Application-au-problEme-du-pendule-inverse

说明：  详细说明Matlab常见图像处理函数，方便Matlab的学习(Details Matlab common image processing functions, to facilitate the learning Matlab)

说明：  在雷达信号处理中，在确定波达方向是的波峰形成算法(In radar signal processing, in determining the direction of arrival of the peak is the formation of algorithm)

susan用PML边界条件编写的FDTD三维程序(susan with PML boundary conditions for the preparation of three-dimensional FDTD program)

提供了一个简单的模拟退火算法的示例。能够帮助初学者快速掌握模拟退火算法的内容。(Provides an example of a simple simulated annealing algorithm. Can help beginners to quickly master the content of simulated annealing algorithm.)

SVM(支撑向量机）分类MATLAB程序，需要安装SVM工具箱(SVM (support vector machine) classifier matlab program, you need to install SVM toolbox)

元胞自动机(Cellular Automata，简称CA，也有人译为细胞自动机、点格自动机、分子自动机或单元自动机)。(Cellular automata (Cellular Automata, called CA, it was also translated into cellular automata, lattice automata, automaton molecule or cell automata).)

用于绘制加工稳定性耳垂图，可以确定不同参数下的稳定性加工极限(For drawing processing stability lobe diagram, can determine the limit of machining stability under different parameters)

用ＭＡＴＬＡＢ实现正交频分复用（ＯＦＤＭ）信道的模拟(Using MATLAB to achieve orthogonal frequency division multiplexing (OFDM) channel simulation)

数字助听器中多通道响度补偿方法的研究.pdf(Multi-channel digital hearing aid loudness compensation method. Pdf)

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.)