The extremely high sampling rate is a challenge for ultra-wideband (UWB) communication. In this paper, we study the compressed sensing (CS) based impulse radio UWB (IR-UWB) signal detection and propose an IR-UWB signal detection algorithm based on compressive sampling matching pursuit (CoSaMP). The proposed algorithm relies on the fact that UWB received signal is sparse in the time domain. The ...

Sign truncated matching pursuit (STrMP) algorithm is presented in this paper. STrMP is a new greedy algorithm for the recovery of sparse signals from the sign measurement, which combines the principle of consistent reconstruction with orthogonal matching pursuit (OMP). The main part of STrMP is as concise as OMP and hence STrMP is simple to implement. In contrast to previous greedy algorithms f...

We shall show that if the restricted isometry constant (RIC) δs+1(A) of the measurement matrix A satisfies δs+1(A) < 1 √ s+ 1 , then the greedy algorithm Orthogonal Matching Pursuit(OMP) will succeed. That is, OMP can recover every s-sparse signal x in s iterations from b = Ax. Moreover, we shall show the upper bound of RIC is sharp in the following sense. For any given s ∈ N, we shall construc...

A large number of pilots are utilized to acquire channel information in traditional channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) system, which leads to lower spectrum efficiency. For exploiting the sparse channel characteristics of 3GPP multipath channels, we employ the Compressed Sensing (CS) approach for channel estimation. Two CS-based recovery algorithms, Orthogo...

Two of the most fundamental prototypes of greedy optimization are the matching pursuit and FrankWolfe algorithms. In this paper, we take a unified view on both classes of methods, leading to the first explicit convergence rates of matching pursuit methods in an optimization sense, for general sets of atoms. We derive sublinear (1/t) convergence for both classes on general smooth objectives, and...

We show that the vector quantizer (VQ) techniques can be used to optimize a matching pursuit dictionary and improve the PSNR performance at low bitrates. The basis functions are the shape part, and the inner product values are the gain part of the VQ. The performance is evaluated based on a comparison of the PSNR in encoding motion residuals obtained using a matching pursuit coder with a refere...

Factorization of polyphonic musical signals remains a difficult problem due to the presence of overlapping harmonics. Existing dictionary learning methods cannot guarantee that the learned dictionary atoms are semantically meaningful. In this paper, we explore the factorization of harmonic musical signals when a fixed dictionary of harmonic sounds is already present. We propose a method called ...

Sparse coding in a redundant basis is of considerable interest in many areas of signal processing. The problem generally involves solving an under-determined system of equations under a sparsity constraint. Except for the exhaustive combinatorial approach, there is no known method to find the exact solution for general dictionaries. Among the various algorithms that find approximate solutions, ...

In this study, we propose and apply a kind of novel subspace pursuit method to guided wave Non-Destructive Testing (NDT) signal decomposition and recognition to reduce the complexity of subspace pursuit. Modified Differential Evolution Algorithm (MDEA) is applied to the Modified Subspace Pursuit (MSP) by choosing chirplet function as match atoms. A steel pipe with hole and notch is detected by ...

We introduce two models for predicting the rate and distortion of the matching pursuit video codec. The rst model is based on a pre-coding analysis pass using the full matching pursuit dictionary. The second model is based on a reduced-complexity analysis pass. We evaluate these models for use within existing rate-distortion optimization techniques. Our prediction results suggest that the model...