared error mse between the transmitted data bit and the correlator output for an additive white gaussian noise awgn channel the optimal correlation vector is the spreading sequence used by the transmitter for interference and multipath channels the optimal correlation vector will suppress the interference and combine the multipath while optimizing the detection of the transmitted data bit the paper presents analytical and simulation results which illustrate the bit error rate ber performance of the receiver in multipath and narrowband interference additionally simulation results are presented illustrating the convergence performance of the receiver when the tap weights are adjusted using either the least mean square lms or recursive least squares rls adaptive algorithms

semiparametric bayesian inference for time series with mixed spectra summary a bayesian analysis is presented of a time series which is the sum of a stationary component with a smooth spectral density and a deterministic component consisting of a linear combination of a trend and periodic terms the periodic terms may have known or unknown frequencies the advantage of our approach is that different features of the data such as the regression parameters the spectral density unknown frequencies and missing observations are combined in a hierarchical bayesian framework and estimated simultaneously a bayesian test to detect deterministic components in the data is also constructed by using an asymptotic approximation to the likelihood the computation is carried out efficiently using the markov chain monte carlo method in o mn operations where n is the sample size and m is the number of iterations we show empirically that our approach works well on real and simulated samples

estimation of the parameters of an arma signal model based on an orthogonal search an iterative procedure for estimating the parameters of an arma signal model input not accessible is empirically compared to the results of several other algorithms the arma identifier reported includes inherent order estimation the empirical results indicate unbiased estimates with less variance than those obtained by the other methods

on the use of the singular value decomposition in the fast multipole method the authors present a new matrix compression algorithm to improve the efficiency of the fast multipole method fmm the method is based on the application of the singular value decomposition svd to the plane wave fmm aggregation matrices these matrices are low ranked which is exploited to provide alternative sets of orthonormal singular basis functions obtained as linear combinations of the original basis by choosing only the most relevant singular functions a much more compact representation is obtained to accurately handle the interactions between the fmm groups the new formulation provides a reduction close to one order of magnitude both in computational cost and memory requirements with a moderate impact on the accuracy of the solution

an iterative solution for electrically large problems combining the characteristic basis function method and the multilevel fast multipole algorithm an iterative scheme for the rigorous computation of electrically large problems is presented the approach is based on a combination of the characteristic basis function method cbfm and the multilevel fast multipole algorithm mlfma that can deal with very large problems that require an iterative solution process even considering that the application of the cbfm entails an important reduction of the number of unknowns when compared to method of moments approaches based on subdomain functions this reduction is due to the fact that the number of macro basis functions called characteristic basis functions cbfs is lesser than the number of low level subsectional functions used to sample the geometry in addition the use of the mlfma avoids the need to calculate and store the coupling terms in the reduced matrix that are not on or close to the diagonal thereby optimizing the cpu time and the memory storage requirements non uniform rational b splines nurbs surfaces are employed for the representation of the geometry and the cbfs are described in terms of curved rooftops generated in the parametric space the associated macro testing functions are defined as aggregations of curved razor blade functions

new efficient ls and svd based techniques for high resolution frequency estimation new least squares and singular value decomposition based methods for the estimation of the frequencies of complex sinusoids in white noise are presented the methods are based on a new symmetric prediction problem that has some very useful properties leading to algorithms that have considerably reduced complexity the new symmetric predictor is superior in performance as compared to the well known symmetric smoother and has a performance comparable to other well known methods finally a new ls based method which combines the new prediction technique with the fblp method is proposed this method performs slightly better than the fblp offering at the same time a significant computational saving as a by product in the derivation of the new methods is the establishment of some useful properties concerning the eigenstructure of hermitian and persymmetric matrices

complex coefficient nonrecursive digital filter design using a least squares method a method for the design of complex coefficient nonrecursive filters is described in this method a mean square error is formulated in a quadratic form the filter coefficients are obtained by solving a system of linear equations using computationally robust and efficient algorithms examples are presented to demonstrate the efficacy of our method

some thoughts on ando s theorem and parrott s example in this short note we present an elementary proof of ando s theorem within a restricted class p of homomorphisms modeled after parrott s example we also show by explicit estimation that the cb norm of the contractive homomorphism of the tri disc algebra induced by the commuting triple of parrott exceeds 1 indeed we construct a polynomial p with matrix coefficients with the property p p in particular we show that there are contractive homomorphisms of the tri disc algebra which are not even 2 contractive