Title :
The method on compression sampling and reconstruction of test signal
Author_Institution :
Sch. of Electron. Inf. & Control Eng. Sch., Beijing Univ. of Technol., Beijing, China
Abstract :
For solving the problem on feature extraction of test signal in high-dimensional space, the compression sampling and reconstruction method based on sparse signal is presented here. Test signal is denoted with sparse representation in specific transform domain, the observation matrix which is unrelated to transform-based is constructed for compressed sampling, Data dimension reduction and signal feature extraction are completed simultaneously, and these discrete data can reconstruct the test signal in compression domain by norm optimization technology perfectly. An illustration verify this method finally.
Keywords :
feature extraction; matrix algebra; signal reconstruction; signal representation; signal sampling; compression sampling method; data dimension reduction; high-dimensional space; norm optimization technology; observation matrix; signal feature extraction; sparse signal representation; test signal reconstruction method; Compressed sensing; Matching pursuit algorithms; Noise measurement; Optimization; Signal reconstruction; Sparse matrices; Transforms; Compressed Sampling; Observation Matrix; Signal Reconstruction; Sparse Representation;
Conference_Titel :
Electronics and Information Engineering (ICEIE), 2010 International Conference On
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-7679-4
Electronic_ISBN :
978-1-4244-7681-7
DOI :
10.1109/ICEIE.2010.5559781