Title :
Reconstruction from random measurements
Author :
Kayvanrad, Mohammad H.
Author_Institution :
Nat. Univ. of Singapore, Singapore
Abstract :
A practical method of reconstruction of signals from a small number of random observations is put forward. The method takes advantage of the sparsity of the signal in wavelet domain to reconstruct it in an iterative manner. The proposed method is shown to be quite successful in reconstruction of 1D as well as 2D signals from a few numbers of randomly acquired samples. It also proves to be robust to observation noise.
Keywords :
signal reconstruction; wavelet transforms; 1D signal reconstruction; 2D signal reconstruction; iterative method; random measurements; signal sparsity; wavelet domain; Bandwidth; Compressed sensing; Discrete wavelet transforms; Filter bank; Iterative methods; Noise robustness; Optimization methods; Particle measurements; Sampling methods; Wavelet domain;
Conference_Titel :
Signal Processing, 2008. ICSP 2008. 9th International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2178-7
Electronic_ISBN :
978-1-4244-2179-4
DOI :
10.1109/ICOSP.2008.4697705