Çarpmasız yapay sinir ağı

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Multiplication-free Neural Networks [Çarpmasiz Yapay Sinir Aʇi].pdf (280.24 KB)

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2015-05

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Abstract

Bu bildiride çarpma işlemi kullanmadan oluşturulan bir Yapay Sinir Ağı (YSA) sunulmaktadır. Girdi vektörleri ve YSA katsayılarının iç çarpımları çarpmasız bir vektör işlemiyle hesaplanmıştır. Yapay sinir ağının eğitimi sign-LMS algoritması ile yapılmıştır. Önerilen YSA sistemi, hesap gücü kısıtlı olan veya düşük enerji tüketimine ihtiyaç duyulan mikroişlemcilerde kullanılabilir.


In this article, a multiplication-free artificial Neural Network (ANN) structure is proposed. Inner products between the input vectors and the ANN weights are implemented using a multiplication-free vector operator. Training of the new artificial neural network structure is carried out using the sign-LMS algorithm. Proposed ANN system can be used in applications requiring low-power usage or running on microprocessors that have limited processing power. © 2015 IEEE.

Source Title

23rd Signal Processing and Communications Applications Conference, SIU 2015 - Proceedings

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IEEE

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Keywords

Artificial Neural Network, Multiplication-free Operator, Neural networks, Inner product, Input vector, LMS algorithms, Low Power, Multiplication-free Operator, Processing power, Vector operators, Signal processing

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http://hdl.handle.net/11693/28530

Published Version (Please cite this version)

http://dx.doi.org/10.1109/SIU.2015.7130369

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Scholarly Publications - Electrical and Electronics Engineering

Language

Turkish

Type

Conference Paper