single_exponential_smoothing

DQPSK SIMULINK调制解调仿真 绝对能运行(DQPSK SIMULINK simulation is absolutely able to run modem)

说明：  数值分析线性方程组LU分解，matlab平台实现(Numerical LU decomposition of linear equations, matlab platform)

测量6205深沟球轴承的故障振动加速度信号, 对信号进行时频分析, 利用经验模态分解方法将振动信号分解成不同特征时间尺度的固有模态函数,对每个固有模态函数进行Hilbert 变换得到Hilbert 谱,通过谱分析识别轴承的故障部位和类型, 证实Hilbert 谱的有效性(Measuring 6205 deep groove ball bearing fault vibration acceleration signal, the signal frequency analysis, empirical mode decomposition method to decompose the vibration signal into different characteristic time scales of intrinsic mode functions, the Hilbert transform of each intrinsic mode functions Hilbert spectrum, spectral analysis to identify the location and type of bearing failure, confirmed the effectiveness of the Hilbert spectrum)

基于matlab的qpsk仿真 仿真源代码(Qpsk simulation based on the matlab simulation source code)

说明：  自己练习编写的波动方程，不知道行不行，求指正，求批评(wave equation)

position of vehicle maneuvering in lane changing with fuzzy

简单的局部二值模式人脸识别程序，采用MATLAB仿真。(A Simple Local Binary Pattern Face Recognition Program Using MATLAB Simulation.)

说明：  遗传算法（Genetic Algorithm，GA）最早是由美国的 John holland于20世纪70年代提出,该算法是根据大自然中生物体进化规律而设计提出的。是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法。该算法通过数学的方式,利用计算机仿真运算,将问题的求解过程转换成类似生物进化中的染色体基因的交叉、变异等过程。在求解较为复杂的组合优化问题时,相对一些常规的优化算法,通常能够较快地获得较好的优化结果。遗传算法已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。(Genetic algorithm (GA) was first proposed by John Holland of the United States in the 1970s. It is designed and proposed according to the evolution law of organisms in nature. It is a computational model of biological evolution process simulating natural selection and genetic mechanism of Darwin's biological evolution theory. It is a method to search the optimal solution by simulating natural evolution process. The algorithm transforms the solving process of the problem into a process similar to the crossover and mutation of chromosome genes in biological evolution by means of mathematical method and computer simulation. When solving complex combinatorial optimization problems, compared with some conventional optimization algorithms, it usually can get better optimization results quickly. Genetic algorithm has been widely used in combinatorial optimization, machine learning, signal processing, adaptive control and artificial life.)

利用主分量分析(PCA)进行模式识别，包括主分量分析运算的主要函数，以及相关应用的例子。(Using principal component analysis (PCA) for pattern recognition, including the principal component analysis of the main function of computing, and related application examples.)

该程序设计简单，计算结果准确。能很好的利用该程序给出二维光子晶体的禁带结构(the design process simple and accurate. Can be a very good use of the program is two-dimensional photonic crystal structure of the forbidden zone)