Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi

Hacer Atar Yildiz

doi:10.1109/SIU49456.2020.9302124

Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi

Hacer Atar Yildiz^*

^*Bu çalışma için yazışmadan sorumlu yazar

Elektronik ve Hab.Müh.Bölümü

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

Özet

A CMOS Gaussian function generator circuit suitable for the implementation of analog neural networks is proposed. For this purpose, it is considered the polynomial approximation of the Gaussian function. The proposed circuit realizes the Gaussian function characteristic inherently, that is without requiring any accurate tuning or adjustment of the circuit parameters. In order to show the usefulness of the proposed circuit, simulation results obtained using Spectre Simulation tool in Cadence design environment are provided. These results show the validity of the theoretical analysis and feasibility of the proposed structure.

Tercüme edilen katkı başlığı	Gaussian Activation Function Realization with Application to the Neural Network Implementations
Orijinal dil	Türkçe
Ana bilgisayar yayını başlığı	2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings
Yayınlayan	Institute of Electrical and Electronics Engineers Inc.
ISBN (Elektronik)	9781728172064
DOI'lar	https://doi.org/10.1109/SIU49456.2020.9302124
Yayın durumu	Yayınlandı - 5 Eki 2020
Etkinlik	28th Signal Processing and Communications Applications Conference, SIU 2020 - Gaziantep, Turkey Süre: 5 Eki 2020 → 7 Eki 2020

Yayın serisi

Adı	2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings

???event.eventtypes.event.conference???

???event.eventtypes.event.conference???	28th Signal Processing and Communications Applications Conference, SIU 2020
Ülke/Bölge	Turkey
Şehir	Gaziantep
Periyot	5/10/20 → 7/10/20

Bibliyografik not

Publisher Copyright:
© 2020 IEEE.

Keywords

Activation function
Gaussian function
Neural network implementation

Belgeye Erişim

10.1109/SIU49456.2020.9302124

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Yildiz, H. A. (2020). Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi. In 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings Makale 9302124 (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SIU49456.2020.9302124

@inproceedings{c3c5ee6b28f045f3821817aae716bef4,

title = "Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi",

abstract = "A CMOS Gaussian function generator circuit suitable for the implementation of analog neural networks is proposed. For this purpose, it is considered the polynomial approximation of the Gaussian function. The proposed circuit realizes the Gaussian function characteristic inherently, that is without requiring any accurate tuning or adjustment of the circuit parameters. In order to show the usefulness of the proposed circuit, simulation results obtained using Spectre Simulation tool in Cadence design environment are provided. These results show the validity of the theoretical analysis and feasibility of the proposed structure.",

keywords = "Activation function, Gaussian function, Neural network implementation",

author = "Yildiz, {Hacer Atar}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 28th Signal Processing and Communications Applications Conference, SIU 2020 ; Conference date: 05-10-2020 Through 07-10-2020",

year = "2020",

month = oct,

day = "5",

doi = "10.1109/SIU49456.2020.9302124",

language = "T{\"u}rk{\c c}e",

series = "2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

booktitle = "2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings",

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}

Yildiz, HA 2020, Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi. in 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings., 9302124, 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 28th Signal Processing and Communications Applications Conference, SIU 2020, Gaziantep, Turkey, 5/10/20. https://doi.org/10.1109/SIU49456.2020.9302124

Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi. / Yildiz, Hacer Atar.
2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2020. 9302124 (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings).

Araştırma sonucu: ???type-name??? › Konferans katkısı › bilirkişi

TY - GEN

T1 - Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi

AU - Yildiz, Hacer Atar

PY - 2020/10/5

Y1 - 2020/10/5

N2 - A CMOS Gaussian function generator circuit suitable for the implementation of analog neural networks is proposed. For this purpose, it is considered the polynomial approximation of the Gaussian function. The proposed circuit realizes the Gaussian function characteristic inherently, that is without requiring any accurate tuning or adjustment of the circuit parameters. In order to show the usefulness of the proposed circuit, simulation results obtained using Spectre Simulation tool in Cadence design environment are provided. These results show the validity of the theoretical analysis and feasibility of the proposed structure.

AB - A CMOS Gaussian function generator circuit suitable for the implementation of analog neural networks is proposed. For this purpose, it is considered the polynomial approximation of the Gaussian function. The proposed circuit realizes the Gaussian function characteristic inherently, that is without requiring any accurate tuning or adjustment of the circuit parameters. In order to show the usefulness of the proposed circuit, simulation results obtained using Spectre Simulation tool in Cadence design environment are provided. These results show the validity of the theoretical analysis and feasibility of the proposed structure.

KW - Activation function

KW - Gaussian function

KW - Neural network implementation

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U2 - 10.1109/SIU49456.2020.9302124

DO - 10.1109/SIU49456.2020.9302124

M3 - Konferans katkısı

AN - SCOPUS:85100304760

T3 - 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings

BT - 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 28th Signal Processing and Communications Applications Conference, SIU 2020

Y2 - 5 October 2020 through 7 October 2020

ER -

Yildiz HA. Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi. In 2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2020. 9302124. (2020 28th Signal Processing and Communications Applications Conference, SIU 2020 - Proceedings). doi: 10.1109/SIU49456.2020.9302124

Yapay Sinir Aglari Uygulamalarina Yonelik Gauss Aktivasyon Fonksiyonu Gerceklemesi

Özet

Yayın serisi

???event.eventtypes.event.conference???

Bibliyografik not

Keywords

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap