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| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Rai, Renuka | - |
| dc.contributor.author | Singh, Harjinder | - |
| dc.date.accessioned | 2014-01-18T06:28:47Z | - |
| dc.date.available | 2014-01-18T06:28:47Z | - |
| dc.date.issued | 2000-03 | - |
| dc.identifier.issn | 0975-0975(Online); 0376-4710(Print) | - |
| dc.identifier.uri | http://hdl.handle.net/123456789/25839 | - |
| dc.description | 323-329 | en_US |
| dc.description.abstract | We have modeled a bistable molecular system using a neural network model and studied its behaviour in the presence of periodic and stochastic forces. It is observed that the signal to noise ratio (SNR) shows a maximum as a function of noise. This is a finger print of the phenomenon of stochastic resonance (SR). Apart from the SNR, we have studied the behaviour of residence time distribution function when noise strength and drive frequency are varied. Another important quantity which is of relevance to chemical systems is the mean first passage time. It shows the existence of a minimum as a function of input frequency which is a characteristic of SR. | en_US |
| dc.language.iso | en_US | en_US |
| dc.publisher | NISCAIR-CSIR, India | en_US |
| dc.rights |  CC Attribution-Noncommercial-No Derivative Works 2.5 India | en_US |
| dc.source | IJC-A Vol.39A(01-03) [January-March 2000] | en_US |
| dc.title | Stochastic resonance in a neuron based model for a molecular system | en_US |
| dc.type | Article | en_US |
| Appears in Collections: | IJC-A Vol.39A(01-03) [January-March 2000] | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| IJCA 39A(01-03) 323-329.pdf | 1.56 MB | Adobe PDF | View/Open |
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