Decimation

Introduction to matlab

leach protocol of wireless sensor network

运用matlab语言编写，可用于一维信号分离，可将高频和低频信号分离出来(Using matlab language, can be used for one-dimensional signal separation, high and low frequency signals can be separated)

提供了广义最小方差控制的MATLAB程序，以及基于广义最小方差控制的自校正控制直接与间接算法的MATLAB程序。(Provides a generalized minimum variance control of MATLAB procedures, and direct and indirect algorithm of self-tuning control based on generalized minimum variance control.)

基于matlab的GMSK仿真， 代码 (it is used for matlab )

本教程提供了使用MATLAB的实践性指导，它基于MATLAB6.0版，内容由浅入深，特别是本书对每一条命令的使用格式都作了详细而又简单明了的说明，并配备了例题加以说明其用法，因此，对于初学者自学是很有帮助的；同时，又对数学中的一些深入问题如数值分析、稀疏矩阵、优化理论以及模糊数学等问题进行了较为详细的论述，因此，该书也可作为科技工作者的科学计算工具书。(This tutorial provides a practical guide for using MATLAB, which is based on MATLAB6.0 version of the content of Deep and, in particular the book using the format of each command are detailed but simple instructions, and be equipped with examples on its usage, therefore, is useful for beginners learning the same time, some of the depth of mathematical problems such as numerical analysis, sparse matrix, optimization theory and fuzzy mathematics and other issues discussed in detail, therefore, the Books can also be calculated as the scientific and technological workers, tool.)

信息理论用的工具包，算法已经很全了matlab编写的(Information theory with the toolkit, the algorithm is already very wide, prepared by the matlab)

一種可用於SAR影像上的應用，並且提供使用者簡單的把圖片慮波得到更好的影像辨識(An application can be used on the SAR images, and provides users with a simple wave to get a better picture into account image recognition)

使用SOM自组织映射网络实现可视化聚类源码(SOM SOM visualization cluster source)

在源信号和传输信道未知情况下，只利用接收天线的观测数据抽取源信号，称为盲信号分离.盲信号分离不仅是信号处理界、而且也是神经网络界的研究热点课题，在无线数据通信、雷达、图像、语音、医学以及地震信号处理等领域都具有广阔的应用前景.采用自然梯度法和分阶段学习法。(The source signal and transmission channel is unknown circumstances, using only observational data extraction receiving antenna source signal, known as blind signal separation. Blind signal separation is not only the signal processing community, but also a neural network hot topic in research circles, in the wireless data communications , radar images, audio, medical and seismic signal processing and other fields have broad application prospects. and the phases using the natural gradient learning method.)