IV-curve

matlab安装后无法运行状况下的解决方案(the matlab installation can not run the solution under the condition)

数字图像处理MATLAB演示程序。包含图像灰度处理、平滑、锐化、压缩等。运行demo.m执行主界面。(Digital Image Processing MATLAB demonstration program. Contains the image gray scale processing, smoothing, sharpening, compression. The run demo.m perform the main interface.)

matalab code for qam

偏最小二乘法是一种数学优化技术，它通过最小化误差的平方和找到一组数据的最佳函数匹配。 用最简的方法求得一些绝对不可知的真值，而令误差平方之和为最小。(Partial least squares method is a kind of mathematical optimization technique, it through the minimum error sum of squares to find a set of data the best function matching. With the Jane s method for some absolutely unknowable true value, and make the sum of error square to a minimum.)

一个简单的遗传算法的例子程序，用作初学者的实验调试，(A simple example of the genetic algorithm process, as a beginner experiment debugging,)

Matlab source for conventional, SINR, Null-steering and minimum variance bemforming in 8 sensors

1.理解显式差分格式的依赖区域。写出所给微分方程的依赖区域。 2.会求显式差分格式的截断误差。 3.能写出显式差分格式的CFL条件，显式差分格式的稳定性条件，写出显式差分格式的收敛性条件。 (Understanding the explicit difference scheme dependent region. Write to differential equations dependent region. 2 will seek explicit difference scheme truncation error. Explicit Difference Scheme CFL conditions, the stability condition of the explicit difference scheme able to write, write explicit difference scheme convergence conditions.)

Matlab code for calculating orbital elements

数学建模中常用的方法：类比法、二分法、差分法、变分法、图论法、层次分析法、数据拟合法、回归分析法、数学规划（线性规划，非线性规划，整数规划，动态规划，目标规划）、机理分析、排队方法、对策方法、决策方法、模糊评判方法、时间序列方法、灰色理论方法、现代优化算法（禁忌搜索算法，模拟退火算法，遗传算法，神经网络）(Mathematical modeling methods commonly used: analog, Dichotomy, difference method, variational method, graph theory, analytic hierarchy process, data fitting, regression analysis, mathematical programming (linear programming, nonlinear programming, integer programming, dynamic programming, goal programming), mechanism analysis, queuing, countermeasure methods, decision-making methods, fuzzy uation method, time series method, gray theory, modern optimization algorithms (tabu search algorithm, simulated annealing algorithm, genetic algorithms, neural networks))

说明：  在Bialas與Karwan的第 解演算法 [13] 則是搜尋限制式解域中的端點，並且歸類為已搜尋端點集合、未搜尋端點集合、可行解端點集合、非可行解端點集合，再從可行解端點集合中找出使高階目標值最佳的端點。(Bialas and Karwan in the first solution algorithm [13] is the search for solutions in the domain of endpoint constraints, and the endpoints are classified as a collection of search, not search a collection of endpoints, the endpoint set of feasible solutions, non-feasible solution side point set, then the endpoint from the set of feasible solutions in order to identify the best target endpoint.)