State space framework for blind dynamic signal extraction and recovery

Proceedings - IEEE International Symposium on Circuits and Systems

Volumn 5, Issue , 1999, Pages

  Salam, F M ^a   Erten, G ^a  

^a MICHIGAN STATE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BLIND DYNAMIC SIGNAL EXTRACTION AND RECOVERY;

CONSTRAINT THEORY; FIR FILTERS; IIR FILTERS; INFORMATION THEORY; NETWORKS (CIRCUITS); STATE SPACE METHODS;

SIGNAL FILTERING AND PREDICTION;

EID: 0032673055     PISSN: 02714310     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Article

References (7)

1. F. M. Salam. An Adaptive Network for Blind Separation of Independent Signals. Proceedings of the 1993 IEEE International Symposium on Circuits and Systems (ISCAS) Vol.1, pp. 431 -434.
2. S. Amari, A. Cichocki, and H. Yang. A new learning algorithm for blind signal separation, MIT Press, 1996.
3. L.Tong, Y. Inouye, and R. Lio. Wave-preserving blind estimation of multiple independent sources. IEEE Trans. On Signal Processing, 41 (7): 2461-2470, July 1993.
4. F. Salam, A. Gharbi, and G. Erten, "Formulation and adaptation For Signal Separation in Dynamic Environments," The IEEE 40th Midwest Symposium on Circuits and Systems, Sacramento, CA, 4-6 August 1997.
5. G. Erten and F. Salam, "Real Time Separation of Audio Signals Using Digital Signal Processors, " MWSCAS 97 Sacramento, California, USA, August 1997.
6. F. Salam and G. Erten, "Blind Signal Separation and Recovery in Dynamic Environments," 1997 IEEE Workshop on Nonlinear Signal and Image Processing, Mackinac Island, September 8-10, 1997.
7. F. Salam and G. Erten, Optimization with constraints formulation of the blind Signal Recovery, M-report 1998-12.