Bayesian random Fourier filters for Gaussian noises  

作　　者：Shiyuan WANG Wanli WANG Shukai DUAN Lidan WANG Chi K.TSE 

机构地区：[1]College of Electronic and Information Engineering,Southwest University,Chongqing 400715,China [2]Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing,Chongqing 400715,China [3]Department of Electronic and Information Engineering,Hong Kong Polytechnic University,Hong Kong,China

出　　处：《Science China(Information Sciences)》2018年第12期210-212,共3页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant Nos. 61671389, 61672436)

摘　　要：Dear editor,Signal processing algorithms are generally used to identify an unknown system, and can be classified as batch algorithms and online learning algorithms(OLAs). Batch algorithms are applied to offline scenarios that require all data being available. In real-time applications, because information is pro-

关 键 词：Bayesian random Fourier filters for Gaussian noises 

分 类 号：N[自然科学总论]