jack_immune

一本介绍将音乐与概率知识相结合的英文原版书籍，对于研究音乐的数学模型有很重要的参考价值，对于研究提取音乐中各种参数提取的朋友们可能很有帮助。(An introductory knowledge of music and the probability of a combination of the original English edition of books, music for studying mathematical models have a very important reference value for studying music extract various parameters extracted friends might be helpful.)

matlab中解决一般线性方程组 微分方程组等各种方程类型的解决方法 入门级的好帮手(matlab help in solving various types of equations of general solutions of differential equations of linear equations, such as the entry-level)

说明：  基于MVDR的聚焦波束形成的辐射噪声源近场定位方法(Based on MVDR Beamforming focus near-field radiation noise source localization)

用matlab 来实现用遗传算法解决tsp问题。(Using matlab to achieve using genetic algorithms to solve the problem tsp.)

空间普估计之mvm算法 此算法是music算法的改进算法(S & P estimates mvm space algorithm This algorithm is music algorithm improved algorithm)

Rayleigh Fading Channel Signal Generator Using the Dent Model (a modification to the Jakes Model)

example to matlab/simulink power system model

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

语音增强的的MATLAB代码，给有需要的人，欢迎交流(Speech Enhancement of MATLAB code, there is need to give the people are welcome to communicate)

基于方差约束 ,研究一类不确定线性定常随机离散系统的 H ∞滤波问题。提出了一种 鲁棒滤波的新算法 ,该算法克服构造对角矩阵约束性较强( H ∞filtering problem under the constraint of variance was discussed for a class of linear stochastic uncertain system. A new algorithm of robust filter design was proposed which avoids strict constraint in constructing diagonal matrix to meet upper bound of variance. The robust filter with both constraints of variance and H ∞was given based on linear matrix inequality (LM I) )