Matching pursuit is an iterative method whereby a signal is decomposed into a linear combination of functions that are selected from a redundant dictionary. In the original paper by Mallat and Zhang [1], a dictionary of Gabor functions is proposed. Each Gabor function is the product of a Gaussian function with a complex sinusoid, and is specified by time, frequency and scale. Since these functi...

Straightforward combination of tree search with matching pursuits, which was suggested in 2001 by Cotter and Rao, and then later developed by some other authors, has been revisited recently as multipath matching pursuit (MMP). In this comment, we would like to point out some major issues regarding this publication. First, the idea behind MMP is not novel, and the related literature has not been...

In this paper transitional speech segments modeling by matching pursuit is proposed. The dictionary for matching pursuit is composed of wavelet functions that implement of psychoacoustic adaptive wavelet filter bank. Psychoacoustically motivated entropy based cost functions allow to greatly minimizing a number of time-frequency atoms in wavelet packet (WP) dictionary. The given transient modeli...

This paper proposes a novel matching pursuit generalized approximate message passing (MPGAMP) algorithm which explores the support of sparse representation coefficients step by step, and estimates the mean and variance of non-zero elements at each step based on a generalized-approximate-message-passing-like scheme. In contrast to the classic message passing based algorithms and matching pursuit...

|The use of matching pursuit (MP) to code video using over-complete Gabor basis functions has recently been introduced 8]. In this paper, we propose new functionalities such as SNR scalability and arbitrary shape coding for video coding based on matching pursuit. We improve the performance of the baseline algorithm in 8] by proposing a new search and a new position coding technique. The resulti...

Rigorous simulations of quantum tunneling dynamics in model systems with up to 20 coupled degrees of freedom are reported. The simulations implement an extension of the recently developed matching-pursuit/split-operator Fourier-transform method to complex-valued coherent-state representations. The resulting method recursively applies the time-evolution operator, as defined by the Trotter expans...

Matching pursuit is a general and exible method for solving an optimization problem that is of interest in signal analysis, coding, control theory and statistics. In this paper, principles of rate-distortion optimal coding are used in combination with matching pursuit algorithm to obtain an enhanced fractal image coding method. The advantages of using such a method over traditional fractal imag...

This paper addresses the problem of image representation based on a sparse decomposition over a learned dictionary. We propose an improved matching pursuit algorithm for Multiple Measurement Vectors (MMV) and an adaptive algorithm for dictionary learning based on multi-Singular Value Decomposition (SVD), and combine them for image representation. Compared with the traditional K-SVD and orthogon...

The use of matching pursuit (MP) to code video using overcomplete Gabor basis functions has recently been introduced. In this paper, we propose new functionalities such as SNR scalability and arbitrary shape coding for video coding based on matching pursuit. We improve the performance of the baseline algorithm presented earlier by proposing a new search and a new position coding technique. The ...

In this paper, the application of the emerging compressed sensing (CS) theory and the geometric characteristics of the targets in radar images are investigated. Currently, the signal detection algorithms based on the CS theory require knowing the prior knowledge of the sparsity of target signals. However, in practice, it is often impossible to know the sparsity in advance. To solve this problem...