Fractal Dimension
Calculating fractal dimension in SAXS data using computational methods
Classical Boundary Element Methods
Implementation of classical boundary element algorithms using MATLAB
Multi-Object Tracking (3D) - Algorithm Implementation
Multi-Object Tracking (3D) Algorithm Developed in MATLAB with Code Implementation Details
Objective of Broadband Focusing Through a Focus Transformation Matrix
The purpose of broadband focusing is to transform data across different frequency bands into data at a common center frequency using a focus transformation matrix, thereby constructing a correlation matrix. The key element lies in the selection of th
PCA Algorithm Programming Design Steps
PCA Algorithm Programming Design Steps: 1. Mean Centering 2. Compute Covariance Matrix and its Eigenvalues/Eigenvectors 3. Count Eigenvalues Exceeding Threshold 4. Sort Eigenvalues in Descending Order 5. Remove Small Eigenvalues 6. Remove Large Eigen
MATLAB Simulation of Logistic Chaotic Mapping
MATLAB simulation of Logistic chaotic mapping including bifurcation diagrams, phase plots, and Lyapunov exponent spectrum generation
MATLAB Implementation of Speed Sensorless Control for Three-Phase Induction Motors
MATLAB-based implementation of speed sensorless three-phase induction motors using MarsMATLAB version 7.4 speed identification algorithm, featuring code structure analysis and signal processing techniques
Three Methods for Computing Matrix Eigenvalues with MATLAB Implementations
MATLAB implementations of three eigenvalue computation algorithms: Power Method, QR Algorithm, and Jacobi Method, including code-specific explanations and application scenarios
OTSU Algorithm for Optimal Threshold Calculation: A Simplified Implementation
MATLAB implementation of the basic OTSU algorithm for determining optimal image threshold values. This algorithm automates the process of finding the best threshold for image binarization by maximizing inter-class variance.
Finite Element Plane Problem Solving Framework
Comprehensive program suite for finite element plane problem analysis, featuring implementations of mass matrix calculation, stiffness matrix assembly, main solver algorithms, and visualization tools.
Cubature Kalman Filter Implementation Example
A practical cubature Kalman filter example demonstrating sensor noise reduction techniques and MATLAB implementation with parameter optimization
Extended Kalman Filter Implementation for Robot Localization, Mapping, and SLAM
Extended Kalman Filter MATLAB simulation for robotic applications including localization, mapping, and SLAM with enhanced algorithm implementation details
Simple Least Squares Approximation Algorithm
A simple least squares approximation algorithm for system identification, featuring modifiable noise parameters and system parameters, providing source code for system identification and simulation assignments.
Common Methods for Chaotic Time Series Analysis and Prediction
This toolbox encompasses common approaches for chaotic time series analysis and prediction, featuring implementations for generating chaotic time series through various attractor models: - Logistic Map (ChaosAttractorsMain_Logistic.m) - Simulates pop
Simulation of Target Tracking: Generating Measurements, Noise, Clutter, and Various Target Motion Models
MATLAB code implementation for target tracking simulation, including measurement generation, noise and clutter modeling, as well as various target motion dynamics with detailed algorithmic explanations
MATLAB Implementation of EM Algorithm for Gaussian Mixture Model Parameter Estimation
MATLAB-based implementation of the Expectation-Maximization algorithm for estimating means, variances, and weights in Gaussian Mixture Models, featuring iterative optimization and parameter estimation capabilities.
Integration of CKF and UKF for Enhanced State Estimation
Combining CKF and UKF effectively addresses state mutation challenges in CKF while maintaining numerical stability through innovative fusion algorithms
Application of EKF Filtering in Navigation Systems
Implementation of EKF filtering for navigation applications with relatively high accuracy, including algorithm explanations and parameter optimization techniques
Applying K-means Algorithm for Image Segmentation
Implementation of K-means clustering for image segmentation using grayscale conversion from color input images, with post-processing median filtering to reduce noise caused by illumination variations and improve segmentation accuracy
Enhanced K-Means Algorithm for Image Processing
Implementation of an improved K-means algorithm for image processing applications with enhanced segmentation capabilities