LVQ Neural Network Prediction for Face Orientation Recognition
Face Orientation Recognition Using Learning Vector Quantization Neural Networks
Support Vector Machine Application Developed Using MATLAB
A MATLAB-based support vector machine application designed for predictive modeling and forecasting tasks.
Application Background of Target Tracking: Radar Data Processing
The target tracking problem finds its application background in radar data processing, where radar systems detect targets, record position data (called plots), process these measurements to automatically form tracks, and predict target positions at the next time step. This study briefly discusses using Kalman filtering for single-target track prediction and evaluates experimental results through MATLAB simulation. The package includes three source code files and an experimental report containing detailed algorithm analysis and scenario assumptions with code implementation insights.
Neural Network Time Series Prediction and Modeling
The simplest approach to understanding command-line functions in the toolbox is to start with the GUI, generate automated scripts, and then modify them for customized network training.
Practical Example of Wavelet Decomposition and Reconstruction
An illustrative example of wavelet decomposition and reconstruction suitable for time series analysis and prediction, including implementation approaches!
Application Background of Target Tracking Problem in Radar Data Processing
The application background of target tracking lies in radar data processing, where radar systems detect targets, record positional data (called plots), and automatically form tracks while predicting targets' future positions. This article briefly discusses using Kalman filtering for single-target trajectory prediction and evaluates experimental results through MATLAB simulation. The implementation includes state-space modeling, prediction-correction cycles, and performance metrics calculation using MATLAB's built-in functions like "kalman" or custom implementations with matrix operations for state estimation.
Wavelet Decomposition Combined with Autoregressive Linear Model for Predictive Analysis
MATLAB source code implementation combining wavelet decomposition and autoregressive linear models for time series forecasting, featuring signal processing and statistical modeling integration
LS-SVM for Time Series Prediction with Implementation Guide
Implementation of LS-SVM (Least Squares Support Vector Machine) for time series forecasting with fully debugged code. The package includes sample datasets and modular code structure covering data loading, normalization, model initialization, cross-validation, training, regression prediction, and denormalization processes. Each module contains detailed comments and supports custom dataset integration.
Optimizing Artificial Neural Networks Using Genetic Algorithms
This program utilizes genetic algorithms to optimize artificial neural networks for predicting SARS trend variations, implementing evolutionary computation techniques to enhance neural network performance.
Kalman Filter Implementation Program
MATLAB routine for Kalman filtering with position and velocity prediction - modified code with clear implementation, easy to understand and suitable for beginners' reference