xpdf3.02_pl5

这个套件包含了C + +实现"减量和增量支持向量机学习"，根据Cauwenberghs和Piggio他们的matlab实现。(This package contains a c++ implementation of "Incremental and Decremental Support Vector Machine Learning, Cauwenberghs and Poggio" based on their matlab implementation. Getting started - make (to compile) - ./inc_svm 1 data_kernel.txt (to train and cross-validate) - ./inc_svm 1 diabetes_kernel.txt)

用MATLAB下面的simulink库里的dsp builder搭建了一个图形化的iir滤波器模型(Using MATLAB simulink library following the dsp builder to build a graphical model of iir filter)

数值分析的牛顿迭代算法数值分析的牛顿迭代算法(matlab )

very good simulation for multipath channel

变步长龙格库塔法,用于解决四阶微分方程组求解析解的问题，尤其适用于两自由度间隙碰撞问题的解决。(This is a matlab program about Runge-Kutta,and it will help you solve many difficulty questions.With its help,you can have a easy way to access your success.)

本程序采用matlab编程，通过设计训练一个人工神经网络来达到其对一个4传感器实时检测输出结果融合判断的模拟，文中涉及人工圣经网络和多传感器融合两们学科的基本知识。(the procedures used Matlab programming, through the design of a training artificial neural network to achieve its right to a four-detection sensor fusion output judgment simulation , the text involving artificial Bible network and multi-sensor fusion of the two disciplines have basic knowledge.)

COMMANDE D un convertiseur AC/DC 脿 deux niveaux par MLI

说明：  经典遗传算法工具箱中的初始种群的生成程序，与大家分享(classical genetic algorithm toolbox initial population of the production process, share with you)

最新国外有关matlab的资料，是国内没有的，希望对大家的学习matlab有帮助。(Matlab latest information about the foreign, is not, we want to learn matlab help.)

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.)