Conference Paper
Enhancement of stochastic resonance by tuning system parameters and adding noise simultaneously
Dept. of Electr. and Comput. Eng., Polytech. Univ. of Brooklyn, NY
DOI: 10.1109/ACC.2006.1657196 Conference: American Control Conference, 2006 Source: IEEE Xplore

Conference Paper: Nonlinear Bistable Stochastic Resonance Filters for Image Processing
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ABSTRACT: Nonlinear bistable doublewell stochastic resonance systems have been successfully used for onedimensional signal processing, based on the concept of parametertuning stochastic resonance. This paper investigates the applications of parametertuning stochastic resonance in image processing. First, a twodimensional stochastic resonance system is introduced as a nonlinear filter for image processing. The equation satisfied by the dynamic probability density function of the images processed by this stochastic resonance filter and its solutions are then discussed. Finally, this nonlinear filter is used to process a blackwhite image corrupted by additive white Gaussian noise to reveal the possibility to extend the concept of parametertuning stochastic resonance to twodimensional cases. This provides an innovative approach for image processingAcoustics, Speech and Signal Processing, 2007. ICASSP 2007. IEEE International Conference on; 05/2007 
Conference Paper: Theoretical Analysis of Image Processing Using ParameterTuning Stochastic Resonance Technique
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ABSTRACT: Parametertuning stochastic resonance has been successfully applied to onedimensional signal processing. This paper explores the feasibility to extend this technique for image processing. Based on the twodimensional nonlinear bistable dynamic system, the equation satisfied by the system output probability density function is derived for the first time. The corresponding equation for the onedimensional system is the famous FokkerPlanckKolmogorov (FPK) equation. The stationary solution, eigenvalues and eigenfunctions of this equation are then investigated. The upper bound of the system response speed and the related calculation algorithm which are necessary for the applications of this technique to image processing are also proposed in this paper. Finally, the potential applications of this approach in image processing and some future research are suggested.American Control Conference, 2007. ACC '07; 08/2007  [Show abstract] [Hide abstract]
ABSTRACT: Stochastic resonance has been increasingly used for signal estimation, signal transmission, signal detection and image processing. The stochastic resonance effect can be realized by tuning system parameters or by adding noise. In our recent paper, we have investigated the possibility to enhance the aperiodic stochastic resonance (ASR) effect by tuning system parameters and adding noise simultaneously for the Gaussiandistribution weak input signal. This paper extends the result to a more general case using standard optimization theory. It is shown that the normalized power norm of the bistable doublewell system with a small input signal can reach a larger maximal value by this scheme. An online fastconverging optimization algorithm is also proposed for searching the optimal values of system parameters and noise intensity
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