benforddoc

通用模拟退火优化算法 General simulated annealing algorithm 模拟退火优化算法能过较大限度的避免局部最优解 (General simulated annealing optimization algorithm General simulated annealing algorithm simulated annealing optimization algorithm can have a greater level of local optimal solution to avoid)

说明：  非常好的数学建模资料，有matlab实现，数学建模与数学实验（第3版）课件+matlab(Mathematical modeling of very good information, there is matlab implementation, mathematical modeling and mathematical experiment (3rd Edition) courseware+ matlab)

该书一本很好的MATLAB仿真教程,特别适合初学者,也可以作为专业人员的参考书(Book is a very good tutorial MATLAB simulation, especially for beginners, but also can serve as a professional reference books)

fuuzy logic examle matlab sı vı seviyesi kontrolu

计算三维数据的法矢量并进行调整，里面包括了自己做的实验数据和结果-(The method to calculate the three-dimensional vector data and make adjustments, which includes the experimental data and the results of their own-)

this is the code to calculate magical hilbert transform of a signal.

matlab中生成各种噪声的程序，包括brown噪声,pink噪声，白噪声等(matlab noise generated in a variety of procedures, including the brown noise, pink noise, white noise, etc.)

autocov computes the autocovariance between two column vectors X and Y with same length N using the Fast Fourier Transform algorithm from 0 to N-2. The resulting autocovariance column vector acv is given by the formula: acv(p,1) = 1/(N-p) * sum_{i=1}^{N}(X_{i} - X_bar) * (Y_{i+p} - Y_bar) where X_bar and Y_bar are the mean estimates: X_bar = 1/N * sum_{i=1}^{N} X_{i} Y_bar = 1/N * sum_{i=1}^{N} Y_{i} It satisfies the following identities: 1. variance consistency: if acv = autocov(X,X), then acv(1,1) = var(X) 2. covariance consistence: if acv = autocov(X,Y), then acv(1,1) = cov(X,Y)

说明：  各种观测矩阵，高斯，伯努利，部分哈德玛，随机，托普利兹，循环，部分傅里叶矩阵(Various observation matrices)

利用粒子群算法对直线阵的权系数进行优化，这里只是对相位进行加权，但是程序有很好的宽展功能(Using particle swarm algorithm of linear arrays of the weight coefficient is optimized )