Neural network based on parametrically-pumped oscillators

We demonstrate that sub-harmonic injection locked oscillators (SHILOs) can serve as building blocks of neural networks. After numerically studying the locking properties of injection-locked ring-oscillator models, we show that resistively or capacitively interconnected networks of such oscillators f...

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Bibliographic Details
Published in2016 IEEE International Conference on Electronics, Circuits and Systems (ICECS) pp. 45 - 48
Main Authors Csaba, Gyorgy, Ytterdal, Trond, Porod, Wolfgang
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2016
Subjects
Couplings
Integrated circuit interconnections
Inverters
Neural networks
Non-Boolean computing
Novel computing architectures
Oscillatory computing
Ring oscillators
Stationary state
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Summary:We demonstrate that sub-harmonic injection locked oscillators (SHILOs) can serve as building blocks of neural networks. After numerically studying the locking properties of injection-locked ring-oscillator models, we show that resistively or capacitively interconnected networks of such oscillators fall into well-defined ground states, which ground states, in turn, depend on the strength of interconnections. We argue that these networks may serve as efficient hardware implementations for emerging neural network-based processing devices.
DOI:10.1109/ICECS.2016.7841128