Comparing FFT and STFT Algorithm Differences Using MATLAB Tools
Comprehensive comparison of FFT and STFT algorithms using MATLAB with code implementation details and spectral analysis demonstrations
Stockwell S-Transform
MATLAB Implementation of Stockwell S-Transform Combining FFT and Wavelet Transform Characteristics
MATLAB Implementation of DSP Functions
MATLAB implementations of fundamental DSP functions including FFT, Chirp Z-transform, DCT, Delta Function, and Hilbert Transform with signal processing applications.
Audio and Image Processing with MATLAB
This comprehensive MATLAB-based toolkit provides robust implementations for various audio and image processing tasks. The audio processing module includes Linear Predictive Coding (LPC), Fast Fourier Transform (FFT), formant analysis, and spectral processing with complete source code. The image processing component offers multiple algorithms with detailed reference implementations. The package features an intuitive GUI interface for easy operation and customization.
MATLAB Code Implementation for Fractal Dimension Calculation
Calculation of fractal dimension using FFT algorithm - MATLAB Central File Exchange implementation for fractal surface analysis with spectral methods
Converting Audio from CEP Unit FFT to Mel Spectrum
Transforming audio from CEP unit FFT to Mel spectrum representation using auditory frequency scaling
Computing FFT Results Using Averaged Periodogram Methods
The averaged periodogram method calculates FFT results by segmenting an N-point finite-length sequence x(n), computing periodograms for each segment, and then averaging them. Bartlett's method implements this basic approach, while Welch's method introduces two key improvements: applying window functions before periodogram computation to ensure non-negative spectral estimates, and allowing overlapping segments to reduce variance. Code implementations typically involve data segmentation, window application, FFT computation, and result averaging.
Image Compressed Sensing with Orthogonal Matching Pursuit (OMP) Implementation
Image Compressed Sensing Using Orthogonal Matching Pursuit Algorithm with Sparse Representation Techniques