xiandainibianjishu-liufengjun

介绍了神经网络的基本知识，适合初学者学习(Introduce a basic knowledge of neural networks, suitable for beginners to learn)

说明：  现代通信系统(MATLAB)版本，作者：普罗克斯等著，刘树棠译。本书采用MATLAB作为“虚拟实验室”，给出了解决“现代通信系统”课程中涉及的各方面问题的分析思路、方法、MATLAB脚本（或程序）文件和处理结果示例(Modern communication systems (MATLAB) version of: Proulx waiting, Liu Shutang translated. This book uses MATLAB as a &quot virtual laboratory&quot , presented to solve the &quot modern communication systems,&quot course involved in all aspects of the analysis of ideas, methods, MATLAB script (or program) file, and Chu Li Jieguoshili)

此文件为 在matlab中rgb2gray的方式(way of rgb2gray in matlab)

neural network using new development method to classifiy

HEED protocol used in wireless sensor networks

数值分析的EULER法，Gabor小波变换与PCA的人脸识别代码，小波包分析提取振动信号中的特征频率。( EULER numerical analysis method, Gabor wavelet transform and PCA face recognition code, Wavelet packet analysis to extract vibration signal characteristic frequency.)

此程序的功能是用自相关法求使信号s均方预测误差为最小的预测系数 (Feature of this program is to use the autocorrelation method for the signal s smallest mean squared prediction error of prediction coefficients)

提供了一个扩展卡尔曼滤波源程序，无迹卡尔曼滤波源程序，交互式模型卡尔曼滤波源程序，扩展卡尔曼滤波及无迹卡尔曼滤波对比源程序及一个扩展卡尔曼滤波的目标跟踪算法源程序。(An extended kalman filter source program, no trace kalman filter source program, interactive model kalman filter source program, extended kalman filter and non trace kalman filter contrast source program and an extended kalman filter target tracking algorithm source program are provided.)

说明：  EM 算法是Dempster，Laind，Rubin于1977年提出的求参数极大似然估计的一种方法，它可以从非完整数据集中对参数进行 MLE估计，是一种非常简单实用的学习算法。这种方法可以广泛地应用于处理缺损数据、截尾数据以及带有噪声等所谓的不完全数据，可以具体来说，我们可以利用EM算法来填充样本中的缺失数据、发现隐藏变量的值、估计HMM中的参数、估计有限混合分布中的参数以及可以进行无监督聚类等等。(EM algorithm is a method for maximum likelihood estimation of parameters proposed by Dempster, Laind and Rubin in 1977. It can estimate parameters from incomplete data sets by MLE. It is a very simple and practical learning algorithm. This method can be widely used in dealing with the so-called incomplete data such as defective data, censored data and noisy data. Specifically, we can use EM algorithm to fill missing data in samples, find hidden variable values, estimate parameters in HMM, estimate parameters in finite mixed distribution, and so on. Unsupervised clustering and so on.)

抑制载波双边带调幅　相干解调　DSBMODE 与离散大载波AM不同(Carrier suppression amplitude modulation with coherent demodulation bilateral DSBMODE with different discrete large-carrier AM)