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Bipin Kumar Tripathi
Harcourt Butler Technical University
Earth & Planetary Sciences Environmental Science Materials Science & Nanotechnology Mathematics Physics

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On the High Dimentional Information Processing in Quaternionic Domain and its Applications Sushil Kumar; Bipin Kumar Tripathi
International Journal of Advances in Applied Sciences Vol 7, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (655.989 KB) | DOI: 10.11591/ijaas.v7.i2.pp177-190

Abstract

There are various high dimensional engineering and scientific applications in communication, control, robotics, computer vision, biometrics, etc.; where researchers are facing problem to design an intelligent and robust neural system which can process higher dimensional information efficiently. The conventional real-valued neural networks are tried to solve the problem associated with high dimensional parameters, but the required network structure possesses high complexity and are very time consuming and weak to noise. These networks are also not able to learn magnitude and phase values simultaneously in space.  The quaternion is the number, which possesses the magnitude in all four directions and phase information is embedded within it. This paper presents a well generalized learning machine with a quaternionic domain neural network that can finely process magnitude and phase information of high dimension data without any hassle. The learning and generalization capability of the proposed learning machine is presented through a wide spectrum of simulations which demonstrate the significance of the work.
Co-Authors Sushil Kumar