Research Paper2023
DMD-CGR: Dynamic Mode Decomposition-based Novel Features for DNA sequence classification
Developed a novel Dynamic Coherent Features through Progressive Rank Approximations (DCFPRA) technique for pathogen classification at the genus level. The method leverages Dynamic Mode Decomposition for feature extraction from genomic sequences, achieving superior performance over traditional alignment-based methods while being computationally efficient for large-scale datasets.
Aadharsh, A., Edpuganti, A., Mohan, N., Kumar, S.S., & Soman, K.P.
Published in: Proceedings of the IEEE 2023 3rd International Conference for Intelligent Technologies (CONIT), Hubballi, Karnataka, India
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An Informal Introduction to Semirings for Graph-BLAS using Matlab
Created an accessible educational framework for understanding semirings and GraphBLAS implementations using Matlab. This work simplifies complex mathematical concepts and provides practical tools for graph algorithms and linear algebra applications, making high-performance computing techniques more approachable for practitioners without deep mathematical backgrounds.
Aadharsh, A., Edpuganti, A., Mohan, N., Kumar, S.S., & Soman, K.P.
Published in: Proceedings of the IEEE 2023 3rd International Conference for Intelligent Technologies (CONIT), Hubballi, Karnataka, India
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Investigating the Significance of Special Measurement Matrices for DMD based Frequency Estimation
Explored the role of specialized measurement matrices in enhancing Dynamic Mode Decomposition (DMD) algorithms for frequency estimation tasks. The research evaluates how different matrix configurations impact accuracy and computational efficiency in signal processing applications, providing insights for optimizing DMD-based frequency analysis methods.
Edpuganti, A., Mohan, J., Mohan, N., Kumar, S.S., & Soman, K.P.
Published in: Proceedings of the International Conference on Automation, Signal Processing, Instrumentation and Control (iCASIC 2022)
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