Compressed Sensing
Applications to Communication and Digital Signal Processing
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Beschreibung
This textbook focuses on applications of compressed sensing (CS) and sub-Nyquist sampling techniques to wireless communications such as multi-carrier, IMIMO, UWB, LTE, 5G, Internet of Things, and machine learning. Written for an engineering audience, the book is presented in a strictly mathematical manner, and to keep it self-contained and accessible to engineering students it explains all the mathematical tools used. It also develops a generalization of CS to more structured signal models, which is necessary in order to apply CS to digital communication. The work is based on research material collected by the authors over recent years.
This textbook focuses on applications of compressed sensing (CS) and sub-Nyquist sampling techniques to wireless communications such as multi-carrier, IMIMO, UWB, LTE, 5G, Internet of Things, and machine learning. Written for an engineering audience, the book is presented in a strictly mathematical manner, and to keep it self-contained and accessible to engineering students it explains all the mathematical tools used. It also develops a generalization of CS to more structured signal models, which is necessary in order to apply CS to digital communication. The work is based on research material collected by the authors over recent years.
Offers a generalization of compressed sensing to more structured signal models
Explains all the mathematical tools used
Presents numerous examples for wireless communication scenarios
Offers a generalization of compressed sensing to more structured signal models
Explains all the mathematical tools used
Presents numerous examples for wireless communication scenarios
Autor*in
Philipp Walk
Themen in »Compressed Sensing«
Compression Convolution DFT Frame Theory Inverse Problems OFDM Phase Retrieval Signal Processing Sparse Signal Models Sub-Nyquist Sampling Techniques