Dheeresh Kumar Mallick

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In the current work, we have proposed a parallel algorithm for the recognition of Epileptic Spikes (ES) in EEG. The automated systems are used in biomedical field to help the doctors and pathologist by producing the result of an inspection in real time. Generally, the biomedical signal data to be processed are very large in size. A uniprocessor computer is(More)
The present paper gives a statistical adventure towards exploring the average case complexity behavior of computer algorithms. Rather than following the traditional count based analytical (pen and paper) approach, we instead talk in terms of the weight based analysis that permits mixing of distinct operations into a conceptual bound called the statistical(More)
In this paper we present an adaptable fast matrix multiplication (AFMM) algorithm , for two nxn dense matrices which computes the product matrix with average complexity Tavg(n) = μ’d1d2n with the acknowledgement that the average count is obtained for addition as the basic operation rather than multiplication which is probably the unquestionable choice for(More)
Theoretical analysis of algorithms involves counting of operations and a separate bound is provided for a specific operation type. Such a methodology is plagued with its inherent limitations. In this paper we argue as to why we should prefer weight based statistical bounds, which permit mixing of operations, instead as a robust approach. Empirical analysis(More)
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