Compressed Sensing & Sparse Filtering (Signals and Communication Technology)
| Author | : | |
| Rating | : | 4.43 (584 Votes) |
| Asin | : | 3642383971 |
| Format Type | : | paperback |
| Number of Pages | : | 502 Pages |
| Publish Date | : | 2016-11-03 |
| Language | : | English |
DESCRIPTION:
It should be of great value to research scientists in related fields, and it could help research and development engineers evaluate the impact these new methods could have in their work.” (Vladimir Botchev, Computing Reviews, February, 2014) . … This book presents cutting-edge research on one of the newest signal processing disciplines. From the reviews:“This book reports on the application of compressed sensing
Each methodology has its own formalities for dealing with such problems. . Compressed sensing techniques and homotopy-type solutions, such as the LASSO, utilise l1-norm penalties for obtaining sparse solutions using fewer observations than conventionally needed. Compressed sensing builds upon the observation that many signals in nature are nearly sparse (or compressible, as they are normally referred to) in some domain, and consequently they can be reconstructed to within high accuracy from far fewer observations than traditionally held to be necessary. Apart from compressed sensing this book contains other related approaches. This book is aimed at presenting concepts, methods and algorithms
"not an introduction to the topic of compressed sensing" according to TL. The book is said to be "aimed at presenting concepts, methods and algorithms able to cope with undersampled and limited data".In other words, it is about compressed sensing (CS). I bought it to learn about this topic. The Introduction (which I found on Springer'swebsite for this book) gives a paragraph-long description