提出一种基于混沌神经网络(CNN)的拟人智能控制方法。
A control method was proposed, which combines the human-imitating control theory and the optimization capability of chaotic neural networks (CNN).
这一简单电路可望在混沌神经网络，混沌通讯领域获得应用。
The simple circuit can be applied in chaotic neural network and chaotic communication.
研究一类离散和分布时变时滞的混沌神经网络的广义投影同步问题。
In this paper, the problem of general projective synchronization of a class of chaotic neural networks with discrete and distributed time-varying delays is investigated.
研究结果表明，基于混沌神经网络的故障诊断有助于故障模式的记忆和重视。
Diagnose result suggest that the chaotic neural network is beneficial to dynamic memory retrieval and faults identification. And chaotic neural network has fault tolerance.
为解决压电陶瓷迟滞建模问题，提出一种新型的G - S混沌神经网络模型。
A novel G-S chaotic neural network is proposed to resolve the hysteresis model of piezoceramics.
基于混沌神经网络模型可以有效地解决高维、离散、非凸的非线性约束优化问题。
The Chaotic neural network model can be used to solve many multi-dimensioned, discrete, non-convex, nonlinear constrained optimization problems.
在此基础上，应用混沌神经网络对异步电动机鼠笼转子断条故障进行动态记忆和恢复。
In the paper faults of three phase induction motors with broken bare is diagnsed usingdrpamic associative memory of chaotic neural network.
基于混沌神经网络的供配电系统故障诊断，采用引入动量项和混沌映射的改进BP算法。
The improved BP algorithm added momentum item and chaotic mapping was adopted in fault diagnosis of power supply system based on chaotic neural network.
回顾了近年来几种主要混沌神经元模型及混沌神经网络的研究进展，介绍了其特点及主要的应用。
Reviews the research progress of chaotic neuron model and chaotic neural networks in recent years, introduces the characteristics and application of the chaotic neural networks.
本文以混沌神经网络为主要研究对象，并应用于典型组合优化问题求解和宽带匹配网络设计之中。
This paper studied the chaotic neural network and applied it to a typical combinatorial optimization problem and broadband matching network design.
混沌神经网络的10个城市的旅行商问题（TSP），和三角函数自反馈对TSP的影响进行了分析。
This chaotic neural network is used to the 10-city traveling salesman problem (TSP), and the influence of trigonometric function self-feedback on TSP is analyzed.
已有的研究结果表明，混沌神经网络在求解复杂优化问题和联想记忆等方面比现有网络有着更好的性能。
The research results show that the chaotic neural networks are more effective than other existing neural networks to solve associative memory and complex optimization problems.
对反馈神经网络进行了研究，在分析现有混沌神经网络的工作原理的基础上，提出一种新的混沌神经网络模型。
The study of the feedback neural network, the analysis of the work principle of Hopfield neural network lead to a neural network model with chaotic character .
在传统混沌神经网络模型的基础上，提出了一种具有衰减混沌噪声的混沌模拟退火神经网络模型(CSA - DCN)。
Based on deeply discussing the principle of chaotic neural network model, the chaotic simulated annealing model with decaying chaotic noise (CSA-DCN) is presented.
确定了模型的输出函数，并推导了模型的学习算法，仿真结果表明永磁同步电机的模糊混沌神经网络模型与原系统是等价的。
It established the model's output mathematic function and learning algorithm. Computer simulations showed the equivalence of fuzzy chaos neural network model and the original chaotic system.
以船舶发电机这一大型非线性系统为例，对其进行混沌神经网络仿真建模研究，提出了用混沌神经网络仿真建模的一般思路和方法。
A general idea and a basic method for modeling with neural networks are put forward on the basis of the study of Marine synchronous generator modeling based on chaotic neural networks.
近年来，人们发现神经系统中存在着许多不规则的混沌现象，所以对于混沌神经网络（CNN）的研究成了摆在人们面前的一个新课题。
Recently, it is found that there are many chaotic phenomenon of chaos in the nervous system, so the research of chaotic neural network (CNN) is becoming a new task for us.
讨论了非平衡B指派问题的求解算法，给出了暂态混沌神经网络模型，并描述了非平衡B指派问题，提出了基于暂态混沌神经网络的非平衡B指派问题的求解算法。
The solution of imbalance B-assignment problem is studied. An assignment's model and network are discussed, and then a new algorithm based on transient chaotic neural networks is proposed.
提出利用直接自适应模糊神经网络控制一类不确定非线性混沌系统新方法。
A novel direct adaptive fuzzy neural networks (FNNs) controller for a class of uncertain nonlinear chaotic system is presented.
提出一种关于多层前向神经网络结构的混沌优化设计方法。
The optimization design method is proposed for feed-forward neural network structure by means of chaos ergodicity and randomicity.
提出了一种基于混沌变量的多层模糊神经网络优化算法设计。
An optimization algorithm design based on chaotic variable is proposed for multilayer fuzzy neural network.
本文给出了一种利用线性输出神经网络实现标量混沌信号同步控制的方法。
An approach to the control and synchronization of the scalar chaotic signal by means of neural networks with linear outputs is presented.
在BP算法中加入动量项和混沌映射，选择神经网络初值。
The momentum item and chaotic mapping was added into BP algorithm, and the initial value of the network was selected.
其次，实验中测得了大量的混沌数据，在神经网络模型的启发下提出了一种新的符号序列去噪算法，应用该算法提高了测量精度。
Secondly, we have obtained plenty of chaotic data, and presented a new method derived from Neural Network theory to process the symbolic series, which improves the accuracy of measurement.
根据逆最优控制方法，针对非线性系统，提出了利用动态神经网络产生混沌的一种新方法。
Propose a new approach to generate chaos via dynamic neural networks according to inverse optimal control for nonlinear systems.
考虑神经网络在训练大规模样品时易陷入局部极小，用梯度下降法与混沌优化方法相结合，使神经网络实现快速训练的同时，避免陷入局部极小。
Combining grading method with chaotic optimization, the neural network model achieves rapid training and avoids local minimum when there are a lot of samples to be trained.
采用新型多重分支时间延迟神经网络进行混沌时间序列预测研究。
A new multi-branch time delay neural network is adopted to conduct prediction research on chaotic time series.
最后阐述应用rbf神经网络进行基于混沌的语音信号非线性处理。
Then RBF neural network used in nonlinear processing of speech signals based on chaos aspects is presented.
最后阐述应用rbf神经网络进行基于混沌的语音信号非线性处理。
Then RBF neural network used in nonlinear processing of speech signals based on chaos aspects is presented.
应用推荐