Fundamental Theoretical Applications and Core Algorithms of Artificial Immune Systems
Simulation and Implementation of Basic Theories and Core Algorithms in Artificial Immune Systems
Fundamental Motion Estimation Algorithms
The core concept of motion estimation involves partitioning each frame of an image sequence into non-overlapping macroblocks, assuming uniform pixel displacement within each macroblock. For every macroblock, the algorithm searches within a specified range in the reference frame to identify the most similar block (matching block) based on predefined matching criteria. The relative displacement between the matching block and current block defines the motion vector. During video compression, storing only motion vectors and residual data enables complete reconstruction of the current block.
Fundamental Algorithms in Optimization Methods
Implementation of key optimization algorithms: 1) Golden Section Method (0.618 Method), 2) Newton's Method, 3) Modified Newton's Method, 4) Fletcher-Reeves (FR) Method, 5) Davidon-Fletcher-Powell (DFP) Method
Fundamental Algorithm of Weed Optimization
Core implementation of the weed optimization algorithm with outstanding precision reaching 10^-12, featuring population initialization, reproduction mechanisms, and spatial dispersal functions.
Fundamental Rough Set Algorithms
Core rough set algorithms including data completion, attribute reduction, value reduction, and rule generation, with practical implementation insights and code-related applications.
Bayesian Matting: The Most Classic and Fundamental Algorithm in Image Matting
Implementation of Bayesian Matting - the most classic and fundamental matting algorithm in MATLAB, demonstrating excellent performance in both output quality and computational efficiency with robust probabilistic frameworks and optimized matrix operations.
Source Code for Basic Wavelet Transform Denoising Algorithm
Source code implementation of the fundamental wavelet transform denoising algorithm for speech signal processing, providing valuable reference material for beginners with MATLAB code examples and implementation details.
Fundamental Ant Colony Algorithm Implementation with MATLAB Code
This document provides MATLAB code implementation and detailed explanations of the basic ant colony optimization algorithm, including practical applications and Word document integration.
Compressive Sensing
Coverage of fundamental algorithms including OMP, SL0, and associated methodologies