linear-category

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.)

matlab实现的k均值聚类算法，可以实现对大量数据的有效分类(matlab implementation of the k-means clustering algorithm, can achieve a large amount of data on an effective classification)

matlab下的adaptfilt，用于自适应滤波器，滤波信号堪比输入无噪音信号(matlab under adaptfilt, for the adaptive filter, filtering the signal comparable to the input signal without noise)

PCA的步骤： 1 先将数据中心化； 2 求得的协方差矩阵； 3 求出协方差矩阵的特征值与特征向量； 4 将特征值与特征向量进行排序； 5 根据要降维的维数d’,求得要降维的投影方向； 6 求出降维后的数据； (PCA steps: 1 of the first data center 2 covariance matrix obtained 3 obtained covariance matrix eigenvalues and eigenvectors 4 eigenvalues and eigenvectors will be sorted 5 according to the dimension of dimension reduction d ' , seek to reduce the dimension projection direction 6, the data obtained after the dimensionality reduction )

最小熵解卷积（MED），是一种自适应滤波器设计方法，可以提取冲击成分(Minimum entropy deconvolution (MED), is an adaptive filter design method that can extract the impact of component)

PID模糊控制程序,附带simulink仿真图形(PID fuzzy control procedures)

说明：  QAM的一种实现方法，欢迎使用。谢谢分享(An Implementation Method of QAM are welcome to use. Thank you to share)

信道估计,we will assume that the receiver knows your name, i.e., it knows s (and of course x). Based on this knowledge, the receiver will estimate h using the MVU and MMSE method (for the latter it is also assumed that the variance of the noise σ2 is known at the receiver).(Channel Estimation:we will assume that the receiver knows your name, i.e., it knows s (and of course x). Based on this knowledge, the receiver will estimate h using the MVU and MMSE method (for the latter it is also assumed that the variance of the noise σ2 is known at the receiver).)

AR自适应滤波器，用Kalman滤波器跟踪AR模型的吸收变化(adaptive AR model，use kalman filter to trace the variance of ar coeffience)

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