Explore MATLAB source code curated for "模式识别" with clean implementations, documentation, and examples.
Input: x: input image, ru, rd: row extension amounts (up and down), cl, cr: column extension amounts (left and right), extmod: extension mode. Valid extension modes include: Primarily used for image processing and pattern recognition applications with border handling implementations.
Support Vector Machine method implemented in MATLAB for classification detection and pattern recognition applications
Implementing logical AND and logical OR operations through linear predictive classifiers in pattern recognition with MATLAB code implementation, algorithm explanation, and key function descriptions
Pattern Recognition - Perceptron Criterion-Based Linear Classifier Design with fully custom Python/MATLAB implementation, comprehensive algorithm explanations, and detailed function documentation
Comprehensive Pattern Recognition Algorithms: C-Means and ISODATA Clustering Methods with MATLAB Code Implementation
The perceptron algorithm, implemented in MATLAB, is a fundamental pattern classification method that adjusts weights and thresholds to map input data into distinct categories.
A fingerprint recognition system developed in MATLAB, primarily implementing common fingerprint recognition techniques in pattern recognition. The package includes test samples and detailed usage instructions (refer to read_me for specifics).
A comprehensive experimental system with GUI for SVM pattern recognition, fully implemented in MATLAB with multi-class classification capabilities. This is an auxiliary program developed for my graduation project, featuring clear code structure with modular design including data preprocessing, model training, and visualization components.
1. Pattern Recognition with BP Neural Networks 2. Nonlinear System Identification Using BP Networks 3. A Neural Network PID Controller 4. PCA Algorithm for Image Processing 5. Exhaustive Search Algorithm for Image Processing
This repository contains the original author's implementation code for Two-Dimensional PCA (2DPCA) - a novel approach for appearance-based face representation and recognition published in IEEE PAMI. The paper has received 681 citations on Google Scholar. Note: While this algorithm is a classic in pattern recognition (primarily for facial recognition), the "speech recognition" categorization is inaccurate as 2DPCA is not commonly applied to audio processing. The code provides practical implementation of 2DPCA's matrix-based dimensionality reduction technique.