Professional MATLAB source code with comprehensive documentation and examples
MATLAB-based simulation program for image mixing and separation implementing Independent Component Analysis (ICA) algorithm with detailed code implementation and signal processing features.
This MATLAB program solves the 0/1 knapsack problem using genetic algorithm optimization. The algorithm selects items from n available objects to pack into a knapsack with capacity c, where each item i has weight w_i and value p_i. The solution ensur
Genetic Algorithm (GA), a type of evolutionary algorithm, simulates the natural selection principle of "survival of the fittest" in biological evolution. Originally proposed by Professor J. Holland at the University of Michigan in 1967, the algorithm
MATLAB implementation of BP neural network for function approximation and pattern classification tasks
An SVM training software featuring clean, readable code with strong interpretability, ideal for educational and research purposes.
Implementation of kernel function-based C-means clustering image segmentation using MATLAB, featuring robust experimental performance and practical usability
MATLAB simulation implementation of adaptive control using RBF neural networks, featuring online learning algorithms and system parameter adaptation
Debugged and operational constrained PSO algorithm featuring constraint-handling mechanisms, parameter configuration guidance, and performance analysis
Support Vector Machine implementation for classification tasks, including dedicated training and test datasets. The package contains six source programs demonstrating practical SVM application with data partitioning strategies.
MATLAB implementation of Particle Swarm Optimization algorithm for solving optimization problems with nonlinear constraints
MATLAB implementation of AdaBoost ensemble learning algorithm with detailed code explanation and classification applications
Time series forecasting holds significant importance in economics and engineering fields. This study leverages the characteristics of dynamic neural networks to propose a time series prediction methodology, implementing a designed dynamic network to
MATLAB-based genetic algorithm implementation using binary encoding with comprehensive documentation and code description.
MATLAB Image Processing with Simulated Annealing Algorithm for Direct Image Matching and Optimization Techniques
Radar signal sorting using clustering algorithms for unknown signal classification, merging multiple hypothesis classes via similarity coefficients, and performing pattern fusion for multi-mode radars through temporal correlation analysis with MATLAB
Particle Swarm Optimization-based microgrid scheduling approach that optimizes power generation unit outputs under dual constraints of minimal operational costs and environmental friendliness
MATLAB Genetic Algorithm Toolbox: A comprehensive toolkit with built-in operators, optimization functions, and real-world implementation examples for solving complex optimization problems.
This comprehensive pattern recognition assignment covers Parzen window principles, algorithm implementation, and source code. Includes detailed result analysis, performance evaluation, and feasibility studies with practical code examples and mathemat
Implementation of key genetic algorithm functions for job shop scheduling optimization, featuring core evolutionary operations and fitness evaluation mechanisms - a fundamental reference in the field
MATLAB implementation of short-term load forecasting using wavelet neural network approach