Implementation issues of neuro-fuzzy hardware: going toward HW/SW codesign
- 6 February 2003
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Neural Networks
- Vol. 14 (1) , 176-194
- https://doi.org/10.1109/tnn.2002.806955
Abstract
This paper presents an annotated overview of existing hardware implementations of artificial neural and fuzzy systems and points out limitations, advantages, and drawbacks of analog, digital, pulse stream (spiking), and other implementation techniques. We analyze hardware performance parameters and tradeoffs, and the bottlenecks which are intrinsic in several implementation methodologies. The constraints posed by hardware technologies onto algorithms and performance are also described. The results of the analyses proposed lead to the use of hardware/software codesign, as a means of exploiting the best from both hardware and software techniques. Hardware/software codesign appears, at present, the most promising research area concerning the implementation of neuro-fuzzy systems (not including bioinspired systems, which are out of the scope of this work), as it allows the fast design of complex systems with the highest performance/cost ratio.Keywords
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