Abstract
IBM Research and five leading universities are partnering to create computing systems that are expected to simulate and emulate the brain’s abilities. Although this project has achieved some successes, it meets great difficulties in the further research. The main difficulty is that it is almost impossible to analyze the dynamic character of neural networks in detail, when more than ten thousands neurons of complex nonlinear neural models are piled up. So it is nature to present such question: in order to simplify the design of brain-like computers, can we use simple neuron models to design brain-like computers or can we find a simplest neuron model which can simulate most neuron models with arbitrary precision? In this paper, we proved that almost all neural models found by neural scientists nowadays can be simulated by Hopfield neural networks. So it is possible to use simple neuron model to design Brain-like computers.
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Hu, H., Shi, Z. (2012). The Possibility of Using Simple Neuron Models to Design Brain-Like Computers. In: Zhang, H., Hussain, A., Liu, D., Wang, Z. (eds) Advances in Brain Inspired Cognitive Systems. BICS 2012. Lecture Notes in Computer Science(), vol 7366. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31561-9_41
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DOI: https://doi.org/10.1007/978-3-642-31561-9_41
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