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说明：  求解细线天线或细直导线的辐射或散射特性的矩量法分析论文(Solution of thin wire antennas or small straight wire radiation or scattering characteristics of the moment method analysis of papers)

说明：  一些适合初学者的MATLAB程序代码，以及功能介绍。(Some MATLAB code for beginners, and Function.)

VTI介质中波动方程的传播规律的速度规律对于认识各项异性介质介质的传播规律有一定的指导作用(asdggggggggggasdgfaaaaaaaaaaaa)

its for a wsn project

说明：  用MATLAB实现（7，3）循环码算法，很好的体现了循环码的特性(Using MATLAB implementation (7,3) cyclic code algorithm shows good characteristics of cyclic codes)

提高风力机将风能转化为机械能的效率，根据我国西北地区的风频风能曲线，用最优设计攻角沿叶片轴线的非线性分布修正传统Wilson算法，优化设计大型水平轴风力机叶片的气动性 能．该优化设计利用Madab优化工具箱，优化速度干涉因子的迭代计算，提高计算效率；考虑多翼型和变攻角等因素对叶片外形优化的影响，从结构及加工工艺角度修正翼型．通过对1．2MW风力发电机组叶片外形的气动性能计算和优化设计，结果表明该优化设计的有效性和可行性，可为风力机叶片外形设计提供参考．(Improve wind turbine wind energy into mechanical energy efficiency, according to the Northwest China wind frequency wind power curve, optimum design angle of attack along the blade axis of traditional non-linear distribution correction Wilson algorithm to optimize the design of the aerodynamic performance of the large-scale horizontal axis wind turbine blades . The Optimal Design Optimization Toolbox Madab optimized for speed interference factor iterative calculation to improve computational efficiency consider multi-airfoil and change the angle of attack and other factors on the blade shape optimization, airfoil from the structure and processing angle correction. By 1.2MW wind turbine blade shape aerodynamic performance calculation and optimization design, the results show that the effectiveness and feasibility of the optimized design can provide a reference for the wind turbine blade shape design.)

q学习算法，在MATLAB中实现，本人已运行成功，希望有帮助(q learning algorithm implemented in MATLAB, I have run successfully, the hope of helping)

EA=R factorization in matlabn

This is an efficient implementation of the algorithm for calculating the universal image quality index proposed by Zhou Wang and Alan C. Bovik. Please refer to the paper "A Universal Image Quality Index" by Zhou Wang and Alan C. Bovik, published in IEEE Signal Processing Letters, 2001.

Fit time series Q(t) to a logistic function. Inputs (vectors of same size): t (time) & Q Outputs: Qpre (logistic model fit to data) and three independent parameters: thalf, Qinf, and a, describing the logistic Q(t) = Qinf/(1 + exp(-a*(t-thalf))) Qinf is value as t --> infinity thalf is time of symmetric inflection point a is time decay constant Written by James Conder, Southern Illinois University, Oct. 2010