autocorr

里查得森(Richardson)法解偏微分方程的程序。解的是定步长的抛物型偏微分方程： du/dx - a * d2u/dx2 = 0 在程序中可以更改 a 的值以实现不同系数的解。由于它是一种显式格式，解的结果不稳定 在Matlab7下面运行发现竟然有一些值达到十的几十次方,这是算法本身决定的。不是程序有错误(Richard Anderson (Richardson) Solving partial differential equations procedures. Solution is scheduled to step parabolic partial differential equation: du/dx- a* d2u/dx2 = 0 in the procedure can be changed in order to realize the value of a different coefficient of the solution. Because it is an explicit format, the result of instability in the solution of the following Matlab7 running even found some value reached ten dozens of parties, this is the decision algorithm itself. Not a procedural error)

自适应中值滤波的编程,用MATLAB实现的,可能程序有点简单,太是真正能实现的(Adaptive median filter programming with MATLAB realize, and perhaps a bit simple procedure, too is really to achieve the)

matlab 求解job shop scheduling problem 遗传算法 整数编码 双点交叉 溢出位修复(job shop scheduling problem genetic algorithm for integer encoding two-point cross-overflow bit repair)

Matlab simulink radar

利用ode45求解三自由度状态方程常微分方程(Solving ordinary differential equations of three degree of freedom equation of state by using ode45)

z bus formation code using modification

说明：  通带截止频率 =2 4k rad/s，阻带截止频率 =2 8k rad/s，通带波纹系数 =0.3dB, 阻带波纹系数 =50dB,采样频率fs=20000Hz。(The digital filter are the digital signal processing important content, the digital filter may divide into IIR and the FIR two main kinds. As for the IIR digital filter design, we need the help of analog prototype filter, and then transform analog filter into digital filter.)

Traditional single particle reconstruction methods use either the Fourier or the delta function basis to represent the particle density map. We propose a more flexible algorithm that adaptively chooses the basis based on the data. Because the basis adapts to the data, the reconstruction resolution and signal-to-noise ratio (SNR) is improved compared to a reconstruction with a fixed basis. Moreover, the algorithm automatically masks the particle, thereby separating it from the background. This eliminates the need for ad-hoc filtering or masking in the refinement loop. The algorithm is formulated in a Bayesian maximum-a-posteriori framework and uses an efficient optimization algorithm for the maximization. Evaluations using simulated and actual cryogenic electron microscopy data show resolution and SNR improvements as well as the effective masking of particle from background

motion estimation motion estimation motion estimation motion estimation

code source pour compression d image sous matlab