Robust Sparse PCA Algorithm
Robust Sparse PCA algorithm demonstrating strong resistance to noise and outlier data with enhanced implementation features
3D Structure Recovery
Recovering 3D structure from motion in noisy 2D images is a fundamental problem addressed by computer vision researchers. By consistently tracking feature points across multiple images using the Lucas-Kanade optical flow algorithm, the Tomasi-Kanade factorization method enables 3D shape reconstruction through matrix decomposition of the feature point trajectories.
MATLAB Implementation of LMS and RLS Adaptive Filter Algorithms
This program implements both LMS (Least Mean Squares) and RLS (Recursive Least Squares) adaptive filter algorithms using MATLAB. Unlike some verbose implementations, this code is concise and clear. It defines an input signal with added noise and applies adaptive filtering using a for loop structure for iterative algorithm execution.
Active Noise Control Using a Filtered-X LMS FIR Adaptive Filter
This demonstration showcases the implementation of adaptive filtering techniques for acoustic noise attenuation through active noise control, featuring real-time algorithm adaptation and anti-noise signal generation.
MATLAB Implementation for Stochastic Resonance Similarity Computation
A MATLAB program for calculating stochastic resonance similarity, demonstrating how input-output similarity S improves with increasing noise standard deviation until reaching a saturation threshold. The implementation includes noise injection mechanisms and similarity quantification algorithms.
MATLAB Denoising Program for Gaussian Noise Removal
MATLAB denoising program designed to handle noise following normal distribution, with implementation details and algorithm explanations