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Open Access research which pushes advances in bionanotechnology

Strathprints makes available scholarly Open Access content by researchers in the Strathclyde Institute of Pharmacy & Biomedical Sciences (SIPBS) , based within the Faculty of Science.

SIPBS is a major research centre in Scotland focusing on 'new medicines', 'better medicines' and 'better use of medicines'. This includes the exploration of nanoparticles and nanomedicines within the wider research agenda of bionanotechnology, in which the tools of nanotechnology are applied to solve biological problems. At SIPBS multidisciplinary approaches are also pursued to improve bioscience understanding of novel therapeutic targets with the aim of developing therapeutic interventions and the investigation, development and manufacture of drug substances and products.

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Adaptive empirical mode decomposition for signal enhancement with application to speech

Chatlani, Navin and Soraghan, J.J. (2008) Adaptive empirical mode decomposition for signal enhancement with application to speech. In: 15th International Conference on Systems, Signals and Image Processing, 2008. IEEE, pp. 101-104. ISBN 978-80-227-2856-0

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Abstract

Speech enhancement is performed in a wide and varied range of instruments and systems. In this paper, a novel approach to signal enhancement using adaptive empirical mode decomposition (SEAEMD) is presented. Spectral analysis of non-stationary signals can be performed by employing techniques such as the STFT and the Wavelet transform, which use predefined basis functions. The empirical mode decomposition (EMD) performs very well in such environments and it decomposes a signal into a finite number of data-adaptive basis functions, called intrinsic mode functions (IMFs). The new SEAEMD system incorporates this multi-resolution approach with adaptive noise cancellation in order to perform signal enhancement on an IMF level. In comparison to the conventional adaptive noise cancellation, the application of SEAEMD to speech gives rise to improved quality and lower level of residual noise.