Title :
Signal processing with the sparseness constraint
Author_Institution :
Dept. of Electr. & Comput. Eng., California Univ., San Diego, La Jolla, CA, USA
Abstract :
An overview is given of the role of the sparseness constraint in signal processing problems. It is shown that this is a fundamental problem deserving of attention. This is illustrated by describing several applications where sparseness of solution is desired. Lastly, a review is given of the algorithms that are currently available for computing sparse solutions
Keywords :
inverse problems; signal processing; algorithms; linear inverse problems; neuromagnetic imaging; signal processing; signal representation; sparse solutions; sparseness constraint; speech coding; Application software; Constraint optimization; Deconvolution; Equations; Inverse problems; Least squares methods; Signal processing; Signal processing algorithms; Signal representations; Vectors;
Conference_Titel :
Acoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-4428-6
DOI :
10.1109/ICASSP.1998.681826
