The Mechanism And Applications Of Logic Stochastic Resonance Induced By A Nonlinear Bistable System

Logic resonance stochastic(LSR)phenomenon refers to a kind of phenomenon that make logical operation by using the part of the noise energy,which can effectively solve the problem of logic operation caused by the noise.In recent years,the computer industry has been got rapid development,and the size of computer is smaller and smaller.However because of the existence of the noise,the computer chip size has reached its limitation.As the LSR can use part of noise energy to make logical operation,they hope that the LSR phenomenon can be applied to the production of computer chips to break the limitation of the size of computer chips.The mechanism of logic stochastic resonance induced by a nonlinear bistable system,in the condition of Gaussian white noise or α stable noise and the detection of weak binary logic signal under strong noise interference are studied in this paper.Firstly,logic stochastic resonance in the condition of Gaussian white noise is studied.Using the probability of correct logic output as the index to measure the LSR phenomenon,the integer order and fractional order logic stochastic resonance in the condition of Gaussian white noise are studied.Results show that by adjusting the intensity of Gaussian white noise D,fractional order m or weak periodic signal,the LSR phenomenon can be induced and “window effects” will be apprered.Then,the logic stochastic resonance in the condition of α stable noise is studied.We explore the functions of fractional order m,characteristic exponent α,skewness parameter β in inducing LSR phenomenon.Results show that by adjusting fractional order m,characteristic exponent α and skewness parameter β,the LSR phenomenon can be induced.Finally,the logical stochastic resonance is applied to the detection of weak binary logic signal under strong noise interference.Results show that by adjusting the intensity of Gaussian white noise D or fractional order m,the error rate of logical information can be effectively reduced.