NDLI: Theory of the Stochastic Resonance Effect in Signal Detection

Content Provider	IEEE Xplore Digital Library
Author	Hao Chen Varshney, P.K.
Copyright Year	1991
Abstract	In Part I of this paper [ldquoTheory of the Stochastic Resonance Effect in Signal Detection: Part I-Fixed Detectors,rdquo IEEE Transactions on Signal Processing, vol. 55, no. 7, pt. 1, pp. 3172-3184], the mechanism of the stochastic resonance (SR) effect for a fixed detector has been examined. This paper analyzes the stochastic resonance (SR) effect under the condition that the detector structure or its parameters can also be changed. The detector optimization problem with SR noise under both Neyman-Pearson and Bayesian criteria is examined. In the Bayesian approach when the prior probabilities are unknown, the minimax approach is adopted. The form of the optimal noise pdf along with the corresponding detector as well as the maximum achievable performance are determined. The developed theory is then applied to a general class of weak signal detection problems. Under the assumptions that the sample size N is large enough and the test statistics satisfies the conditions of central limit theorem, the optimal SR noise is shown to be a constant vector and independent of the signal strength for both Neyman-Pearson and Bayesian criteria. Illustrative examples are presented where performance comparisons are made between the original detector and the optimal SR noise modified detector for different types of SR noise.
Sponsorship	IEEE Signal Processing Society
Starting Page	5031
Ending Page	5041
Page Count	11
File Size	830683
File Format	PDF
ISSN	1053587X
Volume Number	56
Issue Number	10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic resonance Signal detection Detectors Strontium Bayesian methods Nonlinear systems Minimax techniques Object detection Data preprocessing Gaussian noise stochastic resonance Hypothesis testing minimax rule non-Gaussian noise nonlinear systems signal detection Minimax rule Stochastic Resonance Signal Detection Hypothesis Testing Nonlinear Systems Non-Gaussian Noise
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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Theory of the Stochastic Resonance Effect in Signal Detection: Part I—Fixed Detectors

Improving Nonparametric Detectors via Stochastic Resonance

Noise-enhanced M-ary hypothesis-testing in the minimax framework

Noise Enhanced Hypothesis-Testing in the Restricted Bayesian Framework

Noise enhanced detection in the restricted Bayesian framework

Noise Enhanced Signal Detection and Estimation

Approaching Near Optimal Detection Performance via Stochastic Resonance

Improving Sequential Detection Performance Via Stochastic Resonance

Optimum stochastic resonance detector of weak sinusoid signals in additive white Gaussian noise

Theory of the Stochastic Resonance Effect in Signal Detection—Part II: Variable Detectors

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