Spin Torque Nano-Oscillator Based Oscillatory Neural Network

Keywords

Associative memory; Frequency locking; LLG; Oscillatory neural network; Phase locked loop; Phase locking; Spin torque oscillators

Abstract

Oscillatory Neural Networks (ONN) are becoming a popular neuromorphic computing model owing to their efficient parallel processing capabilities. Hoppensteadt and Izhikevich proposed an ONN architecture resembling associative memory, with Phase-Locked Loop (PLL) circuits as neurons. Unfortunately, there are shortcomings in realizing such architectures due to the inefficiencies of CMOS based implementations of oscillators and other hardware. We propose a PLL structure for ONN applications fashioned using energy efficient and scalable Spin Torque Oscillators (STOs). We demonstrate the functionality of a 60 neuron ONN using STOs for binary image identification.

Publication Date

10-31-2016

Publication Title

Proceedings of the International Joint Conference on Neural Networks

Volume

2016-October

Number of Pages

1387-1394

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/IJCNN.2016.7727360

Socpus ID

85007236748 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85007236748

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