Professional MATLAB source code with comprehensive documentation and examples
Utilizing MATLAB mathematical software for numerical computation of six significant chaotic models including the Lorenz system, while simulating unique properties of various chaotic systems such as chaotic attractors, period-doubling bifurcations, se
Implementation and analysis of data mining algorithms including density-based DBSCAN clustering and centroid-based K-Means clustering
MATLAB implementation of hybrid prediction model combining Particle Swarm Optimization and Grey System Theory with high accuracy performance
This implements initial alignment for strapdown inertial navigation using Kalman filtering, referenced from a Harbin Engineering University master's thesis with good performance, though the observation vector construction methodology remains unclear.
An improved version of SFLA (Shuffled Frog Leaping Algorithm) implemented in MATLAB, featuring simplified code structure and practical applications. This implementation includes optimized local search mechanisms and global information exchange betwee
This code provides a foundational implementation of the Extended Kalman Filter algorithm with comprehensive commenting. By studying this code alongside the fundamental principles of Kalman filtering, developers can gain a thorough understanding of th
Practical MATLAB implementations of Fuzzy C-Means (FCM) and Fuzzy K-Means clustering algorithms with detailed documentation and optimization features for enhanced data analysis accuracy.
This method provides an efficient approach to calculate Lyapunov exponents for chaotic systems by modifying their dynamic equations, with implementation demonstrated through numerical algorithms and Jacobian matrix computations.
A computer vision technique for identifying human faces and drawing bounding boxes around facial regions using advanced algorithms
This foundational GPS acquisition code demonstrates clear structure and logical flow, featuring core signal processing algorithms and data handling methods for easy comprehension and modification.
Sparse Component Analysis is an underdetermined blind source separation algorithm based on an instantaneous mixing model. Previously, automated algorithms like ICA or SOBI were unavailable for this method. Our work introduces significant improvements
This presentation focuses on the KSVD algorithm introduction, detailing how to train dictionaries using KSVD methodology with code implementation insights
Triangular meshing for finite element applications with node numbering and element labeling, particularly suitable for electromagnetic field simulations and numerical solutions
A comprehensive Capon algorithm implementation for Direction of Arrival (DOA) estimation, originally developed for graduation thesis. Features fully functional code with detailed inline comments explaining each operation, clear algorithm-to-code mapp
Equation Root-Finding Methods % inv - Matrix inversion for linear systems % roots - Polynomial root calculation % fzero - Single-variable function root solver % fsolve - Nonlinear system solver % solve - Symbolic equation solution % *newton - Newton-
This improved algorithm for online route planning incorporates strategic enhancements that prioritize expansion toward the target point, optimizing path discovery efficiency through heuristic-guided node expansion and goal-oriented search strategies.
MATLAB implementation of Bayesian inference for optimizing Least Squares Support Vector Machine parameters with enhanced computational efficiency
Application of sparse decomposition algorithms in underdetermined blind source separation scenarios with complete English annotations and code implementation insights
GPS IF signal frequency analysis and CA code acquisition program implementation, with downloadable raw test datasets from Beijing Oriental Union Star website
Implementation of Kalman filter-based second-order resistance identification for permanent magnet synchronous motors with embedded algorithmic approach