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|Title:||Motion detection and stochastic resonance in noisy environments|
|Citation:||Microelectronics Journal, 2001; 32(12):959-967|
|Publisher:||Elsevier Advanced Technology|
|G. P. Harmer and D. Abbott|
|Abstract:||Several motion detection schemes are considered and their responses to noisy signals investigated. The schemes include the Reichardt correlation detector, shunting inhibition and the Horridge template model. These schemes are directionally selective and independent of the direction of change in contrast. They function by using spatial information and comparing it at successive time intervals. A rudimentary noise analysis is performed on the Reichardt and inhibition detectors to compare their natural robustness against noise. Using these detectors, stochastic resonance (SR) is applied, which is characterised by an improvement in response when noise is added to the input signal. It is found that the performance of the detectors degrades with the addition of noise. Employing Stocks' suprathreshold SR, an improvement can be gained when considering a network of detectors. Furthermore, when using an incorrect threshold setting for the template model, SR can be displayed.|
|Keywords:||Smart sensors; Motion detection; Collision avoidance; Insect vision; Stochastic resonance; Noisy sensory neural models; Noise|
|Appears in Collections:||Electrical and Electronic Engineering publications|
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