hengxujing

经典的图像修复程序，matlab语言描写(The classic image fix, matlab Descriptions)

用MATLAB解偏微分方程。讨论了以 中偏徽分方程工具箱的用法 用这个工具箱解方程的过程是 确定待解的偏徽分 方程 确定边界条件 确定方程所在城 的几何形状 划分有限元 解方程(Solution of partial differential equations with MATLAB. Discussed in the partial differential equation toolbox emblem with the use of this toolbox is the process of solving equations to be solved to determine the emblem of the partial differential equations boundary conditions to determine the geometry of the city where the equations into the finite element solution of equation)

PARTIAL DIFFERENTIAL EQUATION MODELS WITH MATLAB

从mathswork上下的关于语音识别的完整程序，有GUI实现，相当的全面(Down from mathswork complete on speech recognition procedures, GUI implementation, very comprehensive)

用来估计M-copula中各个部分前面系数值的程序(Procedures used to estimate the various parts of the coefficient in front of a copula in the M-copula)

信号检测与估值大作业，MATLAB画出ROC理论曲线，蒙特卡洛实验画出时间曲线(Signal Detection and valuation of large operations, MATLAB draw ROC curve theory, Monte Carlo experiment shown time curve)

MULTIDIMENSIONAL SCALING in matlab by Mark Steyvers 1999 ％needs optimization toolbox ％Modified by Bruce Land ％--Data via globals to anaylsis programs ％--3D plotting with color coded groups ％--Mapping of MDS space to spike train temporal profiles as described in ％Aronov, et.al. "Neural coding of spatial phase in V1 of the Macaque" in ％press J. Neurophysiology(MULTIDIMENSIONAL SCALING in Matlab by Mar 1999% k Steyvers needs optimization toolbox% M odified by Bruce Land%-- Data via globals to ana ylsis programs%-- 3D plotting with color coded groups%-- Mapping of MDS space to spike train te mporal profiles as described in% Aronov, et.al. "Neural coding of spatial phase in V1 of t he Macaque "in press J. Neurophysiology%)

matpower 工具箱,电力系统最优化工具箱，包括潮流计算和最优潮流等(matpower toolbox)

说明：  非瑞利混响和杂波信号的产生及其统计特性的仿真程序(Simulation of non-Rayleigh reverberation and clutter)

人工智能，解决复杂问题。比如说，解决最优下料问题，解决最优规划问题等。(Artificial intelligence to solve complex problems. For example, the optimal solution under the material and solve optimal planning problems.)