Application issues of a programmable optical CNN implementation

L. Orzó, S. T. Kés, T. Roska

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A programmable opto-electronic analogic CNN computer (POAC) provides an efficient frame for diverse image processing applications, as it combines the enormous inherent computational capabilities of our new, massively parallel, but flexibly programmable optical CNN implementation with the capabilities of a visual CNN-UM chip. Our optical CNN implementation is based on an original, semi-incoherent optical correlator architecture, which is superior to other optical implementations in several respects. It makes real time reprogramming of a new type of joint Fourier transform correlator (t2-JTC) possible while preserving the inherent speed of VanderLugt type of systems. Furthermore the POAC architecture overcomes the main limitations of both the microelectronic (VLSI) and other optical implementations. In this paper it will be shown that this device is particularly useful in image-processing algorithms, which cannot be fulfilled real time by any other existing optical or digital system due to the high number of pattern matching tasks required.

Original languageEnglish
Title of host publicationProceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages156-163
Number of pages8
Volume2002-January
ISBN (Print)981238121X
DOIs
Publication statusPublished - 2002
Event7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002 - Frankfurt, Germany
Duration: Jul 22 2002Jul 24 2002

Other

Other7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002
CountryGermany
CityFrankfurt
Period7/22/027/24/02

Fingerprint

Correlators
Image processing
Computer architecture
Pattern matching
Microelectronics
Fourier transforms
Correlator
Optoelectronics
Image Processing
Computer Architecture
Pattern Matching
Fourier transform
Chip

Keywords

  • Application software
  • Cellular neural networks
  • Computer architecture
  • Concurrent computing
  • Correlators
  • Fourier transforms
  • Image processing
  • Microelectronics
  • Optical computing
  • Real time systems

ASJC Scopus subject areas

  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering
  • Modelling and Simulation

Cite this

Orzó, L., Kés, S. T., & Roska, T. (2002). Application issues of a programmable optical CNN implementation. In Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications (Vol. 2002-January, pp. 156-163). [1035048] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CNNA.2002.1035048

Application issues of a programmable optical CNN implementation. / Orzó, L.; Kés, S. T.; Roska, T.

Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications. Vol. 2002-January Institute of Electrical and Electronics Engineers Inc., 2002. p. 156-163 1035048.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Orzó, L, Kés, ST & Roska, T 2002, Application issues of a programmable optical CNN implementation. in Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications. vol. 2002-January, 1035048, Institute of Electrical and Electronics Engineers Inc., pp. 156-163, 7th IEEE International Workshop on Cellular Neural Networks and their Applications, CNNA 2002, Frankfurt, Germany, 7/22/02. https://doi.org/10.1109/CNNA.2002.1035048
Orzó L, Kés ST, Roska T. Application issues of a programmable optical CNN implementation. In Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications. Vol. 2002-January. Institute of Electrical and Electronics Engineers Inc. 2002. p. 156-163. 1035048 https://doi.org/10.1109/CNNA.2002.1035048
Orzó, L. ; Kés, S. T. ; Roska, T. / Application issues of a programmable optical CNN implementation. Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications. Vol. 2002-January Institute of Electrical and Electronics Engineers Inc., 2002. pp. 156-163
@inproceedings{f70959ab681346a6b0f6281d02567f69,
title = "Application issues of a programmable optical CNN implementation",
abstract = "A programmable opto-electronic analogic CNN computer (POAC) provides an efficient frame for diverse image processing applications, as it combines the enormous inherent computational capabilities of our new, massively parallel, but flexibly programmable optical CNN implementation with the capabilities of a visual CNN-UM chip. Our optical CNN implementation is based on an original, semi-incoherent optical correlator architecture, which is superior to other optical implementations in several respects. It makes real time reprogramming of a new type of joint Fourier transform correlator (t2-JTC) possible while preserving the inherent speed of VanderLugt type of systems. Furthermore the POAC architecture overcomes the main limitations of both the microelectronic (VLSI) and other optical implementations. In this paper it will be shown that this device is particularly useful in image-processing algorithms, which cannot be fulfilled real time by any other existing optical or digital system due to the high number of pattern matching tasks required.",
keywords = "Application software, Cellular neural networks, Computer architecture, Concurrent computing, Correlators, Fourier transforms, Image processing, Microelectronics, Optical computing, Real time systems",
author = "L. Orz{\'o} and K{\'e}s, {S. T.} and T. Roska",
year = "2002",
doi = "10.1109/CNNA.2002.1035048",
language = "English",
isbn = "981238121X",
volume = "2002-January",
pages = "156--163",
booktitle = "Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Application issues of a programmable optical CNN implementation

AU - Orzó, L.

AU - Kés, S. T.

AU - Roska, T.

PY - 2002

Y1 - 2002

N2 - A programmable opto-electronic analogic CNN computer (POAC) provides an efficient frame for diverse image processing applications, as it combines the enormous inherent computational capabilities of our new, massively parallel, but flexibly programmable optical CNN implementation with the capabilities of a visual CNN-UM chip. Our optical CNN implementation is based on an original, semi-incoherent optical correlator architecture, which is superior to other optical implementations in several respects. It makes real time reprogramming of a new type of joint Fourier transform correlator (t2-JTC) possible while preserving the inherent speed of VanderLugt type of systems. Furthermore the POAC architecture overcomes the main limitations of both the microelectronic (VLSI) and other optical implementations. In this paper it will be shown that this device is particularly useful in image-processing algorithms, which cannot be fulfilled real time by any other existing optical or digital system due to the high number of pattern matching tasks required.

AB - A programmable opto-electronic analogic CNN computer (POAC) provides an efficient frame for diverse image processing applications, as it combines the enormous inherent computational capabilities of our new, massively parallel, but flexibly programmable optical CNN implementation with the capabilities of a visual CNN-UM chip. Our optical CNN implementation is based on an original, semi-incoherent optical correlator architecture, which is superior to other optical implementations in several respects. It makes real time reprogramming of a new type of joint Fourier transform correlator (t2-JTC) possible while preserving the inherent speed of VanderLugt type of systems. Furthermore the POAC architecture overcomes the main limitations of both the microelectronic (VLSI) and other optical implementations. In this paper it will be shown that this device is particularly useful in image-processing algorithms, which cannot be fulfilled real time by any other existing optical or digital system due to the high number of pattern matching tasks required.

KW - Application software

KW - Cellular neural networks

KW - Computer architecture

KW - Concurrent computing

KW - Correlators

KW - Fourier transforms

KW - Image processing

KW - Microelectronics

KW - Optical computing

KW - Real time systems

UR - http://www.scopus.com/inward/record.url?scp=11144303491&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=11144303491&partnerID=8YFLogxK

U2 - 10.1109/CNNA.2002.1035048

DO - 10.1109/CNNA.2002.1035048

M3 - Conference contribution

AN - SCOPUS:11144303491

SN - 981238121X

VL - 2002-January

SP - 156

EP - 163

BT - Proceedings of the IEEE International Workshop on Cellular Neural Networks and their Applications

PB - Institute of Electrical and Electronics Engineers Inc.

ER -