Research on Image Signal Identification Based on Adaptive Array Stochastic Resonance

作     者：ZHAO Jingjing MA Yumei PAN Zhenkuan ZHANG Huage ZHAO Jingjing;MA Yumei;PAN Zhenkuan;ZHANG Huage

作者机构：College of Computer Science&TechnologyQingdao UniversityQingdao 266071China. 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2022年第35卷第1期

页      面：179-193页

核心收录：

学科分类：0810[工学-信息与通信工程] 1205[管理学-图书情报与档案管理] 0711[理学-系统科学] 07[理学] 08[工学] 080203[工学-机械设计及理论] 080401[工学-精密仪器及机械] 0804[工学-仪器科学与技术] 080402[工学-测试计量技术及仪器] 0802[工学-机械工程] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by the National Natural Science Foundation of China under Grant Nos.61501276,61573204,61772294 and 61973179 the China Postdoctoral Science Foundation under Grant No.2016M592139 the Qingdao Postdoctoral Applied Research Project under Grant No.2015120 

主　　题：Array stochastic resonance bit error rate image restoration saturating nonlinearity signal identification 

摘      要：Aiming at the problems of low accuracy of image signal identification and poor anti-noise signal interference ability under strong noise environment,a signal identification method of correlated noisy image based on adaptive array stochastic resonance(SR)is proposed in this ***,the two-dimensional grayscale image is transformed to a one-dimensional binary pulse amplitude modulation(BPAM)signal with periodicity by the row or column scanning method,encoding and ***,the one-dimensional low signal-to-noise ratio BPAM signal can be applied to the saturating nonlinearity array SR module for image signal identification processing and part of the noise energy is converted into signal ***,the one-dimensional image signal processed by the nonlinearities is demodulated,decoded and reverse scanned to get the restored grayscale *** simulation results show that the image signal identification method proposed in this paper is highly efficient and accurate for the identification of noisy image signals of different sizes,and the bit error rate(BER)is also significantly reduced.