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Dimensional reduction is a primary way to analyze and work with complex and large amount of multidimensional data by avoiding the effect of curse of dimensionality. This problem of constructing low dimensional embedding gains importance in number of fields like artificial intelligence, image processing, geographical research and lot more. In this paper, we introduce a modified locally linear embedding,...
With rapid technological development and growth of sequencing data, an umpteen gamut of biological data has been generated. As an alternative, Data Compression is employed to reduce the size of data. In this direction, this paper proposes a new reference-based compression approach, which is employed as a solution. Firstly, a reference has been constructed from the common sub strings of randomly selected...
A novel class of CIC FIR filter functions has been developed recently which preserves the simpleness of classical CIC FIR filters by avoiding multipliers but shows improvement in stopband attenuation. In this paper, a compensator filter has been used to reduce the passband droop of the novel class of CIC filter functions. The compensator performs effectual compensation using three additions/subtractions...
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