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Zhang Beibei

Researcher at Anhui University

Publications -  5
Citations -  25

Zhang Beibei is an academic researcher from Anhui University. The author has contributed to research in topics: Blind signal separation & Frequency domain. The author has an hindex of 3, co-authored 5 publications receiving 23 citations.

Papers
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Journal ArticleDOI

A permutation algorithm based on dynamic time warping in speech frequency-domain blind source separation

TL;DR: A permutation algorithm based on Dynamic Time Warping (DTW) is proposed to improve the quality of the separated speech and improves the acoustic quality of separation.
Patent

Scanning signal feature extraction method based on independent component analysis and recognition method

TL;DR: In this paper, a scanning signal feature extraction method based on independent component analysis (ICA) is presented. But the method comprises the steps that six-lead scanning eye electric signals are collected and subjected to band-pass filtering treatment, an airspace filter set corresponding to different scanning task backgrounds is built through an ICA method for filtered data, linear protection is carried out, and airspace feature parameters of scanning signals are obtained.
Journal ArticleDOI

Robust EOG-based saccade recognition using multi-channel blind source deconvolution

TL;DR: A robust EOG-based saccade recognition using the multi-channel convolutional independent component analysis (ICA) method and a constraint direction of arrival (DOA) algorithm that can automatically adjust the order of eye movement sources according to the constraint angle are proposed.
Patent

Robust scanning EOG signal recognition method and system

TL;DR: In this article, a robust scanning EOG signal recognition method and system is presented, which includes the following steps that EOG multi-channel eye movement data is acquired, and eye movement in time domain is pre-treated to obtain eye movement from the frequency domain; the independent components, after compensation and sorting, of each frequency point are subjected to short time Fourier inverse transformation and restored into multichannel EOG data of the time domain.
Patent

Low-speed eye motion recognition method and system based on convolution hybrid model

TL;DR: In this article, a low-speed eye motion recognition method and system based on a convolution hybrid model was proposed, and the method comprises the steps that a complex value ICA algorithm is adopted for performing blind source separation on eye motion data, and a frequency domain isolated component of each independent source signal on a corresponding frequency point is obtained.