Compressed Sensing and Dictionary Learning

Ke-Lin Du () and M. N. S. Swamy
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Ke-Lin Du: Concordia University, Department of Electrical and Computer Engineering
M. N. S. Swamy: Concordia University, Department of Electrical and Computer Engineering

Chapter Chapter 18 in Neural Networks and Statistical Learning, 2019, pp 525-547 from Springer

Abstract: Abstract Sparse coding is a matrix factorization technique. It models a target signal as a sparse linear combination of atoms (elementary signals) drawn from a dictionary (a fixed collection). Sparse coding has become a popular paradigm in signal processing, statistics, and machine learning. This chapter introduces compressed sensing, sparse representation/sparse coding, tensor compressed sensing, and sparse PCA.

Date: 2019
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DOI: 10.1007/978-1-4471-7452-3_18

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