Скачать или смотреть How to Do a Fourier Transform and plot it using Matlab - FFT in Matlab 2024

FFT stands for Fast Fourier Transform. It's a mathematical algorithm used to transform a signal from its original domain (typically time or space) into a frequency domain. This transformation reveals the frequency components that make up the original signal. The FFT is widely used in various fields such as signal processing, engineering, physics, and many more.

In MATLAB, FFT can be simulated using built-in functions like fft() and fftshift(). These functions allow users to compute the FFT of a signal efficiently and effectively. Here’s a brief overview of how it works:

Computing FFT: The fft() function in MATLAB computes the discrete Fourier transform (DFT) of a sequence, which essentially means it calculates the frequency components of the input signal. It takes as input a vector representing the signal in the time domain.

Frequency Spectrum: After computing the FFT, MATLAB provides a vector of complex numbers representing the frequency domain representation of the signal. The magnitude of these complex numbers gives the amplitude of each frequency component, and the angle gives the phase shift.

Plotting: MATLAB's plotting functions (plot(), stem(), etc.) can be used to visualize the frequency spectrum obtained from the FFT. This helps in understanding the frequency distribution and identifying dominant frequencies within the signal.

Applications: FFT in MATLAB is used for various applications such as analyzing audio signals, filtering noise from signals, detecting periodic components in vibrations, and more. Its speed and efficiency make it a powerful tool for real-time and batch processing of data.

Overall, FFT in MATLAB is a fundamental tool for anyone involved in signal processing or related fields. Understanding how to simulate and utilize FFT can greatly enhance the analysis and manipulation of signals in both academic and industrial settings.