Shie Qian

National Instruments (United States)

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Dapang Chen

National Instruments (Ireland)

Xiang‐Gen Xia

University of Delaware

Joel Morris

University of Maryland, Baltimore County

Robert J. Sclabassi

Computational Diagnostics (United States)

Xiaopu Yan

University of Pittsburgh

Stephen B. Baumann

Psychology Software Tools (United States)

Dapang Chen

National Instruments (Ireland)

Qinye Yin

Xi'an Jiaotong University

Victor C. Chen

United States Naval Research Laboratory

Shidong Li

San Francisco State University

Cooperative Institutions

University of Pittsburgh

Neurological Surgery

University of Pittsburgh Medical Center

Northwestern University

National Instruments (Ireland)

Tongji University

Los Alamos National Laboratory

University of Science and Technology Beijing

Shenyang Ligong University

Wenzhou Medical University

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A new approach for signal synthesis from smoothed versions of the Wigner distribution

Shie Qian Joel Morris

A pseudo-simulated annealing (PSA) technique for signal synthesis from smoothed versions of the Wigner distribution is proposed. The PSA adopts a deterministic local search strategy to complement the global search of traditional simulated annealing and accomplish a faster convergence. The squared-error in the joint time-frequency domain is minimized with relation to the real sample sequence directly and, thereby, reduces the phase ambiguity to either 0 or pi . Simulation results are provided to indicate the effectiveness of this approach.< >

Wigner distribution function

Complement

SIGNAL (programming language)

10.1109/icassp.1991.150140

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Citations (1)

A Comparison of the Newly Proposed Gabor Order Tracking Technique vs. Other Order Tracking Methods

SAE technical papers on CD-ROM/SAE technical paper series (2001)

Michael F. Albright Shie Qian

Tracking (education)

10.4271/2001-01-1471

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Citations (15)

Wigner Distribution decomposition and cross-terms deleted representation

Signal Processing (1992)

Shie Qian Joel Morris

Wigner distribution function

Gabor transform

SIGNAL (programming language)

Line (geometry)

10.1016/0165-1684(92)90003-f

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Citations (65)

From the Guest Editors

IEEE Signal Processing Magazine (1999)

Shie Qian Dapang Chen

Presents the guest editorial for this issue of the publication.

10.1109/msp.1999.752056

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Citations (2)

General time-frequency distribution series

Dapang Chen Shie Qian

In this paper, we present a new and robust method, general time-frequency distribution series (TFDS), for time-frequency analysis. We also introduce the concept of local interference and global interference and show that the local interference is important and the global interference is less important in TF analysis. The TFDS is very general. With only one parameter, the order of the TFDS, one can easily balance different and competing requirements for the best result.< >

10.1109/tfsa.1994.467320

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Citations (0)

Convergence of an iterative time-variant filtering based on discrete Gabor transform

IEEE Transactions on Signal Processing (1999)

Xiang‐Gen Xia Shie Qian

An iterative time-variant filtering based on the discrete Gabor transform (DGT) has been previously proposed by the authors. In this article, we present a proof of the convergence of the iterative algorithm under a sufficient condition on the analysis and synthesis window functions of the DGT. In the meantime, we show that the iterative algorithm refines the least squares solution.

Gabor transform

10.1109/78.790674

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Citations (26)

<title>New methods and applications of time-frequency analysis</title>

Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE (1998)

Shie Qian

In this paper, we introduce a new time-dependent power spectrum, the Gabor spectrogram. Compared to other methods, the Gabor spectrogram is not only easier for balancing crossterm interference, time-frequency resolution, and other useful properties, but it is also amenable to software as well as hardware implementation. Over the last five years, the Gabor spectrogram has been successfully applied in many areas, such as radar and medical images, noise and vibration, and non-destructive testing.

Spectrogram

10.1117/12.304877

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Citations (1)

On the rank of the discrete Gabor transform matrix

Signal Processing (2001)

Xiang‐Gen Xia Shie Qian

Gabor transform

Matrix (chemical analysis)

Discrete frequency domain

Rank (graph theory)

Discrete-time signal

10.1016/s0165-1684(00)00271-1

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Citations (2)

Localizing functional activity in the brain through time-frequency analysis and synthesis of the EEG

Proceedings of the IEEE (1996)

Mingui Sun Shie Qian Xiaopu Yan Stephen B. Baumann Xiang‐Gen Xia

Multichannel electroencephalograms (EEGs) are processed using time-frequency (TF) analysis and synthesis techniques to geometrically localize neuroelectric generators of specific activity contained within the observed EEG. The TF domain techniques are utilized to separate the signals of interest from the remainder of the EEG, by allowing the definition of regions of interest which contain the signals for which we desire to localize the underlying neuronal generators. This approach essentially introduces a filtering technique which allows the distortionless separation of the signals of interest from all other components recorded. The source of the functional activity in the brain is estimated and mapped numerically by a least-squares approach. We have applied these techniques to identify the anatomical location of the sleep spindle, a component of the EEG observed during sleep, which is of importance in understanding the generation of sleep and sleep patterns.

Sleep

Sleep spindle

10.1109/5.535248

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Citations (33)

Gabor transforms: some new properties on the Gabor transform matrix

Xiang‐Gen Xia Shie Qian

By using the discrete Gabor transform or expansion, the time domain sequences are mapped into the joint time-frequency domain matrices or vice versa. In many applications, it is more effective to process signals, i.e., two dimensional matrices, in the joint time-frequency domain than in the time or frequency domain alone. From the mathematical point of view, the processing of the discrete Gabor coefficients is no more than the matrix computation. So it is beneficial to understand the properties of the Gabor coefficient matrix. In this paper, we investigate the rank of the Gabor coefficient matrix of a one dimensional time domain signal, which is one of the most important matrix properties.

Gabor transform

Matrix (chemical analysis)

Rank (graph theory)

Gabor wavelet

Discrete frequency domain

10.1109/acssc.1998.750971

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Citations (1)