Reducing probability of decision error using stochastic resonance

IEEE Signal Processing Letters

Volumn 13, Issue 11, 2006, Pages 695-698

  Kay, Steven ^a   Michels, James H ^b   Chen, Hao ^c   Varshney, Pramod K ^c  

^a University of Rhode Island   (United States)

^b JHM Technologies   (United States)

^c Syracuse University   (United States)

Author keywords

Modeling; Pattern classification; Signal detection

Indexed keywords

ERRORS; MATHEMATICAL MODELS; OPTIMIZATION; PROBABILITY DENSITY FUNCTION; RANDOM PROCESSES; SIGNAL RECEIVERS;

BINARY RECEIVER; DECISION ERROR; DIRAC DELTA FUNCTION; OPTIMAL RANDOM VARIABLE;

SIGNAL PROCESSING;

EID: 33750141554     PISSN: 10709908     EISSN: None     Source Type: Journal    
DOI: 10.1109/LSP.2006.879455     Document Type: Article

References (6)

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3. S. Mitaim and B. Kosko, "Adaptive stochastic resonance," Proc. IEEE, vol. 86, no. 11, pp. 2152-2183, Nov. 1998.
4. S. Kay, "Can detectability be improved by adding noise?," IEEE Signal Process. Lett., vol. 7, no. 1, pp. 8-10, Jan. 2000.
5. H. Chen, P. Varshney, J. Michels, and S. Kay, "Optimal stochastic resonance," presented at the 2006 IEEE Int. Conf. Acoustics, Speech, Signal Processing, Toulouse, France.
6. S. Kay, Fundamentals of Statistical Signal Processing: Detection Theory. Upper Saddle River, NJ: Prentice-Hall, 1998.