Architecture of a fully pipelined real-time cellular neural network emulatort

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Tarih

2015-01

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Yayıncı

IEEE-INST Electrical Electronics Engineers Inc

Erişim Hakkı

info:eu-repo/semantics/closedAccess

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Özet

In this paper, architecture of a Real-Time Cellular Neural Network (CNN) Processor (RTCNNP-v2) is given and the implementation results are discussed. The proposed architecture has a fully pipelined structure, capable of processing full-HD 1080p@60 (1920 1080 resolution at 60 Hz frame rate, 124.4 MHz visible pixel rate) video streams, which is implemented on both high-end and low-cost FPGA devices, Altera Stratix IV GX 230, and Cyclone III C 25, respectively. Many features of the architecture are designed to be either pre-synthesis configurable or runtime programmable, which makes the processor extremely flexible, reusable, scalable, and practical.

Açıklama

Anahtar Kelimeler

Cellular neural networks, Field programmable gate arrays, Real time systems, Reconfigurable architectures

Kaynak

IEEE Transactions on Circuits and Systems I: Regular Papers

WoS Q Değeri

Q1
Q1

Scopus Q Değeri

Q1

Cilt

62

Sayı

1

Künye

Yıldız, N., Cesur, E., Kayaer, K., Tavşanogğu, A. V. & Alpay, M. (2015). Architecture of a fully pipelined real-time cellular neural network emulator. IEEE Transactions on Circuits and Systems I: Regular Papers, 62(1), 130-138. doi:10.1109/TCSI.2014.2345502