Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Thesis
Thematic Areas : Center for Computational Engineering and Networking (CEN)
Publisher : Computer Science, Volume Ph.D Thesis
Source : Computer Science, Volume Ph.D Thesis (2013)
Keywords : algorithm, GROUP theory, Signal processing
Campus : Coimbatore
School : School of Engineering
Center : Center for Computational Engineering and Networking
Department : Center for Computational Engineering and Networking (CEN), Computer Science
Year : 2013
Abstract : Different signal processing transforms provide us with unique decomposition capabilities. Instead of using specific transformation for every type of signal, we propose in this paper a novel way of signal processing using a group of transformations within the limits of Group theory. For different types of signal different transformation combinations can be chosen. It is found that it is possible to process a signal at multiresolution and extend it to perform edge detection, denoising, face recognition, etc by filtering the local features. For a finite signal there should be a natural existence of basis in it’s vector space. Without any approximation using Group theory it is seen that one can get close to this finite basis from different viewpoints. Dihedral groups have been demonstrated for this purpose.
Cite this Research Publication : Dr. Rajathilagam B., “G-lets: A New Signal Processing Algorithm”, 2013.