کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
390416 661253 2011 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Dynamic system modeling using a recurrent interval-valued fuzzy neural network and its hardware implementation
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Dynamic system modeling using a recurrent interval-valued fuzzy neural network and its hardware implementation
چکیده انگلیسی

This paper first proposes a new recurrent interval-valued fuzzy neural network (RIFNN) for dynamic system modeling. A new hardware implementation technique for the RIFNN using a field-programmable gate array (FPGA) chip is then proposed. The antecedent and consequent parts in an RIFNN use interval-valued fuzzy sets in order to increase the network noise resistance ability. A new recurrent structure is proposed in RIFNN, with the recurrent loops enabling it to handle dynamic system processing problems. An RIFNN is constructed from structure and parameter learning. For hardware implementation of the RIFNN, the pipeline technique and a new circuit for type-reduction operation are proposed to improve the chip performance. Simulations and comparisons with various feedforward and recurrent fuzzy neural networks verify the performance of the RIFNN under noisy conditions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuzzy Sets and Systems - Volume 179, Issue 1, 16 September 2011, Pages 83-99