Spectral Analysis for Specific Signals
Performing spectral analysis on specific signals using MATLAB, plotting magnitude and phase spectra, including convolution operations and verification procedures
Fractional Fourier Transform with Fast Algorithm Implementation
Fractional Fourier transform program featuring a fast algorithm based on interpolation, decimation operations, and convolution computations.
Image Convolution Operations Using Gabor Filter Banks
Performing Image Convolution with Gabor Filter Banks for Texture and Edge Feature Extraction
Fourier Phase Spectrum of Images
Experimental Content: (1) Compute frequency responses of three given templates and visualize their 3D surface plots; select an image and perform convolution operations using each template, comparing processed images with the original to analyze template types and the differences/connections between templates (b) and (c). (2) Select an image, apply Discrete Fourier Transform (DFT), reconstruct the image using only phase spectrum, then reconstruct using only magnitude spectrum, comparing results; select two distinct image types, perform Fourier transforms, swap their phase spectra, compute inverse Fourier transforms, and compare outcomes to demonstrate the critical role of Fourier phase spectrum in image reconstruction.
MATLAB Code Implementation of Convolution Operation
Convolution Operation: Define signal lengths nx for x(t) and nh for h(t). The total shift length is n=nh+nx-1. Implementation uses for-loops and conditional statements to perform reverse-order summation. Outer loop handles signal shifting through for-statement, while inner summation achieves reverse-order indexing through array element access sequence.