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This paper deals with the robust mixed [H.sub.2]/[H.sub.[infinity]] filtering problem with regional pole assignment for linear uncertain discrete-time systems in the presence of two sets of exogenous disturbance inputs. A general framework for solving this problem is established using a linear matrix inequality (LMI) approach in conjunction with regional pole constraints, and [H.sub.2] and [H.sub.[infinity]] optimization characterization. Necessary and sufficient conditions for the solvability of the problem are given in terms of a set of feasible LMIs. A numerical example is provided to illustrate the effectiveness of the proposed design algorithm. Index Terms--Linear matrix inequality, quadratically D-stable, regional pole assignment, robust mixed [H.sub.2]/[H.sub.[infinity]] filtering.

This paper proposes two frequency based methods for parallel active filtering of current harmonics in utility grids. Active filter (AF) reference prediction and AF current control are the two key-points to obtain high performances. This paper deals with the AF reference prediction. The two proposed methods are based on the Fourier Series and its implementation on Dsp. They. belong to two prediction structures: 1) the open-loop structure which predicts the reference currents from the load currents; 2) the closed-loop structure which predicts the reference currents from the grid currents. Fourier Series based methods are very flexible and have several interesting properties. These two methods have been successfully implemented and tested. The latter method cancels permanent errors and results in better performances. Both methods are very flexible. Index Terms--Active power filtering, closed loop, FFT.

This paper studies the effect of noise at the input channel on the recursive algorithms recently proposed for designing adaptive filters subject to output envelope constraints. It is found that such an adaptive filter may suffer serious performance degradation due to the use of noisy input signal measurements in the filter update equation. To reduce the noise effect, it is proposed to smooth the noisy input signal by averaging over several recent input signal measurements. Numerical results show that a desirable performance improvement can be achieved using such a moving average window. Keywords: Adaptive signal processing; Finite impulse response filter design; Envelope-constrained filters; Constrained optimization; Noisy signals

One-dimensional sections of digital images with space-variant blurs from an uncorrected optical system are restored using Wiener filtering and the Richardson-Lucy method. The simulated blur is from a single-lens optical system configured at moderate focal-length-to-aperture ratio (f#) and near-infinite conjugate. The sections are taken over a range of field-angle displacements from on-axis to approximately 15-deg off-axis. The results identify a range of field angles over which Wiener filtering is useful for sectioned restoration of blurred images from an optical system with significant point-spread-function space-variance. The results also establish a field angle range over which an iterative restoration method such as Richardson-Lucy would be necessary to accommodate point-spread-function space-variance. Index Terms--Image restoration, Richardson-Lucy method, space-variant point-spread-function, Wiener filtering.

This paper examines the success of RF filtering on mitigating interference that occurs between two wireless multiple-access systems operating within the same geographic area. Such interference is referred to as 'competitor-induced interference' and can significantly degrade system capacity and performance. Three dual-system scenarios are considered: a dual code-division multiple-access (CDMA) (IS-95) system, a CDMA mobile in an FM (AMPS) cell, and an FM mobile in a CDMA cell. Index Terms--CDMA, cellular system capacity, intermodulation, RF filters, superconductor filters.

We investigate the data-parallel implementation of a set of 'information filters' used to rule out uninteresting data from a database or data stream. We develop an analytic model for the costs and advantages of load rebalancing for the parallel filtering processes, as well as a quick heuristic for its desirability. Our model uses binomial models of the filter processes and fits key parameters to the results of extensive simulations. Experiments confirm our model. Rebalancing should pay off whenever processor communications costs are high. Further experiments showed it can also pay off even with low communications costs for 16-64 processes and 1-10 data items per processor; then, imbalances can increase processing time by up to 52 percent in representative cases, and rebalancing can increase it by 78 percent, so our quick predictive model can be valuable. Results also show that our proposed heuristic rebalancing criterion gives close to optimal balancing. We also extend our model to handle variations in filter processing time per data item. Index Terms--information filtering, data parallelism, load balancing, information retrieval, conjunctions, optimality, and Monte Carlo methods.

Evoked potentials (EPs) are time-varying signals typically buried in relatively large background noise. To extract the EP more effectively from noise, we had previously developed an approach using an adaptive signal enhancer (ASE) (Chen et al, 1995). ASE requires a proper reference input signal for its optimal performance. Ensemble- and moving window-averages were formerly used with good results. In this paper, we present a new method to provide even more effective reference inputs for the ASE. Specifically, a Gaussian radial basis function neural network (RBFNN) was used to preprocess raw EP signals before serving as the reference input. Since the RBFNN has built-in nonlinear activation functions that enable it to closely fit any function mapping, the output of RBFNN can effectively track the signal variations of EP. Results confirmed the superior performance of ASE with RBFNN over the previous method. Index Terms--Adaptive signal enhancer (ASE), evoked potential, radial basis function neural network (RBFNN), SNR.

We continue the study of adaptive schemes for the sequential lossy coding of individual sequences which was recently initiated by Linder and Lugosi. Specifically, we consider fixed-rate lossy coding systems of fixed (or zero) delay where the encoder (which is allowed to use randomization) and the decoder are connected via a noiseless channel of a given capacity. It is shown that for any finite set of such coding schemes of a given rate, there exists a source code (adhering to the same structural and delay limitations) with the same rate whose distortion is with high probability almost as small as that of the best scheme in that set, uniformly for all individual sequences. Applications of this result to reference classes of special interest are outlined. These include the class of scalar quantizers, trellis encoders with sliding block decoders, and differential pulse code modulator (DPCM)-based source codes. In particular, for the class of all scalar quantizers, a source code is obtained with (normalized) distortion redundancy relative to the best scheme in the reference class of order [n.sup.-1/3] log n (where n is the sequence length). This improves the [n.sup.-1/5] log n rate achieved by Linder and Lugosi. More importantly, the decoder here is deterministic and, in particular, does not assume a common randomization sequence available at both encoder and decoder. Finally, we consider the case where the individual sequence is corrupted by noise prior to reaching the coding system, whose goal now is to reconstruct a sequence with small distortion relative to the clean individual sequence. It is shown that for the case of a finite alphabet and an invertible channel transition probability matrix, for any finite set of sliding-window schemes of a given rate, there exists a source code (allowed to use randomization yet adhering to the same delay constraints) whose performance is, with high probability, essentially as good as the best scheme in the class, for all individual sequences. Index Terms--Individual sequences, limited-delay coding, lossy source coding, noisy source coding, sequential coding, universal coding.

A novel technique for automated filter tuning is introduced. The filter to be tuned is represented by a generalized filter low-pass prototype model rather than a specialized equivalent network. The prototype model is based on the minimum number of characteristic filter parameters to represent the filter transfer function correctly. The parameter values are found from a gradient-based parameter-extraction process using measured S-parameters. Automated filter tuning is performed as a two-step procedure. First, the parameter sensitivities with respect to the tuning elements are determined by a series of S-parameter measurements. Second, the parameter values of the filter are compared to the values of the ideal filter prototype found from a filter synthesis, thus yielding the optimal screw positions. This novel tuning technique has been tested successfully with direct coupled three-resonator and cross-coupled four- and six-resonator filters. Index Terms--Automated tuning, CAD, gradient methods, parameter estimation, sensitivity analysis, waveguide filter.

The creation of the tri-state median (TSM) filter is analyzed, focusing on the filter's ability to preserve an image's details while suppressing noise. The authors discuss their use of center weighted median filters and standard median filters to improve their noise detection structure.

Research regarding the use of L(p) norms to design optimal stack filters is evaluated. Topics include a review of past designs of stack filters, and a discussion of how optimal stack filters can efficiently restore corrupted images.

A new, simplified technique for image processing is presented, which utilizes an embedded zerotree wavelet structure for M-channel linear phase perfect reconstruction filterbanks. The process offers higher energy compaction and finer partitioning of the frequency spectrum.

In the present letter, we investigate the asymptotic performance of a multi-input multi-output decision-feedback (DF) equalizer used to detect a multicarrier (MC) signal based on a filter bank and transmitted over a linear dispersive channel. We derive the optimum DF structure for a minimum-mean square-error criterion. We basically show that with infinite length forward and feedback filters and at high signal-to-noise ratio, the geometrical mean of prediction errors does not depend on the paraunitary filter bank used in the transmitter. Hence, it appears that uncoded filter-bank based MC transmission and single carrier transmission, both used over the same channel and with optimum DF, lead to the same achievable bit rate. Index Terms: Decision-feedback equalization, filter bank, MIMO, multicarrier transmission.

This paper presents a single-user code timing estimation algorithm for direct-sequence code-division multiple access that is based on processing the weight vector of an adaptive filter. The filter weight vector can be shown to adapt in the mean to a scaled time-shifted version of the spreading code of the desired user. Therefore, our algorithm requires very little side information in order to form its estimate. The acquisition performance of the algorithm is investigated when the filter is adapted using the least mean square (LMS) or the recursire least square (RLS) algorithm. The proposed algorithm is shown through experimental results to be resistant to the near-far problem when the RLS adaptation algorithm is used, but not when the LMS algorithm is used. However, the performance of this code-acquisition technique is still substantially better than the traditional correlator-based approach, even when the computationally simple LMS algorithm is used. As an extension to the basic timing estimator algorithm, we consider the effect of frequency synchronization error on the performance of the timing estimate. As expected, frequency-offset error degrades the performance of the timing estimate. However, a modified version of the adaptive filter is presented to combat this effect. Index Terms - Adaptive equalizers, code-division multiaccess, synchronization.

Recursive (online) expectation-maximization (EM) algorithm along with stochastic approximation is employed in this paper to estimate unknown time-invariant/variant parameters. The impulse response of a linear system (channel) is modeled as an unknown deterministic vector/process and as a Gaussian vector/process with unknown stochastic characteristics. Using these models which are embedded in white or colored Gaussian noise, different types of recursive least squares (RLS), Kalman filtering and smoothing and combined RLS and Kalman-type algorithms are derived directly from the recursive EM algorithm. The estimation of unknown parameters also generates new recursive algorithms for situations, such as additive colored noise modeled by an autoregressive process. The recursive EM algorithm is shown as a powerful tool which unifies the derivations of many adaptive estimation methods. Index Terms - Adaptive estimation, colored noise, estimation and maximization algorithm, estimation theory, Kalman filtering, maximum-likelihood estimation, recursive estimation.

A low-sensitivity temperature-compensated programmable BJT current-mode low-voltage filtering technique is proposed. We introduce a new technique in which the dc gain and the location of the second pole of the integrator are controlled such that the Q-enhancement, due to the second pole, is canceled by the effect of finite dc gain. The technique is suitable for integration and can work with low-value capacitors. By making the filter time constant exactly proportional to [r.sub.e]C, good linear tunability is achieved over many decades. The programming current is varied as proportional to absolute temperature (PTAT) to stabilize the time constant [r.sub.e]C. Index Terms - Continuous-time filters, current-mode integrators, Q sensitivity.

A control strategy which allows conventional voltage-source current-controlled (VSCC) pulsewidth modulation (PWM) rectifiers to work simultaneously as active power filters is presented. The proposed control strategy also allows compensating the system power factor and compensating unbalanced loads. The measurement and/or calculation of the harmonics and reactive power are not required, making the proposed control scheme very simple. The active front-end rectifier acts directly on the mains line currents, forcing them to be sinusoidal and in phase with the mains voltage supply. To improve the dynamic of the system, the amplitude of the current is controlled by a fuzzy system, which adjusts the dc-link voltage of the PWM rectifier. The strategy is based on connecting all the polluting loads between the PWM rectifier and their input current sensors. The main advantages of this approach are the following: 1) there is no need to install a specially dedicated active power filter; 2) it also works simultaneously as power factor compensator; and 3) no special and complicated calculations are required for harmonic elimination. The viability of the proposed active front-end rectifier is proved by simulation and with experimental results obtained from a 2-kVA PWM prototype.

Nonlinear anisotropic diffusion algorithms provide significant improvement in image enhancement as compared to linear filters. However, the excessive computational cost of solving nonlinear PDEs precludes their use in real-time vision applications. In the present paper, we show that two orders of magnitude speed improvement is provided by a new image filtering paradigm in which an adaptively determined vector field specifies nonlocal application points for an image filter. Index Terms - Segmentation, diffusion, scale-space, anisotropic diffusion, nonlinear diffusion, filtering, permutation filter, nonlocal filter.

An algorithm derived from pseudo-linear regression and based on QR matrix decomposition was developed for adaptive infinite impulse response filtering. Its application was observed to result in the identification of the minimized pseudo-linear approximation of the squared output error. Simulation testings, on the other hand, revealed that this algorithm is highly stable and has excellent convergence properties.

In this paper, a textured image is considered to be produced by a smooth signal, representing in part the illumination environment, modulated by some frequencies determined by surface characteristics of the textures. Through expansion of the smooth signal into wavelets, a textured image may be decomposed into modulated "wavelets" providing multiresolution information. It is shown that the corresponding wavelet coefficients can be obtained efficiently by using the standard wavelet transform while the associated h and g filters are modulated accordingly. A set of multichannel filters is designed through the use of a modulated "wavelet" multiresolution decomposition, providing both spatial frequency and orientation selectivity. based on these multichannel amplitude responses as discriminating features, an image containing multiple textures can be effectively segmented. The potential of this approach is shown by experimental results. Index Terms - Modulated wavelets, texture segmentation, wavelet transform.

An adaptive, nonlinear image domain filtering strategy is described which improves positron emission tomography (PET) images. The method was formulated to improve on the linear, low-pass filtering typically applied to each projection in the filtered back-projection (FBP) reconstruction algorithm. The algorithm is a potential alternative to linear smoothing which reduces noise but degrades resolution; this method uses the FBP algorithm for reconstruction, but aims to incorporate some of the statistical information and nonlinear smoothing utilized in iterative reconstruction algorithms. The approach uses sinogram segmentation to separate the sinogram elements with higher and lower signal-to-noise ratios, and then reconstruct each with FBP using a more appropriate choice of filter and cut-off frequency. Also, this algorithm addresses the radial streak artifacts introduced by FBP. The algorithm was evaluated using simulations and clinical data of cardiac PET studies on an ECAT 931 PET scanner. The initial results suggest that this technique has advantages over the current clinical protocol. Images processed with the method show generally improved visual image quality and reduced radial streaks without the introduction of artifacts. In simulations, increased contrast recovery and resolution are realized without an increase in the background noise of the reconstructed images.

A finite impulse response (FIR) filtering technique based on the impulse response rounding approach was developed. This method uses a simple recursive equation to estimate an equiripple FIR via the rounding operation and application of the derived impulse response. Test results revealed the technique's applicability in lowpass, highpass, bandpass and bandstop filters characterized by low edge frequencies and sharp transitions.

A simple yet effective algorithm called Weighted Fourier transform and RELAXation (WRELAX) is developed to solve a time delay estimation problem. This approach simplifies a complicated nonlinear least squares criterion using relaxation techniques. It utilizes an ultra-wideband ground-penetrating radar to identify and classify roadway subsurface defects. Experimental and numerical examples on the performance of the algorithm are presented.

Innovative techniques can be utilized in designing optimum finite impulse response (FIR) compaction filters which are suitable for a restricted class of signals. One of the methods utilizes Levinson recursion and two spectral factorization of half the filter order which may yield a two-channel FIR filter bank that optimizes the coding gain under conventional quantization noise assumptions while the window method may provide efficient suboptimal design. The methods are useful in important signal processing applications.

The innovative least squares design methodology can be utilized in approximating perfect reconstruction filter banks which may avoid complex design constraints. The methodology allows the selection of subband filters from the class of rational filters. The design procedure is applicable in obtaining least square synthesis filters from a set of analysis filters despite various numerical limitations in spectral factorization.

An innovative algorithm can be utilized in designing a class of linear-phase paraunitary filter banks with generalized length. The properties of such class of filter banks and the lattice factorizations for filter banks have been identified by utilizing the innovative algorithms. The permissible distributions of the filter banks' length and symmetry polarity among the channels have been identified in the design process.

Effective schemes can be utilized in the computation of a large number of varying scaled/oriented filtered versions of an image. The schemes allow the effective implementation of deformable filter banks based on the use of separable basis filters and multirate implementation. The filter bank, which is placed in a pyramidal structure and designed under a new multirate error criterion which decreases the approximation error and the shift variable, can be utilized in various image processing applications.

Instances of maximally flat digital filters include the maximally flat finite impulse response, infinite impulse response and 'allpass sum' orthogonal flat filters. The solutions for the rational function of an orthogonal infinite impulse response are the intermediate between the Daubechies and Butterworth wavelets where the two together with intermediate solution are unified by a single formula.

An analysis was presented which was aimed at constructing biorthogonal the wavelet bases that start from any two multiresolutions instead of conventional approach. The geometric approach can be utilized in constructing biorthogonal wavelets which contain desired properties and time shape. The desired properties and time shaped can also be expressed by utilizing fast filter bank algorithms.

The Grobner basis computation and computer algebra techniques can be utilized in computing algebraic properties of multivariate polynomials involved in the design of two-dimensional filter banks. By using these techniques, the design of the filter banks yield optimum frequency characteristics such as orthogonality, linear phase features and wavelet bases. Such filter banks are necessary in enhanced signal processing applications.

An analysis was presented to derive a sufficient condition for the M-channel perfect reconstruction filter banks to construct M-channel biorthogonal bases of compact wavelets. The analysis showed that lowpass filters in the perfect reconstruction filter bank must satisfy a regularity condition. Pn the other hand, the bandpass and highpass filters must satisfy the admissibility condition.

An innovative technique in signal processing which utilizes a wavelet transform may be used to compute velocity estimates which are represented by spatiotemporal signals. The technique involves the characterization of scaling and wavelet functions. The method involves two approaches which may generate a class of wavelet and scaling function with compact support and may be used in dealing with numerical instability.

An investigation was conducted to determine the structure and efficiency of the enhanced receivers' design for transmultiplexers-based high bit rate transmission over dispersive channels. The receivers' design involves linear and decision-feedback fractionally spaced detectors which function as modified filter banks. The enhanced receivers can be useful in digital transmission applications with signal detection problems.

The design of the hybrid filter banks allows the utilization of both digital and analog filters which may improve the speed and resolution of signal conversion compared to conventional signal conversion techniques. The hybrid filter banks utilize innovative design algorithms which contribute in the filter banks enhanced performance. The filter banks, which have sufficient stopband attenuation, are also designed to overcome analog inaccuracies.

A study was presented to discuss the design methods of the oversampled cosine-modulated filter banks with integer oversampling factors and arbitrary delay features. The filter banks features' such as the system delay and oversampling can be effective in real-time applications and filter design process. The new filter banks also have higher stopband attenuations compared to other filter banks' design.

Orthogonal transmultipexers can be utilized in an array of single and multiuser communications systems and other telephony applications. Various transmultiplexer structures such as the code division multiple access, frequency division multiple access and time division multiple access are also effective in various communications applications. The efficiency of communications systems that use such schemes can abe attributed to the transmultiplexers' orthogonality.

A study was conducted to evaluate the efficiency of the design of signal-adapted finite impulse response (FIR) paraunitary filter banks which are based on the energy compaction criterion. The innovative filter banks' optimal filters can be utilized in solving linear semi-infinite programming problems. However, the method of designing such optimal filter banks may not be appropriate in multidimensional FIR filter banks due to lack of spectral factorization.

Two-dimensional finite impulse response (FIR) principle components filter banks can be utilized in various applications such as data storage, model reduction, feature extraction, pattern classification and segmentation. The filter banks have maximum energy compaction feature and they optimizes the arithmetic mean ratio of subband variance. Although the innovative filter banks can be effective in various applications, they still have limitations.

The integration of the filter bank structure and Laguerre transform has yielded the extensions of the wavelet transform scheme which allows the implementation of orthogonal or biorthogonal warped wavelets. The warped wavelet bases are generated from the discrete-time warped wavelets and by extending the theory, pitch-synchronous warped wavelets can be analyzed. The properties of the wavelets are useful in understanding signal processing problems such as signal identification, denoising and feature detection.

The innovative type of linear filter which is designed based on the properties of the discrete Zak transform can be utilized for filtering applications in subband decomposition, decimation, interpolation and perfect reconstruction of signals. The filters do not observe complex restrictions on the impulse compared to conventional filters. Such filtering technique offers enhanced applicability in image and signal processing applications.

Arrays with good correlation properties are required for coded-aperture imaging, as well as for other applications of two-dimensional signal processing. Since binary arrays with perfect periodic autocorrelation functions exist for only a few sizes, mismatched filtering is discussed. Mismatched filtering entirely suppresses any sidelobes of the periodic autocorrelation function at the expense of a slightly reduced signal-to-noise ratio. New construction methods for binary arrays are presented for which this loss, with respect to periodic or odd-periodic correlation, converges to zero with an increasing array size.

Research has established a novel two-dimensional optimum block stochastic gradient algorithm for two-dimensional adaptive finite impulse response filtering in image reconstruction. A space-varying convergence factor is used for filter coefficient processing to reduce the posterior estimation error vector. The technique is superior to other two-dimensional optimum block adaptive algorithms.

Gabor filters are preprocessing stages in image-processing and computer-vision applications. One drawback is that they are computationally intensive on a digital computer. This paper describes the design of cellular neural networks (CNN's) which compute the outputs of filters similar to Gabor filters. Analog VLSI implementations of these CNN's might eventually relieve the computational bottleneck associated with Gabor filtering image-processing algorithms. The CNN's compute both the real and imaginary parts of the filter outputs simultaneously, which is an important feature in applying them in algorithms utilizing the phase of the Gabor output. Index Terms - Analog circuits, cellular neural networks, filtering, image processing, neural networks.

An inherent characteristic of most translinear (TL) filters is instantaneous companding. This brief describes a distortionless syllabic companding TL filter based on the 'analog floating-point technique' [1]. Through the addition of a compensation current to each of the capacitances in the filter, distortion is eliminated. By applying syllabic companding to a TL filter, the input current can be much larger than the quiescent current, thus increasing the dynamic range. Index Terms - Companding, continuous-time filters, current-mode.

A study was conducted to investigate the aspects of the pulse elongation and deconvolution (PED) filtering approach which is suitable for medical ultrasonic imaging. The method used was the analysis of the system model of the new method. Results showed that PED may improve the signal-to-noise ratio of a medical ultrasonic image without increasing the excitation voltage or the input of the imaging system.

An investigation was conducted to determine the effects of parameters on the ultrasonic system and the signal processing algorithm on the dynamic range and sensitivity of the multiresolution strain filter. The methods used were the formulation of correlation coefficient among the variables and the simulation of RF echo signals. Results revealed that a multiresolution strain filter can be utilized as an effective quantitative measure for the evaluation of elastographic imaging systems.

A technique on how to achieve a nonlinear phase surface acoustic wave (SAW) filter includes the use of slanted finger interdigital (SFITs) or tapered interdigital transducers. These interdigital transducers are suitable for wide band filter applications in different intermediate frequency stages. The SAW filters which utilize SFITs may provide low ripples in the passband compared to conventional filters.

Consider the response of an unstable LTI filter to an input over a time interval [0, T]. The total response consists of the signal response and the natural response of the filter. The latter grows exponentially so that an unstable filter is not usable. This note shows that by holding the final value of the filter fixed to a finite value (say, zero), the natural response can be forced to be negligible over some initial part of the time interval [0, T] so that the filter can be used. A means of implementing this idea is to reverse the input signal across the interval [0, T] as suggested in [1]-[3]. The purpose of this brief is to present a state-variable perspective of this technique. An example is shown to implement a filter with no phase shifts.

In blind adaptation the dynamics of an unknown channel (system) is recovered together with the transmitted symbol sequence (input signal). This paper generalizes a previous algorithm, that is not derived by criterion minimization, to include adaptive regressor filtering. The resulting scheme, which adapts a finite-dimensional IIR channel model, is designed to converge only to a well-defined set of parameters when binary symbols are transmitted over the channel. This provides a partial solution to the recently discussed ill - convergence problem in blind adaptation. Some connections to adaptive control theory are noted. Index Terms Blind equalization, convergence analysis, nonlinear systems, Wiener model.