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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Hao Chen Varshney, P.K. Michels, J.H. |
| Copyright Year | 1994 |
| Abstract | In this letter, we present a novel instance of the stochastic resonance effect in sequential detection. For a general binary hypotheses sequential detection problem, the detection performance is evaluated in terms of the expected sample size under both hypotheses. Improvability conditions are established for an injected noise to reduce at least one of the expected sample sizes for a sequential detection system using stochastic resonance. The optimal noise is also determined under such criteria. An illustrative example is presented where performance comparisons are made between the original detector and different noise modified detectors. |
| Sponsorship | IEEE Signal Processing Society |
| Starting Page | 685 |
| Ending Page | 688 |
| Page Count | 4 |
| File Size | 256347 |
| File Format | |
| ISSN | 10709908 |
| Volume Number | 15 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2008-01-01 |
| 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 Detectors Strontium Sequential analysis Noise reduction System testing Nonlinear systems Performance loss Signal detection Electronic switching systems stochastic resonance Hypothesis testing nonlinear systems sequential detection sequential probability ratio test |
| Content Type | Text |
| Resource Type | Article |
| Subject | Applied Mathematics Signal Processing Electrical and Electronic Engineering |
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