Learning algorithms and implementation

Olga Krestinskaya; Alex Pappachen James

doi:10.1007/978-3-030-14524-8_7

Learning algorithms and implementation

Olga Krestinskaya, Alex Pappachen James

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

2 Scopus citations

Abstract

This chapter provides a brief overview of learning algorithms and their implementations on hardware. We focus on memristor based systems for leaning, as this is one of the most promising solutions to implement deep neural network on hardware, due to the small on-chip area and low power consumption.

Original language	English (US)
Title of host publication	Modeling and Optimization in Science and Technologies
Publisher	Springer [email protected]
Pages	91-102
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-030-14524-8_7
State	Published - Jan 1 2020
Externally published	Yes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-23

ASJC Scopus subject areas

Modeling and Simulation
Medical Assisting and Transcription
Applied Mathematics

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10.1007/978-3-030-14524-8_7

Cite this

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year = "2020",

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AB - This chapter provides a brief overview of learning algorithms and their implementations on hardware. We focus on memristor based systems for leaning, as this is one of the most promising solutions to implement deep neural network on hardware, due to the small on-chip area and low power consumption.

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PB - Springer [email protected]

ER -

Learning algorithms and implementation

Abstract

Bibliographical note

ASJC Scopus subject areas

Access to Document

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