Fundamental Materials for Learning Kalman Filtering
This resource serves as foundational material for learning Kalman filtering, containing program implementations and documentation suitable for beginners in signal processing and state estimation.
Compressive Sensing Algorithms: Comparative Implementation and Analysis
Application Context Compressive sensing represents a highly valuable source code implementation with significant practical applications in signal processing, image reconstruction, and communication systems. This program provides comparative analysis of multiple algorithms, making it particularly valuable for researchers beginning their exploration of compressive sensing. The implementation demonstrates practical utility while maintaining research-oriented flexibility for algorithm modification and performance evaluation. Key Technologies The codebase implements and compares various compressive sensing algorithms including greedy approaches (OMP, CoSaMP), convex optimization methods (l1-minimization), and iterative thresholding techniques. Each algorithm is implemented with clear parameter configurations and performance metrics to facilitate understanding of trade-offs between reconstruction accuracy and computational complexity.
Ant Colony Optimization Algorithm for Solving TSP Problem - MATLAB Implementation
A comprehensive MATLAB implementation of the basic Ant Colony Optimization algorithm for solving the Traveling Salesman Problem (TSP). This well-commented program features visual result plotting and includes detailed explanations of algorithm principles and execution methods, making it ideal for educational purposes and practical applications.
Unscented Kalman Filter Algorithm Implementation
A fundamental Unscented Kalman Filter program suitable for beginners, featuring practical examples and code implementation details for enhanced learning
Cubature Kalman Filter Implementation Example
A practical cubature Kalman filter example demonstrating sensor noise reduction techniques and MATLAB implementation with parameter optimization
Collected Decision Tree Source Code from Online Resources
Three decision tree algorithm implementations (C4.5, ID3, CART_iris) collected from online sources for collaborative learning and research purposes.
MATLAB GPS Software Receiver: Complete Implementation with Clean Code Structure
This comprehensive GPS receiver implementation features well-structured MATLAB code with excellent readability, detailed comments, and robust functionality. Originally developed by a US university, this implementation has been tested, debugged, and optimized for educational purposes, offering valuable insights into GPS signal processing algorithms and software-defined radio concepts.
Chaotic Optimization Algorithm with Comprehensive Code Comments
A self-implemented chaotic optimization algorithm featuring detailed inline comments and clean code structure, designed for educational purposes and foundational algorithmic understanding
MATLAB Code Implementation for Digital Image Processing
Digital Image Processing, Pattern Recognition, and Face Recognition with included programs and face database - an excellent learning resource with practical implementations
MATLAB Implementation of Cuckoo Search Algorithm with Levy Flight
Comprehensive MATLAB code implementation of the Cuckoo Search algorithm featuring Levy flight behavior, designed for educational purposes and practical optimization applications.