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matlab 经典算法 规划问题讲义及例题(classical algorithm matlab planning notes and Example)

大地测量程序 用于各种坐标系间的相互转换 供测绘遥感工程测量等专业学生学习使用(Procedures for a variety of geodetic coordinate system conversion between the remote sensing for mapping and other engineering students learn to use measurement)

Vision multi-caméra pour la détection d obstacles sur un robot de service

本代码实现了三种直方图相关的算法，分别为直方图均衡化，直方图规定化，对比受限自适应直方图均衡化。三种方法放在3个不同的文件夹下，直接运行test文件，就可以得到运行结果(This code implements three histogram algorithm, respectively histogram equalization, histogram provides contrast limited adaptive histogram equalization. Three methods on three different folder, run directly test file, you can get the results)

数字信号处理中Fourier变换的基本验证。本人验证过，有注释，运行良好。(Fourier transform in digital signal processing basic authentication. I verified, there are notes, running well.)

说明：  基于matlab神经网络工具箱bp神经网络在去噪声方面的应用。(Applications based on neural network toolbox matlab bp neural networks to noise aspects.)

turbo码的编码与译码，交织器 coding and decoding of turbo, interleaver(coding and decoding of turbo, interleaver, almost regular permutation)

This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar -xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. (This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters. )

对声音信号的LMS滤波，噪音为固定信噪比的高斯噪声(LMS filtering of sound signals, noise, Gaussian noise for a fixed signal to noise ratio)

计算小波熵程序，先计算出小波分解后的小波系数，对其求熵得出结果。(Wavelet entropy calculation program, first calculate the wavelet coefficients of the wavelet decomposition, the results of its request entropy.)