GM1_1

说明：  既可以用于高压输电网的潮流解算，又可以用于低压配电网的潮流解算，还可以同时解算输电网 加配电网的混合潮流问题,程序为PQ 分解法.(Both the trend for high-voltage transmission grid solver, but also the trend for low voltage distribution network solver, solver can also increase with the power transmission grid hybrid power flow problem, the program for the PQ decomposition.)

amplitube modulation code matlab

MATLAB关于神经网络的仿真与应用，8个m文件源程序(On the simulation of neural network)

matlab reference manual

qpsk_modulation in matlab

canny edge detection method

一个完整的基于LMS和RLS改进算法的语音增强MATLAB程序，包括了输入输出序列和读取数据，自适应增强算法的程序(Based on a complete LMS and RLS algorithms to improve speech enhancement MATLAB procedures, including the input and output sequences and read data, adaptive enhancement algorithm procedure)

分布式压缩感知中的SOMP算法，可以用于实现JSM-2的场景的信号的重构(The SOMP Distributed compressed sensing algorithm can be used to implement the JSM-2 signal of the reconstructed scene)

Hidden-Unit Conditional Random Fields 工具箱，可以用于训练linearCRF和和L.J.P. van der Maaten, M. Welling 提出的huCRF(We provide Matlab code that implements the training and evaluation of hidden-unit CRFs, as well as code to reproduce the results of our experiments. The code implements four different training algorithms: (1) a batch learner that uses L-BFGS, (2) a stochastic gradient descent learner, (3) an online perceptron training algorithm, and (4) an online large-margin perceptron algorithm. The code can also be used to perform (conditional) herding in hidden-unit CRFs. )

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.)