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01
- 的傅立叶变换,工程技术中,常将看成一时间信号,相应的空间,称为时间域和空域;将其傅立叶变换看成频率函数,相应的空间称为频域。称为其相角,这在物理上是有良好背景的。
实数据快速傅立叶变换算法
- 傅立叶变换是信号处理时最常用的算法之一,实现时域与频域之间的转换,对人们研究各种信号非常有用,本程序利用VC实现快速傅立叶变换算法-Fourier transform signal processing is the most commonly used algorithm, achieving time-domain and frequency domain between the conversion of the people look very useful signal, the pr
fft
- 时域信号转换为频域信号的几个例子,本人都用过的,绝对能运行-Time-domain signal is converted to frequency domain signal a few examples, I have been used, absolutely can run
fft_analysis
- 傅里叶变换是信号处理的重要手段之一,在频域内对信号进行处理具有诸多优点-Fourier transform is an important means of signal processing in the frequency domain signal processing has many advantages
FFTandInverseFFT
- Labview 中FFT 和Inverse FFT功能的应用实例,展示了由时域到频域的变换及由频域到时域的信号重建-Labview, and Inverse FFT in the FFT function of application examples to demonstrate by the time domain to frequency domain transformation, and by the frequency domain to time domain signal rec
Signals_and_systems_frequency_domain_analysis_cont
- 信号与系统连续系统的频域分析Signals and systems in frequency domain analysis of continuous systems-Signals and Systems Analysis in frequency domain continuous system Signals and systems in frequency domain analysis of continuous systems
Signals_and_Systems_Continuous_System_Complex_Freq
- 信号与系统连续系统的复频域分析Signals and Systems Continuous System Complex Frequency Domain Analysis-Continuous Signals and Systems Analysis of Complex Frequency Domain Signals and Systems Continuous System Complex Frequency Domain Analysis
cheng-xu
- (1)认真复习第七章中用窗函数法和等波纹最佳逼近法设计FIR数字滤波器的原理; (2)调用信号产生函数xtg产生具有加性噪声的信号xt,并自动显示xt及其频谱,如图10.5.1所示; 图10.5.1 具有加性噪声的信号x(t)及其频谱如图 (3)请设计低通滤波器,从高频噪声中提取xt中的单频调幅信号,要求信号幅频失真小于0.1dB,将噪声频谱衰减60dB。先观察xt的频谱,确定滤波器指标参数。 (4)根据滤波器指标选择合适的窗函数,计算窗函数的长度N,调用MATLAB函
Ex4_3
- 傅里叶变换是一种将信号从时域变换到频域的变换形式,是信号处理的重要分析工具。离散傅里叶变换(DFT)是傅里叶变换在离散系统中的表示形式。但是DFT的计算量非常大, FFT就是DFT的一种快速算法, FFT将DFT的N2 步运算减少至 ( N/2 )log2N步。-Fourier transform is a signal from the time domain to frequency domain transformation form, is an important signal pr
wavelet
- 小波分析是一个强有力的统计工具,最早使用在信号处理与分析领域中,通过对声音、图像、地震等信号进行降噪、重建、提取,从而确定不同信号的震动周期出现在哪个时间或频域上。现在广泛的应用于很多领域。 在地学中,各种气象因子、水文过程、以及生态系统与大气之间的物质交换过程都可以看作是随时间有周期性变化的信号,因此小波分析方法同样适用于地学领域,从而对各种地学过程复杂的时间格局进行分析。如,温度的日变化周期、年变化周期出现在哪些事件段上,在近100年中,厄尔尼诺-拉尼娜现象的变化周期及其出现的时间段,等
wzFunFFT90
- 频谱分析通用程序,输入为时域信号,返回频域信号(幅值与相位)-Spectrum analysis of the general program, the input time-domain signal, to return to the frequency domain signal (magnitude and phase)
analysis-of-the-gear
- 计算齿轮故障,对齿轮进行时域分析(计算时域信号的各统计特征值)和频域分析(进行傅里叶变换,计算功率谱)-analysis of the gear
wavelet-transform-by-CPP
- 小波变换与Fourier变换相比,是一个时间和频域的局域变换因而能有效地从信号中提取信息,通过伸缩和平移等运算功能对函数或信号进行多尺度细化分析(Multiscale Analysis)。一般都是用MATLAB编写。本压缩包集成了大量C++写的小波变换的源程序,具有更高的移植性和可增改性。-wavelet transform by C++ program. there s many examples how the wavelet transform works.
DFSM
- 用于计算谱相关函数的频域平滑算法,可改参数,改输入信号类型-calculate spectral correlation function by using frequency smoothing Algorithm, you can change the parameters, and the type of input signal
wave_idl
- 用于同时观察信号在时域和频域中的变化以及信号中的不同频率成分随时间的变化-For the simultaneous observation of different frequency components in the time domain and the signal spectrum of the signal changes over time
Fast-Fourier-Transform
- 有了傅立叶变换,我们可以从信号的频域特征去分析信号。尤其在无线通信系统 中,傅里叶变换的重要性就更加明显了,无论是设计者还是测试工程师,在工作中都会和傅立叶变换打交道。-With the Fourier transform, we can go to analyze signals the frequency domain characteristics of the signal. Especially in a wireless communication system, the impo
random
- 压缩感知,观测矩阵采用随机观测矩阵,解码采用OMP算法,信号采用频域稀疏度为7的信号,可以直接运行。-Compressed sensing, observation matrix using random observation matrix decoding using OMP algorithm signal using frequency-domain signal sparsity 7, it can be run directly.
spectrum_Coh
- 两个信号的相干函数和互功率谱(频域)。从网上下载的,还可以-The coherence function and the mutual power spectrum (frequency domain) of the two signals. Download the Internet, but also
pinyu
- 振动信号的频域处理方法,包括谱分析、窗函数等-Vibration signal in the frequency domain processing methods, including spectrum analysis, the window function and so on
nuiqou
- 实现串口的数据采集,详细画出了时域和频域的相关图,连续相位调制信号(CPM)产生。- Achieve serial data acquisition, Correlation diagram shown in detail the time domain and frequency domain, Continuous phase modulation signal (CPM) to produce.