Name
Abstract | ||
|---|---|---|
Stochastic resonance is said to occur when just the right amount of noise enhances the performance of a process. For a simple threshold detector, the first moment of stochastic resonance is obtained by passing the signal through a transfer function equal to a transposed and shifted version of the underlying noise's probability distribution function. The process is readily evident in images wherein noise corresponding to a linear transfer function produces a better visual representation than when other noise is used. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ISCAS.2002.1010507 | Circuits and Systems, 2002. ISCAS 2002. IEEE International Symposium |
Keywords | Field | DocType |
image recognition,image representation,probability,stochastic processes,transfer functions,image visualization,linear transfer function,probability distribution function,stochastic resonance,threshold detector,visual representation | Value noise,Computer science,Noise (electronics),Stochastic process,Electronic engineering,Probability distribution,Moment (mathematics),Stochastic resonance,Gaussian noise,Gradient noise | Conference |
Volume | Citations | PageRank |
4 | 3 | 0.99 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Robert J. Marks II | 1 | 274 | 62.56 |
| Thompson, B. | 2 | 3 | 0.99 |
| Mohamed A. El-sharkawi | 3 | 391 | 46.23 |
| Warren L. J. Fox | 4 | 21 | 6.48 |
| ROBERT T. MIYAMOTO | 5 | 65 | 10.86 |
| Marks, R.J., II | 6 | 165 | 46.04 |
| El-Sharkawi, M.A. | 7 | 3 | 0.99 |