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Memristive neuro-fuzzy system
, Article IEEE Transactions on Cybernetics ; Volume 43, Issue 1 , January , 2013 , Pages 269-285 ; 21682267 (ISSN) ; Shouraki, S. B ; Sharif University of Technology
2013
Abstract
In this paper, a novel neuro-fuzzy computing system is proposed where its learning is based on the creation of fuzzy relations by using a new implication method without utilizing any exact mathematical techniques. Then, a simple memristor cross-bar-based analog circuit is designed to implement this neuro-fuzzy system which offers very interesting properties. In addition to high connectivity between neurons and being fault tolerant, all synaptic weights in our proposed method are always non-negative, and there is no need to adjust them precisely. Finally, this structure is hierarchically expandable, and it can do fuzzy operations in real time since it is implemented through analog circuits....
A novel pipeline architecture of replacing ink drop spread
, Article Proceedings - 2010 2nd World Congress on Nature and Biologically Inspired Computing, NaBIC 2010, 15 December 2010 through 17 December 2010, Kitakyushu ; 2010 , Pages 127-133 ; 9781424473762 (ISBN) ; Bagheri Shouraki, S ; Tabandeh, M ; Mousavi, H. R ; Sharif University of Technology
2010
Abstract
Human Brain is one of the most wonderful and complex systems which is designed for ever; A huge complex network composed of neurons as tiny biological and chemical processors which are distributed and work together as a super parallel system to do control and vital activities of human body. Brain learning simulation and hardware implementation is one of the most interesting research areas in order to make artificial brain. One of the researches in this area is Active Learning Method in brief ALM. ALM is an adaptive recursive fuzzy learning algorithm based on brain functionality and specification which models a complex Multi Input Multi Output System as a fuzzy combination of Single Input...