Deep Belief Network (DBN) Implementation Code

This is a test program implementing a Deep Belief Network (DBN) algorithm using stacked Restricted Boltzmann Machines (RBMs). The current implementation employs contrastive divergence for training individual RBMs and includes both pre-training and fine-tuning phases. However, the performance results have been suboptimal, possibly due to parameter tuning challenges or architectural limitations in the neural network layers.