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)
Myocellular regeneration in vertebrates involves the proliferation of activated progenitor or dedifferentiated myogenic cells that have the potential to replenish lost tissue. In comparison little is known about cellular repair mechanisms within myocellular tissue in response to small injuries caused by biomechanical or cellular stress. Using a microarray(More)
Synovial joints are the lubricated connections between the bones of our body that are commonly affected in arthritis. It is assumed that synovial joints first evolved as vertebrates came to land, with ray-finned fishes lacking lubricated joints. Here, we examine the expression and function of a critical lubricating protein of mammalian synovial joints,(More)
—This paper presents an approach to time series prediction based on Asymmetric Subsethood-Product Fuzzy Neu-ral 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 neuro-fuzzy inference system based on asymmetric subsethood with(More)