smith_chart

libarary of svm for classification

The sourcecode of Universally-Convergent Squared-Operator Iteration Methods for fig3 using MSOM

sep and leach routing protocols in wireless sensor networks is a typical routing protocol

基于matlab GUI界面设计,LYYWKyo参数数学方法是部分子空间法，采用了小波去噪的思想，BP神经网络用于函数拟合与模式识别，PnTuuBt条件包含特征值与特征向量的提取、训练样本以及最后的识别，包括主成分分析、因子分析、贝叶斯分析。( Based on matlab GUI interface design, LYYWKyo parameter Mathematics is part of the subspace, Using wavelet denoising thought, BP neural network function fitting and pattern recognition, PnTuuBt condition Contains the eigenvalue and eigenvector extraction, the training sample, and the final recognition, Including principal component analysis, factor analysis, Bayesian analysis.)

说明：  混沌系统lypunov指数谱，rucklidge系统指数(Chaotic system lypunov index spectrum, rucklidge system index)

120多个用MATLAB编写的信号处理程序，它们是本书各个章节的大部分例题。用MATLAB编写的程序的名称由“exa”开头，接下来是所在的章、节及例题的序号，如exa010101,指的是第1章第1节（即1.1节）的第1个例题，即例1.1.1。如果该程序是为了说明某一个m文件的应用，则在上述名称的后面跟一个下划线，再在后面加上所说明的MATLAB文件的名称，如exa011001_rand，即是例1.10.1,该例用来说明rand.m文件的应用。(More than 120 signal processing programs written in MATLAB are most of the examples in each chapter of this book. The name of the program written in MATLAB begins with "exa", followed by the ordinal number of the chapters, sections and examples, such as exa0101, which refers to the first example of chapter 1, section 1 (i.e. section 1.1), namely example 1.1.1. If the program is to illustrate the application of an M file, then follow the above name with an underscore, and then add the name of the MATLAB file, such as exa011001_rand, which is Example 1.10.1. This example is used to illustrate the application of rand.m file.)

说明：  信道仿真,小尺度衰落信道的MATLAB仿真源码(matlab jakes)

MATLAB编写的ARMA建模程序，可实现UI打开EXCEL文件，自动选取合适滞后阶数ARMA建模和任意几期预测。(ARMA modeling program written in MATLAB, enabling the UI Open EXCEL file and automatically selects the appropriate number of lags several of ARMA modeling and forecasting arbitrary.)

说明：  EKF仅仅利用了非线性函数Taylor展开式的一阶偏导部分（忽略高阶项），常常导致在状态的后验分布的估计上产生较大的误差，影响滤波算法的性能，从而影响整个跟踪系统的性能。最近，在自适应滤波领域又出现了新的算法——无味变换Kalman滤波器（Unscented Kalman Filter-UKF）。UKF的思想不同于EKF滤波，它通过设计少量的σ点，由σ点经由非线性函数的传播，计算出随机向量一、二阶统计特性的传播。因此它比EKF滤波能更好地迫近状态方程的非线性特性，从而比EKF滤波具有更高的估计精度。 (EKF only uses non-linear function of the first-order Taylor expansion of some partial derivatives (ignoring higher order terms), often leading to the posterior distribution of the state estimates to generate large errors affect the performance of filtering algorithms, which affect the whole tracking system performance. Recently, the field of adaptive filtering algorithms and the emergence of new- and tasteless transform Kalman filter (Unscented Kalman Filter-UKF). EKF UKF filter is different from the idea that it points through the design of a small amount of σ by σ point spread through the nonlinear function to calculate the random vector first and second order statistical properties of the transmission. Therefore it is better than the EKF filter nonlinear characteristics equation of state approach, which is more than the EKF filter estimation accuracy.)

说明：  AM信号产生与相关解调的MATALB仿真程序(MATALB simulation program for AM signal generation and correlation demodulation)