Approximate Probabilistic Neural Networks with Gated Threshold Logic

O. Krestinskaya; Alex James Pappachen

doi:10.1109/NANO.2018.8626302

Approximate Probabilistic Neural Networks with Gated Threshold Logic

O. Krestinskaya, Alex James Pappachen

Department of Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Probabilistic Neural Network (PNN) is a feedforward artificial neural network developed for solving classification problems. This paper proposes a hardware implementation of an approximated PNN (APNN) algorithm in which the conventional exponential function of the PNN is replaced with gated threshold logic. The weights of the PNN are approximated using a memristive crossbar architecture. In particular, the proposed algorithm performs normalization of the training weights, and quantization into 16 levels which significantly reduces the complexity of the circuit.

Original language	English
Title of host publication	18th International Conference on Nanotechnology, NANO 2018
Publisher	IEEE Computer Society
ISBN (Electronic)	9781538653364
DOIs	https://doi.org/10.1109/NANO.2018.8626302
Publication status	Published - Jan 24 2019
Event	18th International Conference on Nanotechnology, NANO 2018 - Cork, Ireland Duration: Jul 23 2018 → Jul 26 2018

Publication series

Name	Proceedings of the IEEE Conference on Nanotechnology
Volume	2018-July
ISSN (Print)	1944-9399
ISSN (Electronic)	1944-9380

Conference

Conference	18th International Conference on Nanotechnology, NANO 2018
Country	Ireland
City	Cork
Period	7/23/18 → 7/26/18

Fingerprint

ASJC Scopus subject areas

Bioengineering
Electrical and Electronic Engineering
Materials Chemistry
Condensed Matter Physics

Cite this

Krestinskaya, O., & James Pappachen, A. (2019). Approximate Probabilistic Neural Networks with Gated Threshold Logic. In 18th International Conference on Nanotechnology, NANO 2018 [8626302] (Proceedings of the IEEE Conference on Nanotechnology; Vol. 2018-July). IEEE Computer Society. https://doi.org/10.1109/NANO.2018.8626302

Approximate Probabilistic Neural Networks with Gated Threshold Logic. / Krestinskaya, O.; James Pappachen, Alex.

18th International Conference on Nanotechnology, NANO 2018. IEEE Computer Society, 2019. 8626302 (Proceedings of the IEEE Conference on Nanotechnology; Vol. 2018-July).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Krestinskaya, O & James Pappachen, A 2019, Approximate Probabilistic Neural Networks with Gated Threshold Logic. in 18th International Conference on Nanotechnology, NANO 2018., 8626302, Proceedings of the IEEE Conference on Nanotechnology, vol. 2018-July, IEEE Computer Society, 18th International Conference on Nanotechnology, NANO 2018, Cork, Ireland, 7/23/18. https://doi.org/10.1109/NANO.2018.8626302

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Access to Document

10.1109/NANO.2018.8626302