Paper
3 May 2011 A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy
Jens Müller, Jan Müller, Ronald Tetzlaff
Author Affiliations +
Abstract
For processing of EEG signals, we propose a new architecture for the hardware emulation of discrete-time Cellular Nonlinear Networks (DT-CNN). Our results show the importance of a high computational accuracy in EEG signal prediction that cannot be achieved with existing analogue VLSI circuits. The refined architecture of the processing elements and its resource schedule, the cellular network structure with local couplings, the FPGA-based embedded system containing the DT-CNN, and the data flow in the entire system will be discussed in detail. The proposed DT-CNN design has been implemented and tested on an Xilinx FPGA development platform. The embedded co-processor with a multi-threading kernel is utilised for control and pre-processing tasks and data exchange to the host via Ethernet. The performance of the implemented DT-CNN has been determined for a popular example and compared to that of a conventional computer.
© (2011) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jens Müller, Jan Müller, and Ronald Tetzlaff "A new cellular nonlinear network emulation on FPGA for EEG signal processing in epilepsy", Proc. SPIE 8068, Bioelectronics, Biomedical, and Bioinspired Systems V; and Nanotechnology V, 80680M (3 May 2011); https://doi.org/10.1117/12.886766
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CITATIONS
Cited by 4 scholarly publications.
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KEYWORDS
Electroencephalography

Signal processing

Field programmable gate arrays

Nonlinear optics

Epilepsy

Network architectures

Biomedical optics

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