Author :
Chen, Shaobing ; Donoho, David
Author_Institution :
Dept. of Stat., Stanford Univ., CA, USA
fDate :
31 Oct-2 Nov 1994
Abstract :
The time-frequency and time-scale communities have recently developed an enormous number of over-complete signal dictionaries, wavelets, wavelet packets, cosine packets, Wilson bases, chirplets, warped bases, and hyperbolic cross bases being a few examples. Basis pursuit is a technique for decomposing a signal into an “optimal” superposition of dictionary elements. The optimization criterion is the l1 norm of coefficients. The method has several advantages over matching pursuit and best ortho basis, including super-resolution and stability
Keywords :
adaptive signal processing; signal representation; signal resolution; time-frequency analysis; Wilson bases; adaptive representations; basis pursuit; chirplets; coefficients; cosine packets; dictionary elements; hyperbolic cross bases; optimal superposition; over-complete signal dictionaries; signal decompositon; signal representations; stability; super-resolution; time-frequency analysis; time-scale analysis; warped bases; wavelet packets; wavelets; Chirp; Dictionaries; Explosions; Matching pursuit algorithms; Signal representations; Signal resolution; Stability; Statistics; Time frequency analysis; Wavelet packets;
Conference_Titel :
Signals, Systems and Computers, 1994. 1994 Conference Record of the Twenty-Eighth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-6405-3
DOI :
10.1109/ACSSC.1994.471413
