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kalmanfilter
说明: 一种改进的自适应滤波器的状态估计,效果非常之好,是用MATLAB编写的,直接在matlab下运行就可以看到完美的滤波效果,自适应算法是sage—husa算法,较传统的滤波器有很大提高(An improved adaptive filter state estimation, the effect is definitely a good thing, is to use MATLAB prepared directly in matlab run will be able to see the effect of a perfect filter, adaptive algorithm is sage-husa algorithm, a more traditional filter machine has greatly improved)
- 2020-12-10 20:59:20下载
- 积分:1
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QAM_Eb_No_SER
QAM_Eb_No-SER. This Code describer a modulation program
- 2011-05-12 17:20:47下载
- 积分:1
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matlab_optimization
《matlab实例》有关优化算法的实例源码,希望对大家有帮助。(" Matlab example" examples of the algorithm source code, we want to help.)
- 2010-05-19 19:44:08下载
- 积分:1
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dicetest
基于matlab环境利用递归函数计算n的阶乘(use matlab to caculate N!)
- 2013-11-28 23:24:29下载
- 积分:1
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vector
异步电机矢量控制控制的matlab实现,系统采用3个pi调节器,分别为磁链调节器、转矩电流调节器、转速调节器,封装得比较好,适合初学者,版本matlab7.1(Vector control of induction motor control to achieve matlab, system modulator 3 pi, respectively, flux regulator, torque current regulator, speed regulator, a better package than is suitable for beginners, version matlab7.1)
- 2021-03-13 19:39:24下载
- 积分:1
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bizhi
基于FFT的比值算法,是用比值法实现的MATLAB程序。
(Based on the ratio of FFT algorithm, is the ratio method using the MATLAB program realize.)
- 2007-08-28 10:35:37下载
- 积分:1
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mulVNeton
matlab 的拟牛顿方法,减少计算导数带来的计算量的一种迭代方法,用来计算非线性问题。(matlab quasi-Newton methods to reduce the computational calculation of the amount of the derivative of an iterative method to calculate the nonlinear problem.)
- 2013-07-16 21:05:54下载
- 积分:1
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LMI程序
把鲁棒预测控问题转化为线性矩阵不等式来求解(Solving the problem of robust predictive control into a linear matrix inequality)
- 2021-04-12 09:28:57下载
- 积分:1
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vc
说明: 文件中含有大量的vc++语言和MATLAB语言的源代码,并附带有运算结果(File contains a large number of vc++ language and MATLAB language source code, together with an operation result)
- 2010-10-08 16:40:09下载
- 积分:1
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MatchFilterLFM
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 )
)
- 2013-10-12 22:32:06下载
- 积分:1