Gilbert-Strang5

噪声调频信号的误码率的仿真过程，采用matlab语言(Noise FM signal BER simulation using matlab language)

求解指派问题，再输入指令后，根据信息自动快速的求出最佳分配方案(Solve the assignment problem, and then enter the command, according to the information automatically and quickly find the optimal allocation scheme)

铁电存储器MFIS-FET结构开态电流和关态电流的描述(FRAM MFIS-FET structure of open state current and off current description)

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)

这是一个利用水平集方法进行分割的方法，是目前使用越来越多的方法，并且有严格的数学依据(This is a level set method using segmentation method is currently used by more and more ways, and has a strict mathematical basis for)

基于进化规划算法的医学图像描述 分割函数是最大熵双阈值函数(the segmentation of image)

考虑不同频率复用因子的情况下用户的容量和SINR值变化情况，得出在FRF为3的情况下达到最大的值(calculate the edge user under different frequence reuse factor the performance of capacity and SINR. The result is that when FRF equals to 3 achieve the maximum value.)

Ce fichier mdl permet de tracer la caractéristique pv

希望给辛苦科研的人带来一点点帮助--学习因子可以变化的PSO算法，不再是c1=c2=2，粒子进化更加灵活，下面是学习因子同步变化的pso，调用形式为[xm,fv]=LNCPSO(fitness,N,cmax,cmin,w,M,D)(People who want to work hard to bring a little bit of research to help- learning factor can vary PSO algorithm is no longer c1 = c2 = 2, particle evolution is more flexible, learning factor is below synchronous changes pso, calling in the form of [xm, fv] = LNCPSO (fitness, N, cmax, cmin, w, M, D))

here data is given and estimate using ML estimation in pattern recognition