학술논문

Ramanujan Sums-Wavelet Transform: A New Approach to Signal Processing
Document Type
Conference
Source
2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT) Intelligent Computing Instrumentation and Control Technologies (ICICICT), 2022 Third International Conference on. :179-183 Aug, 2022
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Image resolution
Image coding
Instruments
Time series analysis
Energy resolution
Feature extraction
Discrete wavelet transforms
Ramanujan Sums
wavelet transform
discrete wavelet transform (DWT)
time series
Language
Abstract
Ramanujan Sum is a trigonometric summation introduced by Srinivasa Ramanujan in 1918. Recently, this summation technique is widely used in digital signal processing applications like pattern recognition, feature extraction, signal analysis, image compression, etc. Ramanujan Sums-Wavelet Transform (RSWT) is a signal analysis tool introduced by Chen et al. in 2013, in which the multiresolution representation nature of the wavelet transform and the energy conservation property of the Ramanujan Sums transform are blended to extract more useful information from the signal. Ordinary wavelet transform can be obtained as a special case of RSWT and hence it provides us with a multitude of ways to analyze signals under consideration. In this paper, we discuss RSWT in one-dimensional signal analysis, especially in time series analysis.