cdma_codes

使用Matlab R2009b进行数字音频压缩处理编程(Using Matlab R2009b compressed digital audio programming)

松下假光蓝555+8202L.binL.rar

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. )

Numerical Analysis Using Matlab And Excel (3Ed)

A Survey on Cooperative Diversity for Wireless Networks

车牌检测与识别技术的相关技术： 提出一种梯度增强法对图像边缘进行增强, 该方法主要通过对图像本身信息进行简单梯度变换以突出图像边缘, 并辅以数学形态学中的膨胀法实现牌照的快速定位. 在字符分割部分, 给出了最小面积旋转法以确定牌照的最佳旋转角, 并采用垂直投影法分割牌照中的字符 (License plate detection and recognition technology related technologies: a gradient-enhanced method of image edge enhancement, the method of the image itself, mainly through a simple gradient transform information in order to highlight the image edge, supplemented by mathematical morphology in the expansion of law implementation License Express location. in the character segmentation part, give a minimum area of rotation method to determine the best rotation angle license and using the vertical projection of the character segmentation license)

discrete continuous transform used in mobile communication, perfectly analyzed.

文件中为几类贝塞尔函数，基于MATLAB编写(Bessel functions of several files, based on MATLAB prepared)

MATHWORKS提供MATLAB和C混合编程用户手册(MATLAB and C mixed programming user manual)

对采集的样例数据进行回归分析，包括一元、多元和病态回归三种情况，并在一定执行概率给出置信区间和回归预测(The collected sample data, regression analysis, including a dollar return of three cases and pathological diversity, and given a certain probability of confidence intervals and perform regression)