Professional MATLAB source code with comprehensive documentation and examples
This post discusses moving window polynomial least squares fitting smoothing, roughness penalty methods, and kernel smoothing techniques, including algorithmic implementations and code considerations.
Original particle filter source code with comprehensive documentation, ideal for beginners and academic projects such as graduation theses. Verified functional implementation.
Compressed sensing, also known as compressive sampling or sparse sampling, represents a revolutionary sampling theory that leverages signal sparsity characteristics. It acquires discrete signal samples through random sampling at rates significantly l
Introduction to the CoSaMP algorithm and its practical applications in compressed sensing theory with code implementation insights
Implementation of an adaptive stochastic resonance algorithm with detailed explanations in code comments. Ready for direct deployment.
Comprehensive MATLAB algorithms for 3D point cloud surface rendering and texture mapping, featuring clear implementation and practical applications with detailed code explanations
Introductory examples for compressed sensing, sparse sampling, and sparse representation with practical code demonstrations
Target Tracking and Localization - Including Position, Velocity, and Acceleration Tracking Curves
Implementation of the Shape Context Algorithm as presented in the original authors' research paper, including code-based execution details and algorithmic explanations
Small Sample Development Forecasting Methodology
Comparison of different particle filter resampling methods including SIR resampling, auxiliary resampling, and regular resampling, with algorithm implementation insights.
An improved LMS algorithm and its application in noise cancellation. Building upon traditional fixed-step and variable-step LMS algorithms, this enhanced variable-step method utilizes exponential cubic instantaneous error magnitude with a forgetting
Original MATLAB source code for Kalman filtering implementation, thoroughly tested with excellent performance results. Available for download with detailed algorithm explanations.
Implementation of pedestrian detection using HOG algorithm, with required data provided in *.dat files. Although positive and negative training samples are not included, users can train their own models and integrate them into the project to detect p
Simulation of dual-platform passive localization focusing on bearing-only scenarios! Implemented primarily using Kalman filter algorithms with detailed code structure explanations!
An adaptive interacting multiple model algorithm utilizing Kalman filtering for dynamic system modeling
Fingerprint Image Preprocessing with Algorithm Implementation
Sparsity-Adaptive Algorithms in Compressed Sensing for Iterative Estimation Under Unknown Sparsity Conditions
MATLAB implementation of phase unwrapping featuring two distinct algorithms: quality-guided path-following phase unwrapping and Goldstein's branch-cut method, with detailed code explanations and practical applications.
This program implements particle swarm optimization to tune least squares support vector machine parameters, featuring excellent performance with intelligent parameter selection algorithms and efficient computation workflows.