Motion detection and stochastic resonance in noisy environments

被引:18
作者
Harmer, GP [1 ]
Abbott, D
机构
[1] Univ Adelaide, Ctr Biomed Engn, Adelaide, SA 5005, Australia
[2] Univ Adelaide, Dept Elect Engn & Elect, Adelaide, SA 5005, Australia
基金
澳大利亚研究理事会;
关键词
smart sensors; motion detection; collision avoidance; insect vision; stochastic resonance; noisy sensory neural models; noise;
D O I
10.1016/S0026-2692(01)00094-5
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
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. (C) 2001 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:959 / 967
页数:9
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