Title :
Neural MCA for robust beamforming
Author :
Fiori, Simone ; Piazza, Francesco
Author_Institution :
Dept. of Ind. Eng., Ancona Univ., Italy
Abstract :
This paper aims at recalling recent results about neural Minor Component Analysis and to apply them to spatial adaptive array filtering (adaptive beamforming). The constrained beamformer power optimization principle is employed, which allows us to improve the performances of simpler beamforming algorithms by emphasizing white noise sensitivity control and prior knowledge about the disturbances
Keywords :
array signal processing; neural nets; optimisation; principal component analysis; white noise; adaptive beamforming; beamforming algorithms; constrained beamformer power optimization principle; neural minor component analysis; robust beamforming; spatial adaptive array filtering; statistical signal processing technique; white noise sensitivity control; Adaptive filters; Array signal processing; Constraint optimization; Covariance matrix; Eigenvalues and eigenfunctions; Filtering; Principal component analysis; Random processes; Robustness; Signal processing algorithms;
Conference_Titel :
Circuits and Systems, 2000. Proceedings. ISCAS 2000 Geneva. The 2000 IEEE International Symposium on
Conference_Location :
Geneva
Print_ISBN :
0-7803-5482-6
DOI :
10.1109/ISCAS.2000.856135
