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FFT-matlab FT在matlab中的实践分析
- FFT在matlab中的实践分析,例子为求一个正弦波的频谱图、均方根谱、功率谱、对数谱和进行IFFT的变换-FFT analysis of the practice in matlab, examples for the sake of a sine wave of frequency spectrum, the rms spectrum, power spectrum, and the IFFT on the number of spectral transformation
MATLABprograminfft.用Matlab产生正弦波,矩形波
- 1.用Matlab产生正弦波,矩形波,以及白噪声信号,并显示各自时域波形图 2.进行FFT变换,显示各自频谱图,其中采样率,频率、数据长度自选 3.做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱 4.用IFFT傅立叶反变换恢复信号,并显示恢复的正弦信号时域波形图 ,1. Using Matlab generated sine wave, rectangular wave, as well as the white noise signal, and display their
squarefft2.rar
- 利用FFT分析方波信号的频谱,讨论采样点数、采样频率对谱分辨率的影响。对数据叠加白噪声后再次分析实验结果。,Square-wave signal using FFT spectrum analysis to discuss the sampling points, the sampling frequency of the impact of spectral resolution. White noise superimposed on the data after analysis of e
pinpu2
- 用Matlab产生正弦波,矩形波,以及白噪声信号,并显示各自时域波形图,FFT实践及频谱分析-Matlab generated by sine wave, square wave, and the white noise signal, and display their time-domain waveform, FFT spectrum analysis of practice and
cs-code
- 一个正弦波利用DCT,FFT变换后稀疏化,然后应用压缩感知实现压缩,并有仿真图例说明重构效果。重构算法采用线性规划和OMP算法等,是一个初学CS入门的好例子。-A sine wave using DCT, FFT transform sparse, and then apply compressed sensing to achieve compression, and a legend reconstruction simulation results. Reconstruction algo
fbh
- 使用FFT分析方波信号的频谱,讨论采样点数、采样频率对谱分辨率的影响。对数据叠加白噪声后再次分析实验结果。-Square-wave signal using the FFT spectrum analysis to discuss the sampling points, the sampling frequency of the impact of spectral resolution. White noise superimposed on the data after analysis
sjb
- 使用FFT分析三角波信号的频谱,讨论采样点数、采样频率对谱分辨率的影响。对数据叠加白噪声后再次分析实验结果。-FFT analysis of the use of the triangular wave signal spectrum to discuss the sampling points, the sampling frequency of the impact of spectral resolution. White noise superimposed on the data af
work
- 一个模拟的心电信号的matlab程序,其中一共包含了一个主程序和6个小程序,小程序分别是q波,s波,u波,p波,t波以及QRS波的模拟,运行的时候直接运行主程序complete.m 文件即可,运行良好,可以出波形-A simulated ECG of the matlab program, which includes a total of six small main program and procedures, the procedures are small q-wave, s-wave
fft
- 用于计算任意波形fft结果的Matlab工具-A matlab tool for wave fft calculating
daixianlvbo
- 把雷克子波离散,对其做fft变换到频率域,然后滤波,再做ifft变换回时间域。-To Leike Zi wave dispersion, its to do fft transform into the frequency domain and then filter, do ifft transform back to time domain.
56
- 文主要目的是针对讯号频谱分析仪(Signal spectrum analyzer)做功能测试,以确定讯号频谱分析仪之各种运算功能正确,其中测试共 分为正弦与余弦波检查、反假象滤波器检查(Antialiasing Filter Check)、频率响应函数与相位角检查(FRF & Phase Check)、自身能量密度函 数检查(Power Spectrum Check)、动态范围检查(Dynamic Range Check)等五个项目的快速傅立叶转换检查(Fast Fourier Tran
physical_meaning_of_FFT
- 该文档详细描述了FFT的物理意义,并附有一个正弦波叠加的例子和相关Matlab程序.-The document describes the physical meaning of FFT in details,with a superimposed sine wave and related Matlab examples
FFtandIfftTest
- Matlab编程实现FFT变换及频谱分析的程序代码(适合初学者加强理解)。(1)用Matlab产生正弦波,矩形波,以及白噪声信号,并显示各自时域波形图;(2)进行FFT变换,显示各自频谱图,其中采样率,频率、数据长度自选;(3)做出上述三种信号的均方根图谱,功率图谱,以及对数均方根图谱;(4)用IFFT傅立叶反变换恢复信号,并显示恢复的正弦信号时域波形图。-Matlab codes for FFT Understanding which contains sine wave,rectangula
DSP
- this file is about finding Fast fourier transform for given sine wave using FFT statement. i. with zero padding II. without zero padding
Data-processing
- 基于FFT的功率谱分析程序设计与应用 2)对实验所采集的转子振动信号进行频谱分析 2.讨论: 1) 信号经过均值化处理或不经过均值化处理的结果比较 2)采用不同窗函数时的谱结果(矩形窗函数, 汉宁窗函数,汉明窗) 3)典型函数的频谱(矩形窗函数, 汉宁窗函数,直线,阶跃函数,δ函数,方波,三角波等) 4)整周期和非整周期采样时两者的比较 5)讨论实验结果 -Based on the FFT power spectrum analysis
TDS
- An example to understand sampling of continous wave and fft
wavelet--fft
- 实现频谱分析。能显示信号与频谱图。主要是对正弦信号和三角波进行一维FFT变换,得到频谱图。-To achieve spectral analysis. Shows the signal with the frequency spectrum. Sinusoidal signal and triangular wave one-dimensional FFT algorithm to obtain the frequency spectrum.
zoomfft-fft
- 产生3个频率相近的正弦波叠加组成周期信号,实现ZOOMFFT和FFT的比较。-Realize ZOOMFFT and FFT with three similar frequency sine wave superposition of periodic signal.
FFT
- 快速傅里叶变换示例,修改波信号文件以及采样频率,就可得到波形与频谱图、相位图(Fast Fourier Transform example, modify the wave signal file and the sampling frequency, you can get the waveform and spectrogram, the phase map)
FFT
- 图像的二维傅里叶变换及变换域滤波,同态滤波(FFT and Wave filtering)