Monte-Carlo-and-Matlab

在Matlab/Simulink构造一缓慢时变线性系统。试根据系统的输入生产数据分别用带遗忘因子最小二乘法和广义最小二乘法辨识系统的参数。(in Matlab/Simulink constructed a slow time-varying linear systems. Examination under the input production data were used to bring the forgotten factor method of least squares and generalized least squares method recognition system parameters.)

包括内插，还有成形滤波器等等调制时所用的matlab文件

BOOST电路的仿真，最基本的BOOST电路的仿真，最基本的(BOOST circuit simulation, circuit simulation BOOST most basic and fundamental)

牛顿迭代法，用于对通用多项式的计算，可自己设置处置，精度等(Newton iterative method for the calculation of general polynomials can set up their own disposal, precision)

说明：  KL变换和DCT变换比较分析 在matlab环境下的比较仿真(KL&DCT )

说明：  Matlab/Simulink通信系统建模与仿真实例分析学习辅导和习题详解(Matlab / Simulink communication system modeling and simulation example analysis learning guidance and exercises explanation)

fitting an elips using matalb

在一种变步长LMS 算法的基础上，引进动量因式，提出了一种新的改进LMS 的算法。新算法整体性能优 于变步长LMS 算法以及LMS 算法。通过理论分析，比较了新的算法和变步长LMS 算法以及LMS 算法的收敛性 和稳态性，提出了一种设想以提高新算法的稳态性。仿真试验证明了新算法的优越性以及设想的在仿真条件下的正 确性。(In a variable step size LMS algorithm, based on the introduction of momentum factor, a new improvement of LMS algorithms. The overall performance of the new algorithm is superior to variable step size LMS algorithm and LMS algorithm. Through theoretical analysis, comparing the new algorithm and variable step size LMS algorithm and LMS algorithm convergence and steady-state, and proposes a new algorithm is envisaged to enhance the steady-state nature. Simulation tests proved the superiority of the new algorithm, as well as envisaged under the conditions in the simulation is correct.)

说明：  两类二维相关正态分布条件下的最小错误率贝叶斯分类器，基于最小风险的贝叶斯分类器，Parzen窗法非参数估计分类器程序，Fisher线性判别法分类器程序。(Under normal conditions two types of two-dimensional correlation of minimum error rate of Bayesian classifier, the minimum risk-based Bayesian classifier, Parzen window method estimates non-parametric classification procedures, Fisher Linear Discriminant classifier program.)

今天上传《数学实验与Matlab》程序，希望对大家有用！(today uploaded "Matlab mathematical and experimental" procedures in the hope that it may be useful right! Thank you!)