LearningtheKalmanFilter

用于实现K-means算法以至于解决这类问题(hello,we can realize the problem)

cuckoo optimization for bench mark problems

说明：  Gerchberg–Saxton（GS）算法是一种迭代算法，用于检索通过传播函数（如傅里叶变换）相关的一对光分布（或任何其他数学上有效的分布）的相位，前提是它们在各自光学平面上的强度已知。(The algorithm is an iterative algorithm for retrieving the phase of a pair of light distributions.)

一个可运行的潮流计算程序，用牛顿拉弗逊法进行求解。(verry good!)

this file give simulation for Single Input Dual Output 16-QAM Simulation with comparison in SER between Selective Combining,Equal Gain Combining and Maximum Ratio Combining methods

MUSIC算法[1] 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算法就是利用这两个互补空间之间的正交特性来估计空间信号的方位。噪声子空间的所有向量被用来构造谱，所有空间方位谱中的峰值位置对应信号的来波方位。MUSIC算法大大提高了测向分辨率，同时适应于任意形状的天线阵列，但是原型MUSIC算法要求来波信号是不相干的。(algorithm MUSIC is a method based on matrix feature space decomposition. From a geometric point of view, the signal processing of the observation space can be decomposed into signal subspace and noise subspace, it is clear that these two spaces are orthogonal. Signal subspace by the array received data covariance matrix and signal corresponding to the feature vector and noise subspace is by the covariance matrix of all minimum feature values (noise variance) corresponding to the feature vectors are composed. MUSIC algorithm is to use the orthogonal characteristics of these two complementary space to estimate the azimuth of spatial signals. All vectors of the noise subspace are used to construct spectral, and the peak position in all spatial azimuth spectra correspond to the direction of arrival of the signal. MUSIC algorithm greatly improves the direction finding resolution, and at the same time it is suitable for the antenna array of any shape, but the prototype MUSIC algorithm requir)

用OpenCV实现的Matlab中形态学细化、提取骨架、收缩算法。测试效果与Matlab相同。(Algorithms of morphological thinning,Skeleton and Shrink,ported from Matlab to OpenCV.)

这个matlab代码是实现基于最小二乘算法的常数模算法。较最小均方误差算法，该算法收敛速度较快。(Matlab code to achieve the constant modulus algorithm based on least squares algorithm. Than the minimum mean square error algorithm, the algorithm converges faster.)

根据输入的电路矩阵表示形式，形成节点导纳矩阵，形成因子表的过程可以看做是规格化运算和消去运算的重复过程，重复的次数和非基准点的节点个数相同。 每个过程中进行的操作都相同，首先，存储规格化因子及消去因子；其次，对本行进行规格化运算，并将其值存储在因子表中；然后，对其后的每行进行消去运算；如此循环n次得到因子表。(Representation of the input of the circuit matrix, forming a node admittance matrix formation process can be seen as a factor table normalization process operations and eliminate duplicate operations, the same number of nodes and the number of repetitions of non-reference point. Each operation carried out during the same, first of all, storage and elimination factor normalization factor secondly, the Bank normalized operations, and its value is stored in the factor table then, each row will be erased after their operation so the cycle n times to get factor table.)

用于存储数据,可存储1组数据.具体的大家可以侃侃2408的数据手册.(Used to store data, can store a set of data. Concrete that we can ably 2408 data sheet.)