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.
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.
对于一个经诊断为混沌的统计量序列，应用神经网络建立模型，短期预测混沌序列。
Short term predictions of chaotic series are realised with neural network model, after diagnosing the time series as chaotic statistic series.
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.
这种用改进了的自组织方法所构成的GMDH型神经网络可以应用于混沌时间序列预测。
An improved GMDH-type neural network and its application to predicting chaotic time series are proposed.
本文主要研究混沌模拟退火神经网络(CSAN)在求解tsp中的应用。
In this paper, We mainly do researches on using chaotic neural network based on simulated annealing (CSAN) to solve TSP.
神经网络具备既能实现快速并行运算又有混沌动力学复杂行为的特征，是设计实现适用于实时安全通信应用的安全芯片最佳选择之一。
Neural networks can implement fast parallel computation; meanwhile it has the characteristic of complex chaotic dynamical process, so it is one of the best choices to assist security chip design.
神经网络具备既能实现快速并行运算又有混沌动力学复杂行为的特征，是设计实现适用于实时安全通信应用的安全芯片最佳选择之一。
Neural networks can implement fast parallel computation; meanwhile it has the characteristic of complex chaotic dynamical process, so it is one of the best choices to assist security chip design.
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