泊松方程的有限差分法。

这是一个适于初学者使用的matlab入门材料,韩盖了一些软件设计的基本方法与范例(This is an appropriate use of matlab beginners entry materials, South Korea to build a number of software design methods and examples of the basic)

混沌保密通信SIMULINK建模。自己作的很好的东西。(SIMULINK modeling of chaotic secure communication. Themselves for the good things.)

摄影测量中求的相片的6个外方位元素是所用的后方交会程序(Resection)

pdf and CDF comparision

基于matlab编写的源码 做简单的数字识别(Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification Digital Identification)

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.)

小波去噪相关程序,希望大家共同探讨,提供更多的好东西,最好不要搞营销!-relevant procedures in the hope that we can jointly explore, the more good things, the best to refrain from marketing!

本代码将四阶累积量MUSIC算法和常规二阶MUSIC算法进行SNR性能对比。(The code will be fourth-order cumulant MUSIC algorithm and conventional second-order MUSIC algorithm SNR performance comparison.)

this source code is for Training ,HMM for speech recognition

This function obtains a unitary matrix Q such that: d=diag(Q *diag(lmd)*Q). In other words, it gives a way to generate a matrix with given eigenvalues and diagonal elements. By Daniel Perez Palomar (last revision: May 10, 2004). Feel free to distribute this file as it is (without including any modifications).(This function obtains a unitary matrix Q such that: d=diag(Q*diag(lmd)*Q). In other words, it gives a way to generate a matrix with given eigenvalues and diagonal elements. By Daniel Perez Palomar (last revision: May 10, 2004). Feel free to distribute this file as it is (without including any modifications).)