Design and performance analysis of a signal detector based on suprathreshold stochastic resonance
This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. Th...
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| Eará dahkkit: | |
| Materiálatiipa: | Journal Article |
| Giella: | English |
| Almmustuhtton: |
2013
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| Fáttát: | |
| Liŋkkat: | https://hdl.handle.net/10356/84493 http://hdl.handle.net/10220/12030 |
| _version_ | 1826125171647315968 |
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| author | Hari, V. N. Anand, G. V. Premkumar, A. B. Madhukumar, A. S. |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Hari, V. N. Anand, G. V. Premkumar, A. B. Madhukumar, A. S. |
| author_sort | Hari, V. N. |
| collection | NTU |
| description | This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation σ of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum σ also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum σ depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. |
| first_indexed | 2024-10-01T06:32:20Z |
| format | Journal Article |
| id | ntu-10356/84493 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T06:32:20Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | ntu-10356/844932020-05-28T07:17:30Z Design and performance analysis of a signal detector based on suprathreshold stochastic resonance Hari, V. N. Anand, G. V. Premkumar, A. B. Madhukumar, A. S. School of Computer Engineering DRNTU::Engineering::Computer science and engineering This paper presents the design and performance analysis of a detector based on suprathreshold stochastic resonance (SSR) for the detection of deterministic signals in heavy-tailed non-Gaussian noise. The detector consists of a matched filter preceded by an SSR system which acts as a preprocessor. The SSR system is composed of an array of 2-level quantizers with independent and identically distributed (i.i.d) noise added to the input of each quantizer. The standard deviation σ of quantizer noise is chosen to maximize the detection probability for a given false alarm probability. In the case of a weak signal, the optimum σ also minimizes the mean-square difference between the output of the quantizer array and the output of the nonlinear transformation of the locally optimum detector. The optimum σ depends only on the probability density functions (pdfs) of input noise and quantizer noise for weak signals, and also on the signal amplitude and the false alarm probability for non-weak signals. Improvement in detector performance stems primarily from quantization and to a lesser extent from the optimization of quantizer noise. For most input noise pdfs, the performance of the SSR detector is very close to that of the optimum detector. 2013-07-23T03:12:09Z 2019-12-06T15:46:05Z 2013-07-23T03:12:09Z 2019-12-06T15:46:05Z 2012 2012 Journal Article Hari, V. N., Anand, G. V., Premkumar, A. B., & Madhukumar, A. S. (2012). Design and performance analysis of a signal detector based on suprathreshold stochastic resonance. Signal Processing, 92(7), 1745-1757. 0165-1684 https://hdl.handle.net/10356/84493 http://hdl.handle.net/10220/12030 10.1016/j.sigpro.2012.01.013 en Signal Processing © 2012 Elsevier B.V. |
| spellingShingle | DRNTU::Engineering::Computer science and engineering Hari, V. N. Anand, G. V. Premkumar, A. B. Madhukumar, A. S. Design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| title | Design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| title_full | Design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| title_fullStr | Design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| title_full_unstemmed | Design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| title_short | Design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| title_sort | design and performance analysis of a signal detector based on suprathreshold stochastic resonance |
| topic | DRNTU::Engineering::Computer science and engineering |
| url | https://hdl.handle.net/10356/84493 http://hdl.handle.net/10220/12030 |
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