affine-transformation

禁忌搜索算法的matlab实现，以旅行商问题为例，使用该算法找出满意解。(Tabu search algorithm matlab realize, to the traveling salesman problem, for example, the use of the algorithm to find satisfactory solution.)

Transient Pipe Flow: Compute the transient velocity profile of a flow in a pipe.

这是matlab2011a的源码教程，可用于学习MATLAB的所有功能。(it is the sourse pro about the book <MATLAB 2011a>.it can be used to learn MATLAB)

3Easy Small Cell Backhaul LTE基站回传设备介绍。(3Easy Small Cell Backhaul Feb 2012.rar)

yalmip最新文档，可在matlab中优化使用(Yalmip latest document, can be used in MATLAB optimization)

电力系统传统电网结构下潮流方程中雅克比矩阵的生成程序(Traditional power system grid structure under flow equations Jacobian matrix generation program)

kpib.m contains code for GPIB and serial port communication for a number of scientific instruments, organized so that a single common command syntax can operate them all. For example, the command: r = kpib(INSTRUMENT,GPIB, read ) will return the voltage and current reading from a number of different power supplies. The goal is to be able to write matlab code that can accommodate changing instruments and experimental setups with minimum hassle. If INSTRUMENT and GPIB are defined as constants at the beginning of your code, then they can be changed to accommodate new equipment, and the rest of the code is unchanged. In addition, kpib can test whether an instrument exists at an address and read and write arbitrary strings to instruments for testing.

This simulink model simulates the damped driven pendulum, showing it s chaotic motion. theta = angle of pendulum omega = (d/dt)theta = angular velocity Gamma(t) = gcos(phi) = Force omega_d = (d/dt) phi Gamma(t) = (d/dt)omega + omega/Q + sin(theta) Play with the initial conditions (omega_0, theta_0, phi_0 = omega(t=0), theta(t=0), phi(t=0)) and the system parameters (g, Q, omega_d) and the solver parameters/method. Chaos can be seen for Q=2, omega_d=w/3. The program outputs to Matlab time, theta(time) & omega(time). Plot the phase space via: plot(mod(theta+pi, 2*pi)-pi, omega, . ) Plot the Poincare sections using: t_P = (0:2*pi/omega_d:max(time)) plot(mod(spline(time, theta+pi, t_P), 2*pi)-pi, spline(time, omega, t_P), . ) System is described in: "Fractal basin boundaries and intermittency in the driven damped pendulum" E. G. Gwinn and R. M. Westervelt PRA 33(6):4143 (1986) (This simulink model simulates the damped driven pendulum, showing it s chaotic motion. theta = angle of pendulum omega = (d/dt)theta = angular velocity Gamma(t) = gcos(phi) = Force omega_d = (d/dt) phi Gamma(t) = (d/dt)omega+ omega/Q+ sin(theta) Play with the initial conditions (omega_0, theta_0, phi_0 = omega(t=0), theta(t=0), phi(t=0)) and the system parameters (g, Q, omega_d) and the solver parameters/method. Chaos can be seen for Q=2, omega_d=w/3. The program outputs to Matlab time, theta(time) & omega(time). Plot the phase space via: plot(mod(theta+pi, 2*pi)-pi, omega, . ) Plot the Poincare sections using: t_P = (0:2*pi/omega_d:max(time)) plot(mod(spline(time, theta+pi, t_P), 2*pi)-pi, spline(time, omega, t_P), . ) System is described in: "Fractal basin boundaries and intermittency in the driven damped pendulum" E. G. Gwinn and R. M. Westervelt PRA 33(6):4143 (1986) )

不错的GM_EM代码。用于聚类分析等方面。( GM_EM- fit a Gaussian mixture model to N points located in n-dimensional space. Note: This function requires the Statistical Toolbox and, if you wish to plot (for k = 2), the function error_ellipse Elementary usage: GM_EM(X,k)- fit a GMM to X, where X is N x n and k is the number of clusters. Algorithm follows steps outlined in Bishop (2009) Pattern Recognition and Machine Learning , Chapter 9. Additional inputs: bn_noise- allow for uniform background noise term ( T or F , default T ). If T , relevant classification uses the (k+1)th cluster reps- number of repetitions with different initial conditions (default = 10). Note: only the best fit (in a likelihood sense) is returned. max_iters- maximum iteration number for EM algorithm (default = 100) tol- tolerance value (default = 0.01) Outputs idx- classification/labelling of data in X mu- GM centres)

MATLAB神经网络仿真与应用很详细的一本书 里面含有代码 就是优点简单 适合初学者(MATLAB neural network emulation and application of a very detailed book that contains a code that is suitable for beginners and the advantages of simple)