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arXiv · 2305.10468

CHNNet: An Artificial Neural Network With Connected Hidden Neurons

Rafiad Sadat Shahir·Zayed Humayun·Mashrufa Akter Tamim·Shouri Saha·Md. Golam Rabiul Alam·Abu Mohammad Khan
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Abstract

In contrast to biological neural circuits, conventional artificial neural networks are commonly organized as strictly hierarchical architectures that exclude direct connections among neurons within the same layer. Consequently, information flow is primarily confined to feedforward and feedback pathways across layers, which limits lateral interactions and constrains the potential for intra-layer information integration. We introduce an artificial neural network featuring intra-layer connections among hidden neurons to overcome this limitation. Owing to the proposed method for facilitating intra-layer connections, the model is theoretically anticipated to achieve faster convergence compared to conventional feedforward neural networks. The experimental findings provide further validation of the theoretical analysis.

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Rafiad Sadat Shahir, Zayed Humayun, Mashrufa Akter Tamim, Shouri Saha, Md. Golam Rabiul Alam, Abu Mohammad Khan. 2023-05-17. CHNNet: An Artificial Neural Network With Connected Hidden Neurons. https://arxiv.org/abs/2305.10468

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