典型文献
Complex-Valued Neural Networks:A Comprehensive Survey
文献摘要：
Complex-valued neural networks(CVNNs)have shown their excellent efficiency compared to their real counter-parts in speech enhancement,image and signal processing.Researchers throughout the years have made many efforts to improve the learning algorithms and activation functions of CVNNs.Since CVNNs have proven to have better performance in handling the naturally complex-valued data and signals,this area of study will grow and expect the arrival of some effective improvements in the future.Therefore,there exists an obvious reason to provide a comprehensive survey paper that systemati-cally collects and categorizes the advancement of CVNNs.In this paper,we discuss and summarize the recent advances based on their learning algorithms,activation functions,which is the most challenging part of building a CVNN,and applications.Besides,we outline the structure and applications of complex-valued convolutional,residual and recurrent neural networks.Finally,we also present some challenges and future research directions to facilitate the exploration of the ability of CVNNs.
文献关键词：
中图分类号：
作者姓名：
ChiYan Lee;Hideyuki Hasegawa;Shangce Gao
作者机构：
Faculty of Engineering,University of Toyama,Toyama 930-8555,Japan
文献出处：
引用格式：
[1]ChiYan Lee;Hideyuki Hasegawa;Shangce Gao-.Complex-Valued Neural Networks:A Comprehensive Survey)[J].自动化学报（英文版）,2022(08):1406-1426
A类：
CVNNs,CVNN
B类：
Complex,Valued,Neural,Networks,Comprehensive,Survey,valued,neural,networks,have,shown,their,excellent,efficiency,compared,real,counter,parts,speech,enhancement,image,processing,Researchers,throughout,years,made,many,efforts,learning,algorithms,activation,functions,Since,proven,better,performance,handling,naturally,complex,data,signals,this,area,study,will,grow,expect,arrival,some,effective,improvements,future,Therefore,there,exists,obvious,reason,provide,comprehensive,survey,paper,that,systemati,cally,collects,categorizes,advancement,In,we,discuss,summarize,recent,advances,which,most,challenging,building,applications,Besides,outline,structure,convolutional,residual,recurrent,Finally,also,present,challenges,research,directions,facilitate,exploration,ability
AB值：
0.633315
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