MATLAB Source Code Implementation for Bidirectional Associative Memory (BAM) Neural Network

This document provides comprehensive MATLAB source code for implementing a Bidirectional Associative Memory (BAM) neural network. BAM represents a significant two-layer, heteroassociative neural network architecture widely used in artificial intelligence and machine learning applications, particularly for bidirectional pattern association and recall tasks. The implementation includes core algorithmic components such as weight matrix initialization using Hebbian learning rules, bidirectional pattern recall mechanisms, and stability verification procedures. Key functions demonstrate how to train the network with pattern pairs and perform forward/backward recalls between pattern domains. The MATLAB code structure features: - Weight matrix calculation using correlation-based learning - Pattern recall functions supporting both directions (A→B and B→A) - Energy function computation to verify network stability - Iterative recall processes with convergence checks By analyzing and experimenting with this implementation, researchers and developers can gain practical insights into neural network design principles, understand bidirectional association mechanisms, and adapt the framework for real-world pattern recognition applications. The code serves as an educational foundation for exploring associative memory networks and their extensions.