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Ultra-low-voltage integrable electronic implementation of delayed inertial neural networks for complex dynamical behavior using multiple activation functions

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Abstract

Ultra-low-voltage sinh-domain implementation of delayed inertial neuron is introduced in this paper. The complex dynamical behavior of the neuron has been verified using three different activation functions, namely tanh, unipolar sigmoidal and bipolar sigmoidal. The networks containing two and four neurons have been designed, and their complex dynamical behavior has also been verified. The proposed implementation vis-à-vis the already reported designs offers the benefits of: (1) low-voltage operation, (2) integrability, due to resistor-less design and the employment of only grounded components, (3) electronic tunability of performance parameters by external currents, which adds flexibility to the proposed designs even after their final fabrication, (4) absence of inductors as, in contrast to reported designs, the delay has been implemented using component substitution method where inductors have been replaced by emulated inductors and (5) low-power implementation due to the inherent class AB nature of sinh-domain technique. Besides, for the first time, the complex dynamical behavior of four-neuron delayed inertial network has been implemented and its functioning for different activations functions has been considered and verified. HSPICE simulator tool and TSMC 130 nm CMOS process were used to evaluate and verify the correct functioning of the model.

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Acknowledgements

This work was supported by Science and Engineering Research Board (SERB), Department of Science and Technology (DST), Government of India, under the Extra Mural Research (EMR) Scheme (EMR/2016/007125).

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Authors and Affiliations

  1. Department of Electronics and Instrumentation Technology, University of Kashmir, Hazratbal, Srinagar, Jammu and Kashmir, India

    Farooq Ahmad Khanday, Mohammad Rafiq Dar & Nasir Ali Kant

  2. Electrical and Electronic Engineering Department, Universiti Teknologi PETRONAS, 32610, Seri Iskandar, Perak, Malaysia

    Tun Zainal Azni Zulkifli

  3. Electronics Laboratory, Physics Department, University of Patras, 26504, Rio Patras, Greece

    Costas Psychalinos

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  1. Farooq Ahmad Khanday
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  2. Mohammad Rafiq Dar
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Correspondence to Farooq Ahmad Khanday.

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Khanday, F.A., Dar, M.R., Kant, N.A. et al. Ultra-low-voltage integrable electronic implementation of delayed inertial neural networks for complex dynamical behavior using multiple activation functions. Neural Comput & Applic 32, 8297–8314 (2020). https://doi.org/10.1007/s00521-019-04322-6

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  • DOI: https://doi.org/10.1007/s00521-019-04322-6

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