Explore MATLAB source code curated for "测试样本" with clean implementations, documentation, and examples.
Implementing neural network classification functionality in MATLAB by inputting training and test samples for model training and subsequent classification. This simple neural network algorithm is ideal for beginners, featuring clear implementation steps and basic pattern recognition capabilities.
A simple simulation of Parzen window classification in pattern recognition, where female.txt and male.txt serve as training samples and test.txt contains test samples. This implementation demonstrates excellent classification performance and provides valuable insights for beginners learning pattern recognition, including practical code structure and algorithm implementation details.
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).
MATLAB SVM toolbox implementation with excellent usability. Place data in the MATLAB folder, open MATLAB, and execute the sequence: 1. mex setup 2. y 3. 2 4. y to obtain classification accuracy and test result matrix using training and testing samples. The implementation involves compiling C/C++ extensions through mex configuration for optimized SVM computation.
Implementation of BP neural network for handwritten digit recognition (0-9 digits) with code-oriented architecture and optimization strategies