A realistic mammalian retinal model implemented on complex cell CNN universal machine

D. Bálya, Cs Rekeczky, T. Roska

Research output: Contribution to journalConference article

6 Citations (Scopus)

Abstract

The visual system is probably the most important sensory modality for humans as well as for mammals. Its first and best-known part is the retina, which is not a mere photoreceptor or static camera but a sophisticated feature preprocessor with a continuous input and several parallel output channels [1]. These channels build up a "visual language" and any realistic mammalian retina model should generate the elements of this visual language. The framework of mammalian retinal modeling via multi-layer CNN has been recently published [2]. In the present paper we show the transformation of this model into a CNN-UM algorithm and the design steps of the implementation of this complex visual language. The analogic algorithm consists of a series of different complex-cell CNN dynamics [3]. The algorithm is feasible on a recently fabricated complex cell CNN-UM chip. The decomposition method of the multilayer mammalian retina model will be discussed in detail.

Original languageEnglish
Pages (from-to)IV/161-IV/164
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume4
Publication statusPublished - Jan 1 2002
Event2002 IEEE International Symposium on Circuits and Systems - Phoenix, AZ, United States
Duration: May 26 2002May 29 2002

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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