shu_zhi_ji_suan(matlab)p4

说明：  汉明码生成，74和1511汉明码的生产，以及其检错能力的验证(Hamming code generation, 74 and the 1511 production of Hamming codes and their error detection ability for)

基于matlab 电力系统潮流计算 牛顿拉夫逊法 采用极坐标运算 经过测试 运行良好(failed to translate)

code matlab solve linear equations

该代码由matlab编写而成，主要用于查值计算(The code from matlab prepared, mainly for search terms)

matlab计算常微分方程，讲解通俗易懂(matlab computing ordinary differential equations, explain straightaway)

坐标变换常模盲均衡算法，用于处理高阶QAM信号(Coordinate transformation norm blind equalization algorithm for high-order QAM signal processing)

- XCS for Dynamic Environments + Continuous versions of XCS + Test problem: real multiplexer + Experiments: XCS is explored in dynamic environments with different magnitudes of change to the underlying concepts. +Reference papers: H.H. Dam, H.A. Abbass, C.J. Lokan, Evolutionary Online Data Mining – an Investigation in a Dynamic Environment. 2005, accepted for a book chapter in Springer Series on Studies in Computational Intelligence H.H. Dam, H.A. Abbass, C.J. Lokan, Be Real! XCS with Continuous-Valued Inputs. IWLCS 2005, (International Workshop on Learning Classifier Systems). Washington DC, June 2005.(- XCS for Continuous Dynamic Environments Test versions of XCS problem : real multiplexer Experiments : XCS is explored in dynamic environments with di fferent magnitudes of change to the underlying concepts. Reference papers : H. H. Dam, H. A. Abbass, C. J. Lokan. Evolutionary Online Data Mining-an Investiga tion in a Dynamic Environment. 2005. accepted for a book chapter in Springer Series o n Studies in Computational Intelligence H.H. D am, H. A. Abbass, C. J. Lokan. Be Real! XCS with Continuous- Valued Inputs. IW LCS 2005. (International Workshop on Learning Classifi er Systems). Washington DC, June 2005.)

说明：  This code simulates one dimensional resonance by FDTD

Matlab中文帮助，对于我们学习，理解这款软件有很大的帮助(Matlab Chinese help for us to learn, to understand this software very helpful)

MUSIC算法是一种基于矩阵特征空间分解的方法。从几何角度讲，信号处理的观测空间可以分解为信号子空间和噪声子空间，显然这两个空间是正交的。信号子空间由阵列接收到的数据协方差矩阵中与信号对应的特征向量组成，噪声子空间则由协方差矩阵中所有最小特征值（噪声方差）对应的特征向量组成 (MUSIC algorithm is a feature space based on matrix decomposition method. From the geometric point of view, the observed signal space can be decomposed into signal subspace and noise subspace, it is clear that two spaces are orthogonal. Signal subspace to the data received by the array covariance matrix and the eigenvector corresponding to the signal component, the noise subspace from the covariance matrix of all the smallest eigenvalue (noise variance) eigenvector corresponding to the composition )