Results 231 to 240 of about 15,595 (260)

Adaptive Quantization for Matching Pursuit

2006 IEEE Workshop on Multimedia Signal Processing, 2006
We propose an adaptive quantization scheme for matching pursuit. Different quantizers are used in different matching pursuit (MP) stages based on the probability distribution of MP coefficients. The quantizers are optimized for a given rate budget constraint.
Alireza Shoa, Shahram Shirani
openaire   +1 more source

Oblique Projection Matching Pursuit

Mobile Networks and Applications, 2016
Recent theory of compressed sensing (CS) tells us that sparse signals can be reconstructed from a small number of random samples. In reconstruction of sparse signals, greedy algorithms, such as the orthogonal matching pursuit (OMP), have been shown to be computationally efficient.
Jian Wang 0016, Feng Wang 0008, Yunquan Dong, Byonghyo Shim   +3 more
openaire   +1 more source

Random Matching Pursuit for Image Watermarking

IEEE Transactions on Circuits and Systems for Video Technology, 2019
The classical solution to an underdetermined system of linear equations mainly has two opposite directions, which lead to either a large $\ell _{2}$ -norm sparse solution or a non-sparse minimum $\ell _{2}$ -norm solution. In this paper, we systematically show that by modifying the well-known basic matching pursuit algorithm originally ...
Guang Hua 0001, Lifan Zhao, Haijian Zhang, Guoan Bi, Yong Xiang 0001   +4 more
openaire   +2 more sources

Refining Kernel Matching Pursuit

2010
Kernel matching pursuit (KMP), as a greedy machine learning algorithm, appends iteratively functions from a kernel-based dictionary to its solution An obvious problem is that all kernel functions in dictionary will keep unchanged during the whole process of appending It is difficult, however, to determine the optimal dictionary of kernel functions ...
Jianwu Li, Yao Lu 0001
openaire   +1 more source

The design of matching pursuit filters

Network: Computation in Neural Systems, 1998
This paper presents a new technique for creating efficient and compact models from data, called matching pursuit filters. The design of a matching pursuit filter is based on an adapted wavelet expansion, where the expansion is adapted to both the data and the pattern recognition problem being addressed.
openaire   +3 more sources

Covariance-Assisted Matching Pursuit

IEEE Signal Processing Letters, 2016
We consider the problem of greedy sparse approximation in the presence of noise, given a-priori knowledge of the sparse coefficients’ covariance and mean. The proposed Covariance-Assisted Matching Pursuit (CAMP) combines the a-priori knowledge by leveraging the Gauss-Markov theorem, and provides significantly better performance than the classical ...
openaire   +1 more source

Probabilistic Orthogonal Matching Pursuit

2022 IEEE International Conference on Big Data (Big Data), 2022
Ghazal Fazelnia, John W. Paisley
openaire   +1 more source

System Identification by Matching Pursuit and Orthogonal Matching Pursuit

2022 International Conference on Machine Learning and Intelligent Systems Engineering (MLISE), 2022
openaire   +1 more source

Parallel Matching Pursuit Algorithm and Analysis

SSRN Electronic Journal, 2022
Wenbiao Tian, Guosheng Rui, Song Zhang, Haibo Zhang   +3 more
openaire   +1 more source

Efficient Implementations for Orthogonal Matching Pursuit

Electronics (Switzerland), 2020
Hufei Zhu, Yanpeng Wu, Wen Chen
exaly