Results 31 to 40 of about 209,947 (320)
Revisiting matching pursuit: Beyond approximate submodularity
Signal Processing, 2023 We study the problem of selecting a subset of vectors from a large set, to obtain the best signal representation over a family of functions. Although greedy methods have been widely used for tackling this problem and many of those have been analyzed under the lens of (weak) submodularity, none of these algorithms are explicitly devised using such a ...
Tohidi, Ehsan +2 more
openaire +2 more sources
A Sparsity Preestimated Adaptive Matching Pursuit Algorithm
Journal of Electrical and Computer Engineering, 2021 In the matching pursuit algorithm of compressed sensing, the traditional reconstruction algorithm needs to know the signal sparsity. The sparsity adaptive matching pursuit (SAMP) algorithm can adaptively approach the signal sparsity when the sparsity is ...
Xinhe Zhang, Yufeng Liu, Xin Wang
doaj +1 more source
Model-Driven Deep-Learning-Based Underwater Acoustic OTFS Channel Estimation
Journal of Marine Science and Engineering, 2023 Accurate channel estimation is the fundamental requirement for recovering underwater acoustic orthogonal time–frequency space (OTFS) modulation signals.
Yuzhi Zhang +4 more
doaj +1 more source
Expectation maximization based matching pursuit [PDF]
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012 A novel expectation maximization based matching pursuit (EMMP) algorithm is presented. The method uses the measurements as the incomplete data and obtain the complete data which corresponds to the sparse solution using an iterative EM based framework. In standard greedy methods such as matching pursuit or orthogonal matching pursuit a selected atom can
Gurbuz, Ali Cafer +2 more
openaire +4 more sources
Improved Weighted Matching Pursuit based Channel Estimation Algorithm
Guangtongxin yanjiu, 2022 Compressive sensing based matching pursuit algorithm can estimate the channel state information of communication system with shorter pilot sequences. It has the advantages of lower computational complexity and less number of pilots.
Zhi-guo Lü, Meng QI, Hong-xiang SHAO
doaj +3 more sources
Mptk: Matching Pursuit Made Tractable [PDF]
2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings, 2006 Matching Pursuit (MP) aims at finding sparse decompositions of signals over redundant bases of elementary waveforms. Traditionally, MP has been considered too slow an algorithm to be applied to real-life problems with high-dimensional signals. Indeed, in terms of floating points operations, its typical numerical implementations have a complexity of O(N^
Krstulovic, Sacha, Gribonval, Rémi
openaire +2 more sources
Constrained Backtracking Matching Pursuit Algorithm for Image Reconstruction in Compressed Sensing
Applied Sciences, 2021 Image reconstruction based on sparse constraints is an important research topic in compressed sensing. Sparsity adaptive matching pursuit (SAMP) is a greedy pursuit reconstruction algorithm, which reconstructs signals without prior information of the ...
Xue Bi +5 more
doaj +1 more source
High resolution direction of arrival (DOA) estimation based on improved orthogonal matching pursuit (OMP) algorithm by iterative local searching. [PDF]
Sensors (Basel), 2013 Wang W, Wu R.
europepmc +3 more sources
Underdetermined noisy blind separation using dual matching pursuits [PDF]
, 2004 Underdetermined blind source separation is a key application in audio where it is desirable to extract multiple sources from a stereo recording. A new variant on the stereo matching pursuit, the dual matching pursuit, is presented whereby independent ...
Canagarajah, CN, Sugden, Paul
core +2 more sources
Dynamic Orthogonal Matching Pursuit for Sparse Data Reconstruction
IEEE Open Journal of Signal Processing, 2023 The orthogonal matching pursuit (OMP) is one of the mainstream algorithms for sparse data reconstruction or approximation. It acts as a driving force for the development of several other greedy methods for sparse data reconstruction, and it also plays a ...
Yun-Bin Zhao, Zhi-Quan Luo
doaj +1 more source