IoT-Oriented Design of an Associative Memory Based on Impulsive Hopfield Neural Network with Rate Coding of LIF Oscillators
The smart devices in Internet of Things (IoT) need more effective data storage opportunities, as well as support for Artificial Intelligence (AI) methods such as neural networks (NNs). This study presents a design of new associative memory in the form of impulsive Hopfield network based on leaky int...
Main Author: | Petr Boriskov |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-09-01
|
Series: | Electronics |
Subjects: | |
Online Access: | https://www.mdpi.com/2079-9292/9/9/1468 |
Similar Items
-
Computational Complexity of Hopfield Networks
by: Tseng, Hung-Li
Published: (1998) -
Discrete Mutation Hopfield Neural Network in Propositional Satisfiability
by: Mohd Shareduwan Mohd Kasihmuddin, et al.
Published: (2019-11-01) -
Integrating ECG Monitoring and Classification via IoT and Deep Neural Networks
by: Li-Ren Yeh, et al.
Published: (2021-06-01) -
Beyond the Maximum Storage Capacity Limit in Hopfield Recurrent Neural Networks
by: Giorgio Gosti, et al.
Published: (2019-07-01) -
Sparse Computation in Adaptive Spiking Neural Networks
by: Davide Zambrano, et al.
Published: (2019-01-01)