FPGA implementations of scale-invariant models of neural networks

Authors

ZEINULLA ZHANABAEV
YELDOS KOZHAGULOV
DAUREN ZHEXEBAY

Abstract

Integrated circuit implementations of new models of neural networks with scale-invariant properties are presented. The specifics of such models are necessary in analysis of discrete mappings containing fractional power. We suggest an algorithm for increasing the power of a physical value by using a field-programmable gate array (FPGA). Comparisons between FPGA implementations and numerical results are demonstrated.

DOI

10.3906/elk-1504-204

Keywords

Neural networks, field-programmable gate array, digital scheme, scale invariance

First Page

5090

Last Page

5099

Recommended Citation

ZHANABAEV, ZEINULLA; KOZHAGULOV, YELDOS; and ZHEXEBAY, DAUREN (2016) "FPGA implementations of scale-invariant models of neural networks," Turkish Journal of Electrical Engineering and Computer Sciences: Vol. 24: No. 6, Article 40. https://doi.org/10.3906/elk-1504-204
Available at: https://journals.tubitak.gov.tr/elektrik/vol24/iss6/40