201. Architecture of a Fully Pipelined Real-Time Cellular Neural Network Emulator.
- Author
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Yildiz, Nerhun, Cesur, Evren, Kayaer, Kamer, Tavsanoglu, Vedat, and Alpay, Murathan
- Subjects
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CELLULAR neural networks (Computer science) , *EMULATION software , *DATA pipelining , *FIELD programmable gate arrays , *CONTINUOUS-time filters , *RUN time systems (Computer science) - Abstract
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 \times 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. [ABSTRACT FROM AUTHOR]
- Published
- 2015
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