TM_image_segment_watershed

光纤微振动传感器之相位OTDR方案信号处理程序，基于matlab程序的处理，可以直接仿真。(Fiber distributed disturbance sensor, phase OTDR scheme signal processing program, based on matlab program，can be simulated directly.)

CHAPTER 10 控制系統的設計 許多受控程序的轉移函數包含一對或更多對的共軛複數極點。在s 平面中若複數 根非常接近虛數軸，則閉迴路系統會變成輕微阻尼或不穩定(CHAPTER 10 control system design of many controlled program transfer function contains a pair or more pairs of conjugate complex number of poles. If the plural in the s-plane root number very close to the imaginary axis, then the closed loop system becomes slightly damped or unstable)

here is the matlab source code for parallel port communication

MMAdapGA:用多变异位自适应遗传优化求解一维无约束优化问题 (MMAdapGA: with changeable ectopic adaptive genetic optimization solution of one-dimensional unconstrained optimization problems)

应用Firsher线性判别器在matlab环境中实现模式识别的分类，简单直接，望采纳(Pattern recognition classification application Firsher linear discriminant in the Matlab environment is simple and direct, looking to adopt)

说明：  MOPSO多目标粒子群优化算法MATLAB实现(Implementation of MOPSO multi-objective particle swarm optimization algorithm in MATLAB)

该压缩包包括两个m文件，一个为IEEE推荐的UWB信道模型的matlab仿真程序，另一个为对应的RMS时延扩展计算，并附带了一个文档文件作说明。(The archive includes two m files, one for the IEEE UWB channel model recommended by the matlab simulation program, and the other for the corresponding calculation of RMS delay spread, and comes with a document file for instructions.)

this is a mat lab tutorial thanks

经典的扩展卡尔曼滤波卡尔曼滤波程序，首先对非线性函数取一阶近似，生成近似的新型函数，然后进行卡尔曼滤波，通过一步状态和估协方差估计产生新息，然后生成状态预测(Classical extended Kalman filter, Kalman filter procedure, first take the first order approximation of nonlinear function to generate the new function approximation, and then proceed to the Kalman filter step state estimate covariance is estimated to generate new interest, and then generate the state prediction)

MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成 (MUSIC algorithm is a feature space based on matrix decomposition method. From the geometric point of view, the observed signal space can be decomposed into signal subspace and noise subspace, it is clear that two spaces are orthogonal. Signal subspace to the data received by the array covariance matrix and the eigenvector corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector corresponding to the composition )