sun_mdl_base

说明：  光通信系统的MATLAB实现，在OPTISYSTEM中运行(run in optisystem)

為jacobi與gauss seidal迭代法 只要把A,b,N更換成你要的即可(To jacobi and gauss seidal iterative method as long as the A, b, N you want to replace)

MY AREA OF WORKING IS ON IMAGE WATERMARKING.. I WANT SOME HELP REGARDING THAT..

说明：   经典控制理论MATLAB-GUI设计(classical control theory MATLAB- GUI design)

距离扩展目标的双门限恒虚警检测器及性能分析.pdf(Double Threshold CFAR Detector of Range-spread Target and Its Performance Analysis)

chen分数阶的吸引子仿真，很容易实现的，希望可以帮助你。一起学习混沌吧。(chen fractional attractor simulation, it is easy to achieve, I hope you can help. With learning chaos.)

搭建的IEEE14节点阻抗仿真模型,里面参数齐全、结果正确。(The IEEE14 nodes impedance simulation model)

These are codes for system identification using various algorithm like LMS,RLS,PSO+FLANN

说明：  共轭梯度法（Conjugate Gradient）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。 在各种优化算法中，共轭梯度法是非常重要的一种。其优点是所需存储量小，具有步收敛性，稳定性高，而且不需要任何外来参数。(The Conjugate Gradient method is a method between the steepest descent method and the Newton method. It only needs to use the first derivative information, but overcomes the shortcomings of the steepest descent method and avoids the need for the Newton method to store And the calculation of Hesse matrix and the inverse of the shortcomings, conjugate gradient method is not only to solve large-scale linear equations one of the most useful methods, but also solution for large-scale nonlinear optimization of one of the most effective algorithm. In a variety of optimization algorithms, conjugate gradient method is a very important one. The advantage is that the required storage capacity is small, with step convergence, high stability, and does not require any external parameters.)

Used to simulate fourth-folder dendrite growth