Advance-NSGA-II

函数HistBackground功能是将高速公路的视频文件中的多帧图片利用统计直方图的方法提取不含运动车辆的背景，(Function HistBackground function is to freeway video files of images using statistical histogram to extract the background without moving vehicles,)

介绍傅里叶变换和数字信号处理的一些书籍，希望对大家有所帮助，基础的书籍。(Introduce the Fourier transform and digital signal processing some of the books, we want to help, based on books.)

这个包实现了ITU - T的G.723.1语音编码器和解码器在Matlab。该方案的目标是提供一个良好的记录和模块化设计方案，实验和研究，以方便使用为基础的实际编码器。 编码器实现了G.723.1的多脉冲模式（在6.3 kb / s的运行）。解码器可以解码的5.3 kb / s的，在6.3 kb的多脉冲/秒，连续传输，数据包丢失隐藏）编码器（所有的ACELP方式。 该编码器和解码器之间的标准接口是位文件（同位文件由ITU - T参考代码产生兼容）。第二个选项之间传递的编码器和解码器使用Matlab的数据信息文件。此选项允许测试通过传递量化或unquantized之间的编码器和解码器的信息。 有报道[1]描述了G.723.1编码与Matlab实现与分布包括在内。 ITU - T建议G.723.1的[2]在线提供。该建议含(This package implements the ITU-T G.723.1 speech coder and decoder in Matlab. The goal of the package is to provide a well-documented and modular program that was designed to facilitate experimentation and research using a practical coder as a base. The coder implements the multipulse mode of G.723.1 (running at 6.3 kb/s). The decoder can decode all modes of the coder (ACELP at 5.3 kb/s, multipulse at 6.3 kb/s, discontinuous-transmission, packet loss concealment). The standard interface between the coder and decoder is a bit file (compatible with the bit files generated by the ITU-T reference code). A second option passes information between the coder and decoder using a Matlab data file. This option allows for testing by passing quantized or unquantized information between the coder and the decoder. A report [1] describing the G.723.1 and the Matlab implementation is included with the distribution. ITU-T Recommendation G.723.1 [2] is available on-line. The recommendation incl)

Back propagation neural network for blasting PPVV prediction

直流电机的双闭环仿真，实现点击的无静差调速功能(Double closed loop simulation of DC motor)

用matlab模拟布朗运动，可输入温度，来估计在该温度下布朗运动的程度(Brownian motion simulation using matlab, you can enter the temperature, to estimate the temperature in the extent of Brownian motion)

code of implementing the K-Nearest Neighbor method

VC++与matlab混合编程实例和VC调用matab生成的DLL说明(The mixed VC++ with matlab programming examples and generated by the VC call matab DLL description)

Title: "Modeling Lung Cancer Diagnosis Using Bayesian Network Inference" This demo illustrates a simple Bayesian Network example for exact probabilistic inference using Pearl s message-passing algorithm. Introduction: Bayesian networks (or belief networks) are probabilistic graphical models representing a set of variables and their dependencies. The graphical nature of Bayesian networks and the ability of describing uncertainty of complex relationships in a compact manner provide a method for modelling almost any type of data.

fingure print in matlab