jisuanjizucheng

主要应用Matlab实现均值漂移算法在图像平滑中应用(Application of Matlab to achieve the major shift algorithm applied in image smoothing)

本代码包含遗传算法matlab工具箱中部分代码，与GAmat1.rar，GAmat2.rar共同使用(This code contains the genetic algorithm matlab toolbox, part of the code, and GAmat1.rar, GAmat2.rar common use)

雅克比迭代法 求Hilbert矩阵病态方程组(Iterative Method Jacobian matrix pathological Hilbert equations)

SAR信号处理程序，配有详细说明，请打开后查看，matlab编程(SAR emulation)

产生两不迥频率的信号，并对两信号作复数FFT变换，找出频率为50Hz的信号对其进行能量计算(Two distant signal is not generated frequency, and two signals for complex FFT transform to identify the frequency of 50Hz signal to calculate its energy)

粒子滤波预测电池寿命，并且以不确定性概率输出结果。(Particle Filter estimated battery life, and with the uncertainty probability output.)

Tank Level Control using PID

this source code is good

A.2 Open Image Files This function looks for x-ray images (.tif) in directory ‘dname’ and creates a movie of I(q) versus q and saves the corresponding 3D matrix. ‘TempA’ and ‘TempB’ are the slope and y-intercept of the ramp temperature profile, respectively. Variables ‘timeA’ and ‘timeB’ are the slope and y-intercept of the time dependence on the frame number. ‘IC1A’ and ‘IC1B’ are the slope and y-intercept of the IC1 value (prior to sample) dependence on the frame number. It load background matrices ‘B’ which should be double-format and corrected for IC1 and any difference for acquisition time. This function calls radialintegrationBNL A.4 Lorentz Correction This function creates and saves the Lorentz-corrected intensity matrix calculated the intensity matrix created in A.2. It also saves each frame as a separate ascii file for crystallinity uation in Origin or other software.

共轭梯度法是介于最速下降法与牛顿法之间的一个方法，它仅需利用一阶导数信息，但克服了最速下降法收敛慢的缺点，又避免了牛顿法需要存储和计算Hesse矩阵并求逆的缺点，共轭梯度法不仅是解决大型线性方程组最有用的方法之一，也是解大型非线性最优化最有效的算法之一。(Conjugate gradient method is between the steepest descent method and Newton method between a method that only use the first derivative information, but the steepest descent method to overcome the disadvantage of slow convergence, but also avoids the need to store and calculate Newton Hesse matrix and the shortcomings of the inverse, conjugate gradient method is not only linear equations to solve large-scale one of the most useful, large-scale nonlinear optimization solution is also the most efficient algorithms.)