Wavelet Transforms Applications and Interpretation Based on the Signal Genesis
S. Ananthi Arun1, Ananthanarayanan2, S. Sivakannan3, G. Prashanth4
1Dr. S. Ananthi, Professor, Department of Electronics and Communication Engineering, MVJ College of Engineering Bangalore (Karnataka), India.
2Dr. Arun Ananthanarayanan, Assistant Professor, Department of Electronics and Communication Engineering, MVJ College of Engineering Bangalore (Karnataka), India.
3Sivakannan Subramani, Assistant Professor, Department of Electronics and Communication Engineering, MVJ College of Engineering, Bangalore (Karnataka), India.
4Mr. Prahanth, Assistant Professor, Department of Electronics and Communication Engineering, MVJ College of Engineering, Bangalore (Karnataka), India.
Manuscript received on 24 November 2019 | Revised Manuscript received on 07 December 2019 | Manuscript Published on 14 December 2019 | PP: 30-37 | Volume-9 Issue-1S October 2019 | Retrieval Number: A10061091S19/19©BEIESP | DOI: 10.35940/ijeat.A1006.1091S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: A signal from any measurement system provides insight into its genesis, thereby enabling an understanding of a certain activity or phenomenon. Seismic signals, radar echo signals, physiological signals, signals from specially fabricated instruments such as MRI, CT scanner all provide information by using an analysis that resolves the signal into its frequency components. While the Fourier transform and its fast – evaluating algorithm known as FFT are standard for such analysis, there are presently additional signal transforms in use, of which “ Wavelets” or Wavelet transform or wavelet decomposition are becoming very important. If the Fourier transform resolved the signal into its spectral components of Sine and Cosine waves, the Wavelets do the same in terms of non- sinusoidal oscillatory wave-shapes of burst – like appearance. This paper deals with the choice of wavelet transforms based on signal genesis and the interpretation required from the analysis of the signal, that one is expected to infer.
Keywords: Fourier Transform, Haar, Morlet. Daubechies Wavelet Transform, Denoising, Data Compression.
Scope of the Article: Signal and Image Processing