untitledZHU

数字PID的matlab仿真程序，针对刘金琨的先进PID控制的matlab仿真，里面的部分程序进行了修改 第五章(Digital PID of matlab simulation program for Liu Jinkun matlab advanced PID control simulation, which part of the program were modified Chapter)

二维OSTU方法 ，能够自动给出合适阈值 matlab环境下开发(Two-dimensional OSTU method that can automatically give the appropriate thresholds developed under matlab environment)

A Binary Particle Swarm Optimization for Optimal Placement and Sizing of Capacitor Banks in Radial Distribution Feeders with Distorted Substation Voltages

最小二乘法辨识 对系统输入伪随即序列输入，得到输出， 加入噪声，模拟辨识过程(least squares method for identification system importing counterfeit immediately sequence input and output is, by adding noise to simulate the process of identification)

different matlab code for convolution, discrete fourier transform, finite impulse response, inverse DFT, descimator

第四版prokias数字通信之配套代码第九章(source code(matlab )for prokias Digital Communication (4th edition))

在目标被动式跟踪中广泛应用的伪量测变换估计器(PLE)具有良好的误差收敛性。然而由于等价噪声和状态的相关性,该估计器的估计是有偏的。提出的强跟踪滤波器(STF)通过强制白化残差具有自适应地校正估计偏差和迅速跟踪状态变化的能力。STF已经在非线性系统时滞估计、故障诊断与容错控制方面取得了很好的效果。(Passive target tracking is widely used in the pseudo-measurement transform estimator (PLE) has a good error convergence. However, due to the equivalent noise and the relevance of state, the estimator is a biased estimate of. Raised strong tracking filter (STF) has adopted mandatory bleaching residuals adaptively estimated bias correction and rapid tracking of the status change. STF has been estimated in the time-delay nonlinear systems, fault diagnosis and fault-tolerant control has been achieved very good results.)

cut image and corepoint for fingerprint

说明：  双线性插值matlab代码。 子函数: bilinear_interpolat2()采用双线形插值实现图像放大 参数说明： I_in - 输入待放大图像 N - 放大系数 I_out - 返回的放大图像

Speech Recognition - Numbers 1 to 5 Energy normalization and time alignment References: [1] L. Rabiner and B.H. Juang,Fundamentals of Speech Recognition, Prentice-Hall, 1993. ％ [2] P.E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. ％ [3] J.D. Markel and A.H. Gray,Linear Prediction of Speech(Speech Recognition-Numbers 1 to 5 Energy n ormalization and time alignment References : [1] L. Paras and B. H. Juang, Fundamentals of Speech Recognition. Prentice-Hall, 1993. % [2] P. E. Papamichalis, Practical Approaches to Speech Coding, Prentice-Hall, 1987. % [3] J. D. Markel and A. H. Gray, Linear Prediction of Speech)