Bingo Wing-Kuen Ling

Guangdong University of Technology

205Publications

18H-index

1,000Citations

Publications 204

Newest

Underlying Trend Extraction via Joint Ensemble Intrinsic Timescale Decomposition Algorithm and Matching Pursuit Approach

#1Xiaoling Wang (GDUT: Guangdong University of Technology)

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Time series usually consist of an underlying trend and the irregularities. Therefore, the underlying trend extraction plays an important role in the analysis of the time series. This paper proposes a method which combines the ensemble intrinsic timescale decomposition (EITD) algorithm and the matching pursuit (MP) approach for performing the underlying trend extraction. In order to extract the underlying trend, the EITD algorithm is applied to obtain a set of components. Then, the first componen...

Linear phase properties of the singular spectrum analysis components for the estimations of the RR intervals of electrocardiograms

#1Xiaozhu Mo (GDUT: Guangdong University of Technology)

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Last.Yang Zhou (GDUT: Guangdong University of Technology)H-Index: 2

view all 4 authors...

Denoising is the first step in both the QRS complex detection and the beat classification. However, infinite impulse response filters usually exhibit nonlinear phase responses. As a result, the group delays of the output signals based on the infinite impulse response filtering are different at different time instants. This causes the inaccuracies of the estimations of the RR intervals of the electrocardiograms. In this paper, the denoising is performed based on the singular spectrum analysis app...

Properties of approximated empirical mode decomposition and optimal design of its system kernel matrix for signal decomposition

#1Nili Tian (Guangzhou Higher Education Mega Center)

#2Xiaoling Wang (Guangzhou Higher Education Mega Center)

Last.Mustafa Sakalli (Marmara University)

view all 4 authors...

An approximated empirical mode decomposition generates a set of approximated intrinsic mode functions via a linear, nonadaptive but iterative approach. The decomposition was found to be very useful for a content-independent pattern recognition application. As the process is characterized by a system kernel matrix and performed iteratively, the approximated intrinsic mode functions can be understood as the original signals processed by a set of mask operations. Here, some properties of the decomp...

Piecewise linear relationship between L1 norm objective functional values and L∞ norm constraint specifications

#1Qing Miao (FOSU: Foshan University)

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Last.Xiaoling Wang (GDUT: Guangdong University of Technology)

view all 3 authors...

Abstract For a sparse optimization problem with an L 1 norm objective function subject to an L ∞ norm inequality constraint, this paper finds that there is a piecewise linear relationship between the L 1 norm objective functional values and the L ∞ norm constraint specifications. This piecewise linear relationship is proved mathematically. Also, computer numerical simulations on a set of signal vectors verify the validity of this result. This result can provide a guidance for system analysts to ...

Parallel implementation of empirical mode decomposition for nearly bandlimited signals via polyphase representation

#1Qiuliang Ye (GDUT: Guangdong University of Technology)

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Last.Weichao Kuang (GDUT: Guangdong University of Technology)H-Index: 2

view all 4 authors...

Nearly bandlimited signals play an important role in the biomedical signal processing community. The common method to analyze these signals is via the empirical mode decomposition approach which decomposes the non-stationary signals into the sums of the intrinsic mode functions. However, this method is computational demanding. A natural idea to reduce the computational cost is via the block processing. However, the severe boundary effect would happen due to the discontinuities between two consec...

#1Libo Huang (Guangzhou Higher Education Mega Center)H-Index: 1

#2Bingo Wing-Kuen Ling (Guangzhou Higher Education Mega Center)H-Index: 18

Last.Yao Chen (Guangzhou Higher Education Mega Center)H-Index: 3

view all 6 authors...

In recent years, the signal processing opportunities with the multi-channel recording and the high precision detection provided by the development of new extracellular multi-electrodes are increasing. Hence, designing new spike sorting algorithms are both attractive and challenging. These algorithms are used to distinguish the individual neurons’ activity from the dense and simultaneously recorded neural action potentials with high accuracy. However, since the overlapping phenomenon often inevit...

#1Yang Zhou (GDUT: Guangdong University of Technology)H-Index: 2

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Moving object detection is a fundamental and necessary step in many computer vision algorithms. These algorithms are built in many intelligent devices such as in the smartphones, the tachographs and the personal video recorders. Recently, the methods for performing the moving object detection based on the low-rank representation have been proposed. For these methods, it is assumed that the background is represented by a low-rank matrix. On the other hand, the foreground objects cannot be represe...

Decimations of intrinsic mode functions via semi-infinite programming based optimal adaptive nonuniform filter bank design approach

#1Chuqi Yang (GDUT: Guangdong University of Technology)H-Index: 1

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Last.Jialiang Gu (GDUT: Guangdong University of Technology)H-Index: 1

view all 4 authors...

Abstract A signal can be represented as the sum of the intrinsic mode functions via performing the empirical mode decomposition. For the discrete time signals, the lengths of the intrinsic mode functions are equal to the lengths of the input signals. As there is usually more than one intrinsic mode function, the total numbers of discrete points of all the intrinsic mode functions are usually more than the lengths of the input signals. In other words, the empirical mode decomposition is an oversa...

#1Nili Tian (GDUT: Guangdong University of Technology)H-Index: 1

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Last.Kok Lay Teo (Curtin University)H-Index: 48

view all 5 authors...

The main problem to be addressed in this paper is on the high required computational powers of the existing fractional pixel location search algorithms. The current solution method is based on the computation of the phase shift of the power spectral densities of two consecutive frames of a video sequence. Since the probability density function of each frame of the video sequence is required for computing its power spectral density but it is unknown in the practical situation, this method is not ...

Singular spectral analysis-based denoising without computing singular values via augmented Lagrange multiplier algorithm

#1Peihua Feng (GDUT: Guangdong University of Technology)H-Index: 1

#2Bingo Wing-Kuen Ling (GDUT: Guangdong University of Technology)H-Index: 18

Last.Jinrong Chen (GDUT: Guangdong University of Technology)

view all 4 authors...

This study proposes an augmented Lagrange multiplier-based method to perform the singular spectral analysis-based denoising without computing the singular values. In particular, the one-dimensional (1D) signal is first mapped to a trajectory matrix using the window length L . Second, the trajectory matrix is represented as the sum of the signal dominant matrix and the noise-dominant matrix. The determination of these two matrices is formulated as an optimisation problem with the objective functi...

12345678910