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Digital filter simulation in Matlab.

matlab高级编程 苏金明《Matlab高级编程》(matlab advanced programming Su Jinming " Matlab Advanced Programming" )

用matlab对duffing方程进行求解，duffing方程是混沌算法的主要分支之一，具有效果较为良好的微弱信号检测功能。(Duffing equation is solved using matlab Duffing equation is one of the main branches of the chaotic algorithm with a the effect weak signal detection function.)

基于光流场的视频运动检测,介绍了光流的原理，计算出运动图像的光流场。(Optical flow-based video motion detection, introduced the principle of optical flow to calculate the optical flow motion picture)

运用传输矩阵法计算仿真一维光子晶体双缺陷(use TTM calculating the double defects of 1D PC)

利用pca计算出两个统计量，通过对统计量的大小比较以判定故障是否发生。(Pca is calculated using two statistics, by comparing the size of the statistic to determine whether the fault occurs.)

用Ziegler--Nichols整定公式来求P,PI,PID的个参数，其中Gc是校正器的传递函数,kp为比例系数， Ti为积分时间常数，Td为微分时间常数，输入参量vars为带迟滞--惯性环节模型的KT τ(With Ziegler- Nichols tuning formula to seek P, PI, PID' s parameters, which Gc is the corrector transfer function, kp is proportional coefficient, Ti the integral time constant, Td for the differential time constant, input parameters vars as with hysteresis- inertia model of the KT τ)

粗糙集理论是一种基于对现实世界进行不确定描述的理论,属性约简是粗糙集理论的核心理论之一。对粗糙集理论进行阐述,并给出基于启发式的知识约简算法,最后结合MATLAB程序实例说明了该算法的可行性与有效性。(Rough set theory is based on the uncertainty of the real world is described in theory, attribute reduction is the core theory of rough set theory one. Elaborate on the rough set theory, and gives the knowledge-based heuristic reduction algorithm, and finally with MATLAB program example illustrates the feasibility and effectiveness of the algorithm.)

主成分分析法，主要用在光谱处理上的，包括可见和近红外光谱，对于其他的一些统计学数据也比较适用，包括原数据和处理后的数据(Principal component analysis (pca), mainly used on spectrum processing, including visible and near infrared spectrum, and is also applicable for other statistical data)

基于二阶泛模型的无模型自适应控制及参数整定，充分利用无模型自适应控制边建模边控制的特点，推导基于二阶泛模型的改进无模型自适应控制，应用辨识出的近似模型针对不同目标函数进行优化(Pan model based on second order approximation model of model-free adaptive control and parameter tuning, make full use of model-free adaptive control side edge control modeling features derived model-free adaptive control model based on improved second-order pan, identify the application The objective function to be optimized for different)