Yanti, D.K. and Yusoff, M.Z. and Asirvadam, V.S. (2011) Widely linear based filter using Short Term Fourier Transform for Visual Evoked Potential extraction. In: UNSPECIFIED.
Full text not available from this repository.Abstract
Noise reduction is normally carried out in time domain and works well with the real-valued signal. The reduction of noise can also be performed in frequency domain. However, the signal must be transformed into complex random variable. The widely linear distortionless (WLD) filter has already been used for the speech enhancement. The WLD filter utilizes the Short Term Fourier Transform (STFT) to transform real valued signals into complex random variables in the frequency domain. The designed filter exclusively depends on the non-circularity coefficient of the non-stationary signal. Moreover, WLD filter works well even in the very noisy environments where the input signal-to-noise ratio (SNR) is far down below 0 dB. Visual Evoked Potential (VEP) is known as non-stationary signal and its characteristic shows that this signal also has very low SNR such as 10 dB. In this paper, we have proposed the frequency domain based WLD filter for VEP estimation. The results demonstrate that the WLD filter has been able to better estimate the VEP signals, as it effectively suppressed the unwanted VEP signal peaks. Moreover, it also raised the amplitudes of the desired peaks to considerable levels for their easy detections. © 2011 IEEE.
Item Type: | Conference or Workshop Item (UNSPECIFIED) |
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Additional Information: | cited By 0; Conference of 3rd National Postgraduate Conference - Energy and Sustainability: Exploring the Innovative Minds, NPC 2011 ; Conference Date: 19 September 2011 Through 20 September 2011; Conference Code:88531 |
Uncontrolled Keywords: | circularity; Complex-valued signal; noisy environment; Nonstationary signals; Short time Fourier transforms; Visual evoked potential; Widely linear estimations, Random variables; Speech enhancement; Sustainable development, Frequency domain analysis |
Depositing User: | Mr Ahmad Suhairi UTP |
Date Deposited: | 09 Nov 2023 15:49 |
Last Modified: | 09 Nov 2023 15:49 |
URI: | https://khub.utp.edu.my/scholars/id/eprint/1716 |