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基于rosenstein法的混沌时间序列最大利亚普诺夫指数算法(Method based on chaotic time series rosenstein largest Liapunov exponent algorithm)

说明：  MATLAB示例代码 从2004年11月起，《MATLAB及在电子信息课程中的应用》的下载程序dsk01改为dsk02。两者只有微小的差别。主要的修改是： 1． 所有的生成图形都由灰色改成白色，以便与书籍上的图相同。 2． 删去了几个无用的程序； 3． 加了了几个程序（如q48a和q48b），以便和书上的章节演示内容相符。(MATLAB sample code from November 2004 onwards, "MATLAB and electronic information in the curriculum of" download dsk01 dsk02 changed. Taken only a very small difference. The major changes are : 1. All graphics generating replaced by gray and white, with the books to the same map. 2. By deleting a few useless procedures; 3. The increase in the number of procedures (such as q48a and q48b), and to book chapters on the demonstration line content.)

constancy gui using white patch

很不错的流形学习算法 包含了MDS PCA ISOMAP LLE等算法(Very good manifold learning algorithm includes the MDS PCA ISOMAP LLE, such as eight kinds of algorithms)

多维粒子群优化算法的matlab代码，可求解多目标问题(Multidimensional particle swarm optimization matlab code, multi-objective problem can be solved)

Fuzzy clustering methods including subtractive and Fuzzy C-means and comparing them to Kmeans clustering method

关于滤波的程序，可以减少Gipps效应，提高信号的分辨率。(On filtering procedures, can reduce the Gipps effect, improve the resolution of the signal.)

inverter : onduleur 3 nivoeu onduleur monophase three order

本文采用小波神经网络进行交通流量预测，短时交通流量存在随机性和非线性因素，影响预测的准确性。传统预测模型难以反映交通流量变化特点，同时传统神经网络易陷入局部极小值，泛化能力差，交通流量预测精度低。为了提高短时交通流量预测精度，提出一种小波神经网络的短时交通流量预测模型。小波神经网络可以对短时交通流量随机性、不确定性进行局部分析，并进行非线性预测，验证了模型的有效性，进行了对比试验。验证结果表明，小波神经网络提高了短时交通流量预精度，预测结果更具应用价值。(In this paper, wavelet neural network is used to forecast traffic flow. There are random and nonlinear factors in short-term traffic flow, affecting the accuracy of prediction. The traditional prediction model is difficult to reflect the characteristics of traffic flow changes. At the same time, the traditional neural network is easy to fall into the local minimum, the generalization ability is poor, and the prediction accuracy of traffic flow is low. In order to improve the accuracy of short-term traffic flow forecasting, a short-term traffic flow prediction model based on wavelet neural network is proposed. The wavelet neural network can analyze the randomness and uncertainty of short-term traffic flow and perform nonlinear prediction. The validity of the model is verified and a comparative experiment is conducted. The verification results show that the wavelet neural network improves the short-term traffic flow pre-precision, and the prediction result has more application value.)

matlab的体育场混响空场测试推算满场时间程序(matlab empty stadium reverberation field testing market projections over time procedures)