Sandeep Paul

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A new subsethood-product fuzzy neural inference system (SuPFuNIS) is presented in this paper. It has the flexibility to handle both numeric and linguistic inputs simultaneously. Numeric inputs are fuzzified by input nodes which act as tunable feature fuzzifiers. Rule based knowledge is easily translated directly into a network architecture. Connections in(More)
Nervous system is one of the most complex networks known to mankind. An attempt in understanding and analyzing the functionalities of the nervous system would provide solutions to various problem pertaining in fields like medicine, robotics, ergonomics, bio-mechanics, medical research etc. Basic activities like rapid eye movements (Saccades), hand movements(More)
This paper presents an approach to time series prediction based on Asymmetric Subsethood-Product Fuzzy Neural Inference System (ASuPFuNIS). The standard time series techniques have standard averaging where a fixed weight is added to the past values. In this paper we present a novel neurofuzzy inference system based on asymmetric subsethood with intervention(More)