Particle Filter for Target Tracking with 100 Monte Carlo Simulations
Implementation of particle filter in target tracking with 100 Monte Carlo simulations generating trajectory plots and error curves
Professional MATLAB source code with comprehensive documentation and examples
Implementation of particle filter in target tracking with 100 Monte Carlo simulations generating trajectory plots and error curves
MATLAB implementation of the Detrended Cross-Correlation Analysis (DCCA) algorithm for analyzing covariance between two datasets, calculating DCCA exponents, and performing statistical validation through T-tests
Coordinate Transformation: Determines transformation relationship between two coordinate systems A and B using optimization methods with standard 7-parameter transformation (translation along x,y,z; rotation about x,y,z axes; and scaling factor). Inc
GPS signal tracking implementation using phase-locked loop technology, including code loop tracking and carrier tracking loop with algorithm explanations and key MATLAB functions
The K-means algorithm represents the most fundamental partition-based clustering approach and ranks among the top ten classic data mining algorithms. Its core concept involves clustering data points around k centroids in space, iteratively updating c
Adaptive Least Mean Square (LMS) algorithm implementation using MATLAB platform, including filter design and noise reduction applications
Standard Particle Filter target tracking source code! Suitable for one-dimensional scenarios with nonlinear and non-Gaussian characteristics. Implementation includes Monte Carlo sampling and weight updating mechanisms.
A comprehensive program demonstrating various filtering techniques suitable for passive localization and tracking, including particle filter implementations and alternative filtering approaches with detailed code implementation examples.
Implementation of track analysis in target tracking leveraging the Kalman toolbox for enhanced state estimation and trajectory prediction
A comprehensive target tracking program developed in MATLAB featuring Constant Velocity (CV) model implementation, Kalman tracking algorithm, trajectory simulation capabilities, error analysis, and performance evaluation with simulated tracking resul
This article explores image segmentation using k-means clustering with manually selected cluster centers, demonstrating effective segmentation results through practical implementation examples and algorithm optimization techniques.
A MATLAB-implemented finite element toolbox featuring planar beam elements, bar elements, and solid elements with comprehensive structural analysis capabilities.
Simulation of passive acoustic target localization with five-element cross array, analyzing estimation accuracy for target azimuth angle, elevation angle, distance measurement, and direction finding precision with code implementation details
Implementation of the ITTI algorithm for region of interest selection - a robust method featuring direct execution capability with comprehensive code integration.
Recommendation system source code implementation in MATLAB, based on collaborative filtering algorithm with practical applications in personalized recommendation scenarios
Source code for spectrum estimation algorithms: implementing classic ESPRIT and MUSIC algorithms with detailed function descriptions and parameter explanations
This MATLAB implementation demonstrates telephone user arrears prediction using Markov chain algorithms, featuring comprehensive code commenting for each functional block to facilitate understanding of state transitions and probability calculations.
Multi-Scale Retinex Algorithm in MATLAB format consisting of a single file: MSR.m, implementing multi-scale Gaussian filtering and logarithmic domain image enhancement operations.
This study implements response surface methodology to improve multidisciplinary collaborative optimization algorithms, with numerical case studies demonstrating the enhanced effectiveness of the modified collaborative optimization approach through sy
Simulation algorithm for the Duffing oscillator. By modifying program parameters, different state diagrams can be generated for studying nonlinear system behaviors.