Researches On Monostable Logical Stochastic Resonance And Its Application

The weak signal detection technology is a branch of measurement technology. With it, a weak signal can be detected under strong noise background. In recent years, it becomes a hot research. Comparing with the traditional noise suppression method, the method based on stochastic resonances is a novel one. It uses the cooperative effect among signal, noise and systems to drive part of the noise energy into the signal energy. At last, the signal is greatly enhanced. In this paper, logical stochastic resonance in monostable systems and its application in image de-noising are studied.Firstly, logic stochastic resonances in monostable systems driven by square waves are studied. Gauss white noises and Gauss color noises are considered, respectively. The influences of the system parameters and noise intensity on the probability of obtaining a successful gate operation are given, respectively. Results show that monostable systems can produce logic stochastic resonances. With same system parameters, the width of band of noises for Gauss white noises is wider than that for Gauss color noises. At the same time, many-level square waves with noise can also be de-noised by logic stochastic resonances in such monostable systems.Secondly, logic stochastic resonances in series and parallel monostable systems are studied, respectively. Under Gauss white noises, the influences of the system parameters and noise intensity on the probability of obtaining a successful gate operation are given. Results show that comparing series systems with parallel ones, logic stochastic resonances can be realized in relatively wider band of noise for series ones. The perfoamance of parallel monostable systems is much worse than that of one monostable system or series monostable systems.Finally, series monostable systems are applied to image de-noising, respectively. A binary piture is given as an example. Results show that the perfoamance of series monostable systems is better than single ones. The best denoising effect for different levels of series monostable systems corresponds to different width of band of noise. Therefore, in practice the the appropriate level of series monostable systems should be chosen according to the intensity of noises.