Professional MATLAB source code with comprehensive documentation and examples
Official MATLAB implementation of Compressive Sensing recovery algorithms with detailed PDF documentation describing the algorithm's principles, complete with code examples for practical understanding and implementation guidance.
A custom particle filter implementation with video testing capability - users can integrate their own video data for evaluation
Implementation of least squares inverse filters for deconvolution problems with observation noise, employing pre-whitening methods to mitigate noise effects, and designing an FIR inverse filter with length N=50 using minimum square error criteria
Implementation of K-Means Clustering Algorithm: Given K number of clusters, the algorithm partitions n objects into K classes, maximizing within-cluster similarity while minimizing between-cluster similarity. The implementation involves iterative cen
Original Implementation: Simulating BCH algorithms using MATLAB, with tested and fully functional code
Simulation of single-station passive positioning algorithms for targets moving in two-dimensional linear trajectories, including code implementation details for motion modeling and signal processing.
A successfully debugged classical optical flow-based motion image object detection system with enhanced algorithm implementation details
Example Program Demonstrating LSSVM Parameter Optimization Using Particle Swarm Intelligence (LSSVM+PSO Implementation)
Recent observations on blind source separation algorithms, focusing on maximum entropy principle-based approaches with code implementation insights
Practical MATLAB programs for interpolation and curve fitting with detailed code implementation explanations
12-Dimensional System State Model Using UKF to Generate Importance Probability Density Function Updating Particle Set's Covariance Matrix with Resampled P Matrix Based on Version 1.0
Enhance comprehension of the Kalman Filter algorithm by exploring its fundamental characteristics, implementation workflows, and practical applications with code-based examples. Learn the essential steps and methodologies for applying Kalman filterin
Implementation and error analysis of a nonlinear Kalman filter tracking system; includes code structure explanations and algorithm breakdowns for beginners in target tracking
RRT Random Tree Algorithm for Robot Path Planning - Easy Implementation with Basic Sampling and Tree Expansion Techniques
Reconstructing surfaces from 3D point clouds using advanced algorithms! This represents an excellent approach for surface reconstruction with robust implementation capabilities.
Simulation of motors, including motor modeling and implementation of various algorithms, primarily utilizing closed-loop control systems
Comprehensive comparison of various nonlinear Kalman filters with code implementation insights, focusing on Unscented Kalman Filter (UKF) and different Extended Kalman Filter (EKF) approaches
Hooke-Jeeves pattern search algorithm for multivariable optimization, implementing direct search method for multi-dimensional problems with dynamic step size adjustment and fast convergence properties.
Real-time motion foreground detection using Gaussian Mixture Model (GMM) with improved performance over traditional single Gaussian - features enhanced segmentation and adaptability to dynamic scenes
Data Fitting % interp1 - 1D Interpolation % spline - Spline Interpolation % polyfit - Polynomial Interpolation and Fitting % curvefit - Curve Fitting % caspe - Spline Interpolation with Various Boundary Conditions % casps - Spline Fitting (Not Availa