adaptcdma

说明：  这是一篇比较完成的MATLAB编程的教学实例，很值得下载。(This is a relatively complete MATLAB programming teaching examples, it is worth downloading.)

motor simulation using Simulink software for beginners in drives and motor control

matlab符号运算的ppt讲解教程，讲解通俗易懂，易于学习(ppt matlab symbolic computation tutorials explain, easy to understand explanation, easy to learn)

遗传算法求函数极大极小值，可用于简单的最优控制(Genetic algorithms function Minimax, optimal control for simple)

Jackknife PARAFAC, 用在多维线性分解.(Very famous Jackknife parafac, suited for multi-way data decomposition.)

盲源分离（BSS: Blind Source Separation），又称为盲信号分离，是指在信号的理论模型和源信号无法精确获知的情况下，如何从混迭信号（观测信号）中分离出各源信号的过程。盲源分离和盲辨识是盲信号处理的两大类型。盲源分离的目的是求得源信号的最佳估计，盲辨识的目的是求得传输通道混合矩阵。(Blind signal separation (BSS), also known as blind source separation, is the separation of a set of source signals from a set of mixed signals, without the aid of information (or with very little information) about the source signals or the mixing process. This problem is in general highly underdetermined, but useful solutions can be derived under a surprising variety of conditions. Much of the early literature in this field focuses on the separation of temporal signals such as audio. However, blind signal separation is now routinely performed on multidimensional data, such as images and tensors, which may involve no time dimension whatsoever.)

WIRESLESS SENSOR NETWORKS ALGORTHIM 2

说明：  利用Crank-Nicolson 方法解决偏微分方程(using Crank-Nicolson solution PDE)

Turbo code bit interleaved code modulation(BICM)

This file compares three different versions of the Kalman filter. The Kalman filter is used for recursive parameter estimation. The Kalman filter can handle noisy measurements. The first implemented filter (fcn_KF) is the Kalman filter with standard update of the covariance matrix P. The covariance matrix reflects the uncertainties of the predictions. To improve the numerical stability Potter developed a square root update (fcn_KF_SRP) of the covariance matrix P. Another version is the square root covariance update via triangularization (fcn_KF_SRT). This file generates a model. Then the three Kalman filters perform an estimation of the model parameter. At the end the results are compared. Sources: Simon, D. (2006): Optimal state estimation Kaminski, P. (1971): Discrete Square Root Filtering: A Survey of Current Techniques Golub, G. (1996): Matrix Computations