MATLAB Implementation of FFT and IFFT Algorithms

Implementation of FFT (Fast Fourier Transform) and IFFT (Inverse Fast Fourier Transform) algorithms in MATLAB, including files for butterfly operations. FFT is an efficient algorithm for computing the Discrete Fourier Transform (DFT), which converts time-domain signals into frequency-domain representations. IFFT performs the reverse operation by transforming frequency-domain signals back to the time domain. These algorithms are widely used in signal processing, image processing, communications, and other fields. The butterfly operation is a crucial step in FFT algorithms that recursively divides input sequences into smaller subsequences for computation, ultimately producing the frequency-domain representation. The MATLAB implementation typically includes functions and scripts demonstrating key aspects like radix-2 decomposition, twiddle factor calculation, and recursive/iterative approaches. Through this implementation, you can better understand the principles and applications of these algorithms, and apply them for signal processing or frequency-domain analysis in your own projects. Code examples may include functions for handling different input sizes, optimizing computational efficiency, and visualizing input/output signals in both time and frequency domains.