Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers (1994)
Pacific Grove, CA, USA
Oct. 31, 1994 to Nov. 2, 1994
Shaobing Chen , Dept. of Stat., Stanford Univ., CA, USA
D. Donoho , Dept. of Stat., Stanford Univ., CA, USA
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 l/sup 1/ norm of coefficients. The method has several advantages over matching pursuit and best ortho basis, including super-resolution and stability.<
signal representation, signal resolution, adaptive signal processing, time-frequency analysis
Shaobing Chen and D. Donoho, "Basis pursuit," Proceedings of 1994 28th Asilomar Conference on Signals, Systems and Computers(ACSSC), Pacific Grove, CA, USA, 1995, pp. 41-44.