کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5000403 1460686 2017 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Efficient hardware implementation of radial basis function neural network with customized-precision floating-point operations
ترجمه فارسی عنوان
اجرای سخت افزاری کارآمد شبکه عصبی مبتنی بر شعاع با عملیات دقیق نقطه شناور سفارشی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی هوافضا
چکیده انگلیسی
This paper aims at the proposition of novel architectures for radial basis function neural networks implementation on hardware with custom-precision floating-point operations for black-box system modeling. An analysis tool was built to establish the trade-off between the consumption of hardware resources and the precision of the outputs, on the basis of the usage of the logic blocks on a field-programmable gate array and output quality. The architectures have been tested with a standard system identification benchmark and the speedup factors, when compared to a C implementation, are on the order of hundreds, what shows the importance of ad-hoc hardware architectures for improving computational efficiency.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Control Engineering Practice - Volume 60, March 2017, Pages 124-132
نویسندگان
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