改进的混沌Hopfield神经网络盲检测算法

以提高Hopfield神经网络盲检测算法激活函数的灵活性为目标,提出一种在原点附近非线性逼近能力更优的激活函数。针对算法存在陷入局部最优的情况,利用混沌映射优良的遍历性和类随机性,在算法起始点利用混沌产生初始序列,在当前全局最优值不变时进行小幅度混沌扰动,以减少算法的误码性能。仿真结果表明,基于激活函数和混沌映射相结合的改进算法,能够提高神经元输入值敏感区域抗干扰能力,加快收敛速度,提高盲检测性能。...

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Published in电信科学 Vol. 34; no. 2; pp. 81 - 87
Main Authors 于大为, 陈少威, 于舒娟
Format Journal Article
LanguageChinese
Published 中国通信学会 01.02.2018
人民邮电出版社有限公司
苏州信息职业技术学院计算机科学与技术系,江苏苏州,215200%南京邮电大学电子科学与工程学院,江苏南京,210003
Subjects
混沌扰动
盲检测
激活函数
Hopfield神经网络
activation function
blind detection
Hopfield neural network
chaos disturbance
Online AccessGet full text
ISSN1000-0801
DOI10.11959/j.issn.1000-0801.2018016

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Abstract 以提高Hopfield神经网络盲检测算法激活函数的灵活性为目标,提出一种在原点附近非线性逼近能力更优的激活函数。针对算法存在陷入局部最优的情况,利用混沌映射优良的遍历性和类随机性,在算法起始点利用混沌产生初始序列,在当前全局最优值不变时进行小幅度混沌扰动,以减少算法的误码性能。仿真结果表明,基于激活函数和混沌映射相结合的改进算法,能够提高神经元输入值敏感区域抗干扰能力,加快收敛速度,提高盲检测性能。
AbstractList 以提高Hopfield神经网络盲检测算法激活函数的灵活性为目标,提出一种在原点附近非线性逼近能力更优的激活函数。针对算法存在陷入局部最优的情况,利用混沌映射优良的遍历性和类随机性,在算法起始点利用混沌产生初始序列,在当前全局最优值不变时进行小幅度混沌扰动,以减少算法的误码性能。仿真结果表明,基于激活函数和混沌映射相结合的改进算法,能够提高神经元输入值敏感区域抗干扰能力,加快收敛速度,提高盲检测性能。
TN911; 以提高Hopfield神经网络盲检测算法激活函数的灵活性为目标,提出一种在原点附近非线性逼近能力更优的激活函数.针对算法存在陷入局部最优的情况,利用混沌映射优良的遍历性和类随机性,在算法起始点利用混沌产生初始序列,在当前全局最优值不变时进行小幅度混沌扰动,以减少算法的误码性能.仿真结果表明,基于激活函数和混沌映射相结合的改进算法,能够提高神经元输入值敏感区域抗干扰能力,加快收敛速度,提高盲检测性能.
Abstract_FL In order to improve the flexibility of the activation function of the blind detection algorithm in Hopfield neural network,an activation function with better nonlinear approximation ability near the origin was proposed.For the case where the algorithm trapped in local optima,utilizing the good ergodicity and randomness of chaos mapping,chaos was used to generate the initial sequence at the starting point of the algorithm,and small-amplitude chaotic perturbation was performed when the current global optimum value was constant,so as to reduce the error performance of the algorithm.The simulation results show that the proposed algorithm reduces the sensitivity of neurons to input values,has strong anti-interference ability and fast convergence speed,and improves the blind detection performance.
Author 于大为
于舒娟
陈少威
AuthorAffiliation 苏州信息职业技术学院计算机科学与技术系,江苏苏州,215200%南京邮电大学电子科学与工程学院,江苏南京,210003
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Author_FL CHEN Shaowei
YU Shujuan
YU Dawei
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DocumentTitle_FL An improved blind detection algorithm of chaos Hopfield neural network
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Issue 2
Keywords 混沌扰动
盲检测
激活函数
Hopfield神经网络
activation function
blind detection
Hopfield neural network
chaos disturbance
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Publisher 中国通信学会
人民邮电出版社有限公司
苏州信息职业技术学院计算机科学与技术系,江苏苏州,215200%南京邮电大学电子科学与工程学院,江苏南京,210003
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Title 改进的混沌Hopfield神经网络盲检测算法
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