№2, 2018
A WAVELET-BASED FILTRATION METHOD OF NOISY TECHNOLOGICAL ACOUSTIC AND SPEECH SIGNALS
scb_06@gmail.com, pasha.farhad@gmail.com, bikies418@gmail.com, ulker.rzaeva@gmail.com, vusal_bayramov84@mail.ru
In this paper a wavelet-based denoising algorithm applied to technological acoustic and speech noisy signals is proposed. The analysis is done by applying discrete wavelet transform to technological acoustic and speech noisy signals and applying new denoising method for reconstruction of wavelets. The analysis is verified through simulation studies (pp.25-29).
Keywords: Wavelet Transform, Acoustic Signals, Speech Signals, Denoising, MATLAB.
DOI : 10.25045/jpit.v09.i2.03
References
- Pashayev F.H. Smoothing algorithms for characteristics of seismic-acoustic signals // Azerbaijan Oil Industry, 2013, №6, pp.42–48.
- Pashayev F.H., Pakdel M., Rzaeva N. A Wavelet Based Denoising of Seismic Acoustic Signals / IV ALL-Ukranian Scientific-Practical conf. “Informatics and Systems sciences”, Poltava, 2013, pp. 310–313.
- Guluev G., Pashayev F. Pakdel M., Sattarova U. Prediction of Signal Characteristics Using Autoregressive Moving Average Method / IV International Conf. “Problems of Cybernetics and Informatics”, vol.II, 12–14.09.2012, Baku, pp.102–104.
- Sukhostat L.V. Adaptive noise reduction method based on empirical wavelet transform // Problems of Information Technology, 2017, №1, pp 53–58.
- Lockwood O.G., Kanamori H. Wavelet analysis of the seismograms of the 2004 Sumatra-Andaman earthquake and its application to tsunami early warning // Geochemistry Geophysics Geosystems, 2006, no.7, pp. 1–10.
- Pramanik N., Rabindra K. PAdvPSanda and Adarsh Singh. Daily river flow forecasting using wavelet ANN hybrid models // Journal of Hydroinformatics, 2011, no.1, pp. 49–63.
- Haltmeier M. et al. Compressed sensing and sparsity in photoacoustic tomography // Journal of Optics, 2016, 18 114004, pp. 1–12.
- Daubechies I., Ten Lectures on Wavelets, New York: SIAM, 1992, 357 p.
- Mallat S.G. A Wavelet Tour of Signal Processing, Academic Press, 3rd Edition, 2008, 832 p.
- Mallat S.G. A Theory of Multiresolution Signal Decomposition: The Wavelet Representation // IEEE Transactions on Pattern Analysis and Machine Intelligence, July 1989, 11(7),
674–693. - Vidakovic B., Lozoya C.B. On time-dependent wavelet denoising // IEEE Transaction on Signal Processing, 1998, vol.46, no.9, pp. 2549–2554.
