Showing papers in "Signal Processing in 2006"

TL;DR: This paper proposes a greedy pursuit algorithm, called simultaneous orthogonal matching pursuit (S-OMP), for simultaneous sparse approximation, and presents some numerical experiments that demonstrate how a sparse model for the input signals can be identified more reliably given several input signals.

TL;DR: A concise survey of the literature on cyclostationarity is presented and includes an extensive bibliography and applications of cyclostatedarity in communications, signal processing, and many other research areas are considered.

TL;DR: This paper presents theoretical and numerical results for a greedy pursuit algorithm, called simultaneous orthogonal matching pursuit, and develops conditions under which convex relaxation computes good solutions to simultaneous sparse approximation problems.

TL;DR: Two sets of tuning rules for fractional PIDs are presented, quadratic and require the same plant time-response data used by the first Ziegler-Nichols tuning rule for (usual, integer) PIDs, to provide a starting point for fine tuning.

TL;DR: Two classes of rate-adaptive distributed source codes, both based on low-density parity-check (LDPC) codes, are developed and their design is studied, showing specific realizations to be better than alternatives of linear encoding and decoding complexity.

TL;DR: This paper deals with the application of fractional system identification to lead acid battery state of charge estimation and a new fractional model of the battery is proposed based on parameter variations of this model.

TL;DR: This paper presents several alternative methods for the control of power electronic buck converters applying fractional order control (FOC), and the fractional calculus is proposed in order to determine the switching surface applying a fractional sliding mode Control (FRSMC) scheme to theControl of such devices.

TL;DR: The filtering problem for a class of linear uncertain systems with Markovian jump parameters and functional time delay is examined and results for robust weak-dependent stochastic stability and robust linear filter design are provided.

TL;DR: This paper quantifies the 'sufficient sparsity' condition, defining an equivalence breakdown point (EBP), and describes a semi-empirical heuristic for predicting the local EBP at this ensemble of 'typical' matrices with unit norm columns.

TL;DR: The robust stability check problem for uncertain fractional-order linear time invariant (FO-LTI) systems with interval coefficients described in state space form is solved for the first time.

TL;DR: Wavelet-based partitioning approach for symbol generation is presented, instead of the currently practiced method of phase-space partitioning, and various aspects of the proposed technique, such as wavelet selection, noise mitigation, and robustness to spurious disturbances, are discussed.

TL;DR: This paper establishes here the stability of the BP in the presence of noise for sparse enough representations, and is a direct generalization of noiseless BP study, and indeed, when the noise power is reduced to zero, the known results of the noisless BP are obtained.

TL;DR: This work derives a simple and advanced algorithm for the optimum joint statistical adaptation of both filter coefficients in time-varying and noisy acoustic environments based on the Kalman filter theory.

TL;DR: The results show that, compared with conventional methods, the pitch determination method based on HHT well improves the accuracy and resolution of pitch recognition.

TL;DR: The results reveal that the least-squares approach gives similar or superior approximations in comparison with other widely used methods.

TL;DR: The well-known Shannon sampling theorem and previously developed sampling criteria for Fresnel and fractional Fourier transformed signals are shown to be a special cases of the theorem developed here.

TL;DR: In this approach, the FDEs are expressed in terms of Caputo type fractional derivative, and between two successive intervals the unknown functions are approximated using quadratic polynomials to obtain a set of equations.

TL;DR: The Burg-type Nuttall Strand method (multivariate Burg) for estimating MVAR parameters yielded the best results, and the Arfit estimates performed worst.

TL;DR: The proposed compression method combines the approximation scheme with a customized scattered data coding scheme, which is the Delaunay triangulation of a small set Y of significant pixels, and is compared with JPEG2000 on two geometric images and on three popular test cases of real images.

TL;DR: This paper presents a simple yet efficient algorithm for multifocus image fusion, using a multiresolution signal decomposition scheme based on a nonlinear wavelet constructed with morphological operations.

TL;DR: It turns out that the controllability check for FO-LTI systems amounts to checking the controLLability of conventional integer order state space, and the key is to check the linear dependency of a set of interval vectors.

TL;DR: This paper investigates a machine learning, descriptor-based approach that does not require an explicit descriptors statistical model, based on support vector novelty detection, and introduces a sequential optimization algorithm.

TL;DR: A simple and robust two-stage, non-coherent TOA estimation approach for positioning algorithms utilizing both noniterative and iterative techniques and a positioning algorithm for node location in multi-hop distributed networks is proposed.

TL;DR: PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables, and the introduced relationships between the models extend the collection of analysis tools for both model classes.

TL;DR: This paper describes a method for construction of fractional generalized splines through evaluating fractional finite differences and characterization of these functions in both time and frequency domain to reveal the suitability of the proposed basis functions for signal approximation.

TL;DR: This paper proposes to use a mixture approach, adaptively combining two independent LMS filters with large and small step sizes to obtain fast convergence with low misadjustment during stationary periods.

TL;DR: The fractional differencing method and weighted least squares approach are presented and an adaptive fractional order differentiator is developed and applied to estimate the parameters of 1/f noise from the finite observation data set.

TL;DR: A new high performance sparse adaptive algorithm is presented and comparative echo cancellation results are provided to show the relative performance of the existing and new algorithms.

TL;DR: This paper presents approximations which allow an efficient computation and compensation of the bias in moving average and first-order recursive smoothed psd estimates and discusses factors that influence the bias.