Helmholtz

本程序基于visual C++ 实现标准正态分布，正态分布累积函数，正态分布累积函数的逆函数分别输出到不同表，是仿真实验的很好参考！(This procedure based on visual C++ Achieve the standard normal distribution, the cumulative distribution function, the cumulative distribution function of the inverse function of the respective output to a different form, is a good reference simulation!)

粒子群优化算法的源程序和pdf课件，还包括几个应用粒子群算法解决优化函数的例子(Particle swarm optimization algorithm source and pdf courseware)

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) )

说明：  tsp的算法讲解和实现，适合学生应用，也适合需要者参考(tsp explanation and implementation algorithms, suitable for students to use, but also for those who need information)

channel modeling S*P(S parameter) to verilog module

Forensic science it the study of objects that relate to a crime. Forensic scientists study evidence so that it can be used in a court of law. Forensic scientists observe, classify, compare, use numbers, measure, predict, interpret data, and draw inferences based on evidence. In this lesson, students will use these science inquiry skills.In this dental image was classify by sift algorithm

the simulation provides computation of target reflectivity data in the deficient elevation domain. Simulations are implemented to test the decoupled least-squares technique for high resolutionspectral estimation of target reflectivity.all seven (7)files should be downloaded for the simulation to work.(dls3D.m,estimate.m,get2S1Data.m,getConstraints.m, getImageData.m,getPixelData.m, getSLICYData.m)

水文趋势、突变点分析的matlab相关程序——Lee-Heghinan法、Mann-Kendall法(Hydrological trends point mutation analysis matlab procedures- Lee-Heghinan France, Mann-Kendall method)

semi conductor text book

rs 里查森迭代法求线性方程组 crs 里查森参数迭代法求线性方程组 grs 里查森迭代法求线性方程组 jacobi 雅可比迭代法求线性方程组 gauseidel 高斯-赛德尔迭代法求线性方程组 SOR 超松弛迭代法求线性方程组 SSOR 对称逐次超松弛迭代法求线性方程组 JOR 雅可比超松弛迭代法求线性方程组 twostep 两步迭代法求线性方程组 fastdown 最速下降法求线性方程组 conjgrad 共轭梯度法求线性方程组 preconjgrad 预处理共轭梯度法求线性方程组 BJ 块雅克比迭代法求线性方程组 BGS 块高斯-赛德尔迭代法求线性方程组 BSOR 块逐次超松弛迭代法求线性方程组 (iterative method of linear equation.)