image-stitch

高分辨率雷达 距离向压缩算法滤波器设计 三种方法 全面设计(clc clear all close all 2013年9月28日 ---------------参数---------- Tr=42e-6 fs=9.5e6 K=0.7e11 Nfft=2048 -------------匹配滤波 时域生成-------------- t=(-Tr/2+1/fs:1/fs:Tr/2-1/fs) w = kaiser(length(t),2.5) w=w w = ones(1,length(t)) ht1=w.*exp(-1i*pi*K*t.^2) ht2=w.*exp(1i*pi*K*t.^2) hf1=fft(ht1,Nfft) hf2=fft(ht2,Nfft) figure subplot(211) plot(abs(hf1)) title( 匹配滤波器1 幅频响应 ) subplot(212) plot(phase(hf1)) title( 匹配滤波器1 相位 ) figure subplot(211) plot(abs(hf2)) title( 匹配滤波器2 幅频响应 ) )

2PSK的调制解调过程的仿真及在不同信道下误码率仿真分析(2PSK modem emulation and simulation of BER)

AWGN信道的设计与仿真加性高斯白噪声在通信领域中指的是一种各频谱分量服从均匀分布（即白噪声），且幅度服从高斯分布的噪声信号。因其可加性、幅度服从高斯分布且为白噪声的一种而得名。(Design and Simulation of additive white Gaussian noise AWGN channel in the middle of the field of communication is a uniform distribution of each spectral component (ie, white noise), and the amplitude of the noise signal to obey a Gaussian distribution. Because it can increase resistance, the magnitude of Gaussian distribution and is named after a white noise.)

详细描述了对模糊控制工具箱的介绍以及如何用matlab的模糊控制工具箱(A detailed description of the introduction of fuzzy control toolbox and how to use fuzzy control toolbox matlab)

自适应模糊滑模控制器设计的matlab源代码，对于研究滑模变结构控制的同学很有用。(Adaptive fuzzy sliding mode controller design matlab source code for the study of sliding mode variable structure control students useful.)

MATLAB统计分析与应用：40个案例分析( data input and export )

这是图论里面的一个定理，即Havel定理，它是用来判断一系列的度的序列能否组成一个简单图，在这儿我实现了它。(This is the inside of a theorem of graph theory, that Havel theorem, which is used to determine whether a series of sequences degrees to form a simple graph, here I realized it.)

目标因子分析，用于找寻主因子数的个数，清晰明了的看出其步骤(Target factor analysis, to find the main number for the number of factors, see the steps clarity)

ECT中用于加噪声条件下的重建程序以及计算灵敏度的matlab程序文件(It is used to add noise conditions in the reconstruction program for ECT)

ACF(x) plots the sample autocorrelation function of the univariate time series in vector x. By default, the sample autocorrelation function is plotted up to lag 25. ACF(x,k) plots the sample autocorrelation function up to lag k. ACF(X,k, name ) sets the title of the plot to name .