SOM Neural Network Classification Tutorial 1D Matrix Classification for 2-Class and 3-Class Problems in MATLAB

This tutorial demonstrates how to perform 1D matrix classification for 2-class and 3-class problems using a Self-Organizing Map (SOM) neural network. It includes a matrix-based AND gate example with input samples of sizes 12 and 3. The approach uses machine learning principles to classify the data, making it suitable for tasks such as pattern recognition and clustering. The MATLAB code provided helps implement and visualize the classification process in a straightforward manner. The classification results can be interpreted using the SOM algorithm, which adjusts the map neurons based on the input data features.