Basic Bayesian Transform for Compressed Sensing
A fundamental Bayesian transform approach for compressed sensing, including source code implementation with one-dimensional signal processing example and two-dimensional image processing demonstrations
Explore MATLAB source code curated for "源代码" with clean implementations, documentation, and examples.
A fundamental Bayesian transform approach for compressed sensing, including source code implementation with one-dimensional signal processing example and two-dimensional image processing demonstrations
This MATLAB source code implements a genetic algorithm incorporating elitism strategy. The implementation details the complete genetic algorithm workflow and significantly improves performance over basic genetic algorithms by preserving elite individuals across generations. The code includes key functions for selection, crossover, mutation, and elite preservation mechanisms.
MATLAB implementation of Convolutional Neural Network (CNN) with detailed source code, including layer configurations and training algorithms
Simulation of the Energy Detection Method in Cognitive Radio with Source Code and Implementation Guide
Source code for multiscale chirplet basis sparse signal decomposition algorithm, highly effective for multicomponent non-stationary signal analysis with implementation featuring adaptive basis selection and sparse optimization techniques.
MATLAB source code implementation of ant colony optimization algorithm for solving max-min problems, featuring valuable reference material with code structure analysis and parameter configuration insights.
This repository contains implementation source code for Principal Component Analysis (PCA) and Kernel PCA (KPCA), developed for intelligent technology courses with detailed algorithmic explanations and MATLAB/Python implementation considerations.
MATLAB-based 16QAM modulation source code with detailed bit error rate analysis for signal transmission evaluation
Basic source code for the firefly algorithm with comprehensive explanations, optimized for newcomer comprehension and practical application scenarios.
Source code implementation combining Kalman filter and Camshift algorithms for robust object tracking, featuring probabilistic prediction and adaptive color-based tracking mechanisms.