ls_discrete

智能天线中多单元线形天线阵的波达方向估计(Smart antennas in multi-element linear antenna array of the Direction of Arrival Estimation)

这个文件包含了正弦调频信号的魏格纳威利分布以及经过平滑和加窗后的伪魏格纳威利分布和平滑伪魏格纳威利分布(This file contains a sinusoidal FM signal of the Wigner distribution and Na Weili after smoothing processing window of the pseudo-Wigner-Na Weili smoothed pseudo-Wigner distribution and the distribution of Na Weili)

Image processing Basic Programms -1 using Matlab(Image processing Basic Programms-1 using Matlab)

A matlab code to extract MFCC features, with several options

说明：  SIMULATION A DC MACHINE WITH USING MATLAB

matlab简单示例练习,matlab2010版本，实用的教程算例。。。(Matlab simple example exercise)

正态分布的shapiro-wilk检验法，适合样本量n满足3=<n<=50的情况。(Shapiro-wilk test, in the normal distribution for sample size n satisfies 3 = <n<=50的情况。)

simulink构建的简单的离散型的积分分离法整定PID参数模拟仿真(Simulink to build a simple discrete integral separation tuning PID parameters simulation)

假设一个交换系统有M部电话，每个用户在很短的时间（单位时间内）呼叫一次的概率为P；用户间呼入的时刻相互独立，当M很大，P很小时，时间t内到达交换机的呼叫次数构成泊松过程N(t)。 1、确定此泊松过程的参数。利用计算机仿真N(t)的生成过程。注意合理选择M和P，时间分辨率为一个单位时间。 2、为了比较生成的N(t)与理论模型的吻合程度。取N(t)的多个样本并选取3个典型时间,,，得到,,三个随机变量的样本，在一张图上画出其直方图及理论分布曲线，并将两者对照。比较M选取不同时的效果。注意：样本个数足够多。 3、画出任意相邻两次呼叫间隔的直方图，和理论值进行对照。验证其与其它相邻两次呼叫间隔随机变量的独立性。 试推导在N（t）=N条件下第n次呼叫时刻的概率密度函数（1≤n≤N）。并比较仿真生成的呼叫时刻与所推导理论模型的吻合程度（可取N=10）(Suppose an exchange system has a M phone, the probability of each user calling once in a very short time (per unit time) is P; the time for the incoming call between the users is independent, when the M is large and the P is very small, the number of calls to the switch within the time t constitutes the Poisson process N (T).)

信号与信息处理――阵列信号处理DOA估计的matlab算法，这是线性调频信号的稀疏分解算法，wigner_will分布-Signal and information processing- array signal processing matlab algorithm for DOA estimation, which is a linear FM signal sparse decomposition algorithm, wigner_will distribution