Study On Application Of Neural Stochastic Resonance In Speech And Image Processing

Stochastic resonance (SR) is a cooperative phenomenon between signal and randomnoise in the nonlinear system.It reflects whereby the noise can benefit to the signal,whichcan be observed in many nonlinear systems.Especially in the neural system,stochasticresonance may play an important role for information processing.Up to now,the research of stochastic resonance in the neuron models was mainlyfocused on the subthreshold periodic input.But indeed,application of SR techniques toaperiodic signal detection or estimation is more meaningful.Furthermore,Some researches oftheory and models indicate that suprathreshold stochastic resonance may be the mechanismof human hearing and visual signal detection.This thesis focused on the research ofsuprathreshold aperiodic stochastic resonance in neuron models,and this mechanism to detectweak signal was applied to speech restoration,image restoration and image enhancement.At first,the research status of the SR theory was introduced.The traditional andnon-traditional SR theory was explained in brief,and the formal methods for performanceevaluation of stochastic resonance were analyzed.The work of the thesis includes three parts.1.Research of stochastic resonance in the neuron modelsThe function of the stochastic resonance for information processing in neural systemwas simulated by using of Hodgkin-Huxley (H-H) neuron model,Fitzhugh-Nagumo(FHN)neuron model and EEG model.Based on analyzing the subthreshold SR phenomenon,thesuprathreshold SR was studied carefully.The effect of suprathreshold stochastic resonance ofthe neuron models was analyzed quantitatively by signal-noise-ratio,cross correlationcoefficient and mutual information ratio.The threshold characteristic of one neuron wasdiscussed.The result of simulation and experiment showed that in follows:Stochastic resonance in the neuron models was not only for periodic signal but alsofor aperiodic signal.It revealed that the organism may make use of stochasticresonance to detect the weak signal in complex background.Suprathreshold SR would be happened in the neuron models under certainconditions.By analyzing the threshold characteristic of FHN neuron,the conclusion wasobtained that the dynamics conduct can be equivalent to the transit action from onestate to another.2.Study of application on one-dimension signal processing The corrupted speech signal was selected as a case study.The SR performance of speechsignal was estimated by the improved cross correlation coefficient.The speech restorationalgorithm was proposed based on the mechanism of suprathreshold stochastic resonance inthe neuron models,and was used to reconstruct the speech signal.Compared with traditionalrestoration methods,this new method had better performance and good robustness.3.Study of application on two-dimension signal processingThe stochastic resonance phenomenon in two-dimension image signals was analyzed.Self-adaptive stochastic resonance method of image restoration was proposed and used torestore gray-scale image with noise.Because the information amount of the color image withnoise was very large and the range of optimum noise intensity was variable,fast self-adaptiveoptimal stochastic resonance method of image restoration was proposed and used to restoregray-scale image and color image with noise.The new method was based on thefixed-threshold and the certain type of noise.The quick-bisearch method was designed toimprove the efficiency of algorithm.The phenomenon of suprathreshold aperiodic stochastic resonance was analyzedquantitatively and qualitatively.The contrast experiments were done according to variousrestoration methods and various adding noise number.In two-dimension informationprocessing,the restoration performance and robustness of gray-scale image or color imagewith noise were both better than the formal methods'.Comparing the effect of equality distributing stochastic noise and Gaussian white noiseto the stochastic resonance performance and image restoration quality,it was found that thecharacteristic of the equality distributing stochastic noise was better than of Gaussian whitenoise.At last,the question of the enhancement of weak image signal was studied based SRmechanism in order to detect the weak signal from the image with the help of the addednoise.The experiment results showed that the fast self-adaptive stochastic resonance methodwas effective to enhance the image.It was remarkable that the method based on RGB colormodel and the method based on HSI color model has some advantage respectively.The SR theory can be used in many other fields,such as image segment,test ofmechanical failure,etc.It is valuable to study more deeply and widely.