Study on the Capacity of Hopfield Neural Networks

Sulehria, Humayun Karim; Zhang, Ye

doi:10.3923/itj.2008.684.688

Cited by 6 publications

(1 citation statement)

References 20 publications

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“…The most prominent feature of the Hopfield neural network concept is designed closely related to circuit hardware deployment [58]. The main idea of the Hopfield is the use of the hardware circuit to simulate neural network optimization process.…”

Section: Hopfield Algorithmmentioning

confidence: 99%

An Overview of Neuromorphic Computing for Artificial Intelligence Enabled Hardware-Based Hopfield Neural Network

Abdulghani

Zahid

et al. 2020

IEEE Access

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Compared with von Neumann's computer architecture, neuromorphic systems offer more unique and novel solutions to the artificial intelligence discipline. Inspired by biology, this novel system has implemented the theory of human brain modeling by connecting feigned neurons and synapses to reveal the new neuroscience concepts. Many researchers have vastly invested in neuro-inspired models, algorithms, learning approaches, operation systems for the exploration of the neuromorphic system and have implemented many corresponding applications. Recently, some researchers have demonstrated the capabilities of Hopfield algorithms in some large-scale notable hardware projects and seen significant progression. This paper presents a comprehensive review and focuses extensively on the Hopfield algorithm's model and its potential advancement in new research applications. Towards the end, we conclude with a broad discussion and a viable plan for the latest application prospects to facilitate developers with a better understanding of the aforementioned model in accordance to build their own artificial intelligence projects. Neuromorphic computing, neuro-inspired model, Hopfield algorithm, artificial intelligence. INDEX TERMS

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Section: Hopfield Algorithmmentioning

confidence: 99%