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Bacterial foraging algorithm for neutron radiography image quality improvement

Bacterial foraging algorithm for neutron radiography image q...

引用

International Multi-Conference on Systems, signals and Devices

作者： Saadi, S. Kouzou, A. Guessoum, A. Bettayeb, M. Department of Electronics University Ziane Achour of Djelfa Algeria Department of Electronics Signal and Image Processing Laboratory USDB Blida Algeria Department of Electrical and Computer Engineering University of Sharjah United Arab Emirates

ISBN: (纸本)9781424475346

We want to implement a new optimal approach for image restoration problem, which is useful for neutron radiography images enhancement to assist the physician interpreter on his evaluation. Our approach is based on using swarm intelligence optimization algorithms to solve a least squares minimization ill-posed problem, using Bacterial Foraging Optimization (BFO) Algorithm. To get smoothed images in presence of noise, a Laplacian constraint is introduced for regularization purpose. ©2010 IEEE.

关键词： Image reconstruction

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Inference of gene regulatory networks from time-series microarray data

Inference of gene regulatory networks from time-series micro...

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Annual IEEE Northeast Workshop on Circuits and Systems (NEWCAS)

作者： Ola ElBakry M. Omair Ahmad M. N. S. Swamy Center of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

The regulation of gene expression is a dynamic process, hence it is of vital interest to identify and characterize these dynamic processes. Since genes work in a cascade of networks, gene regulatory network (GRN) reconstruction is a crucial process for thorough understanding of the underlying biological interactions. We present here a technique based on partial correlations to infer the GRN. Our proposed technique takes into account the possible and variable time delays between various genes. The results have shown that our proposed algorithm has results consistent with the existing biological knowledge. Our algorithm is implemented in R.

关键词： Correlation Delay Gene expression Bioinformatics Delay effects Humans Graphical models

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Spectral clustering approach with sparsifying technique for functional connectivity detection in the resting brain

Spectral clustering approach with sparsifying technique for ...

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2010 International Conference on Intelligent and Advanced Systems, ICIAS 2010

作者： Ramezani, Mahdi Heidari, Amin Fatemizadeh, Emad Soltanian-Zadeh, Hamid Biomedical Signal and Image Processing Laboratory Sharif University of Technology Tehran Iran Radiology Image Analysis Laboratory Henry Ford Health System Detroit MI 48202 United States Control and Intelligent Processing Center of Excellence Electrical and Computer Engineering Department University of Tehran Iran

ISBN: (纸本)9781424466238

The aim of this study is to assess the functional connectivity from resting state functional magnetic resonance imaging (fMRI) data. Spectral clustering algorithm was applied to the realistic and real fMRI data acquired from a resting healthy subject to find functionally connected brain regions. In order to make computation of the spectral decompositions of the entire brain volume feasible, the similarity matrix has been sparsified with the t-nearestneighbor approach. Realistic data were created to investigate the performance of the proposed algorithm and comparing it to the recently proposed spectral clustering algorithm with the Nystrom approximation and also with some well-known algorithms such as the Cross Correlation Analysis (CCA) and the spatial Independent Component Analysis (sICA). To enhance the performance of the methods, a variety of data pre and post processing steps, including data normalization, outlier removal, dimensionality reduction by using wavelet coefficients, estimation of number of clusters and optimal number of independent components (ICs). Results demonstrate the applicability of the proposed algorithm for functional connectivity analysis.

关键词： Brain

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A broadband speech enhancement technique based on frequency invariant beamforming and GSC

A broadband speech enhancement technique based on frequency ...

引用

1st International Conference on Green Circuits and Systems, ICGCS 2010

作者： Zou, Yue-Xian Li, Bo Liu, Wei Advanced Digital Signal Processing Laboratory School of Computer and Information Engineering Peking University Shenzhen Graduate School Shenzhen China Communications Research Group Dept. of Electronic and Electrical Engineering University of Sheffield S1 3JD Sheffield United Kingdom

ISBN: (纸本)9781424468775

Speech enhancement is one of the key and challenging techniques for a real-time speech recording system working in a meeting room, where cancellation of the competing speech and improvement of the speech intelligibility are two major concerns. In this paper, the application of frequency invariant beamforming to the speech enhancement problem based on the generalized sidelobe cancellation (GSC) structure is studied. It leads to a novel hybrid broadband speech enhancement technique, which combines the ideas of subband processing, frequency invariant beamforming and voice activity detection under the GSC framework. Simulation results show that the proposed method outperforms two previously proposed ones in terms of speech distortion, background noise and competing speech reduction. © 2010 IEEE.

关键词： Speech enhancement

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A novel morphology-based classifier for automatic detection of epileptic seizures

A novel morphology-based classifier for automatic detection ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Rajeev Yadav R. Agarwal M.N.S. Swamy Center of Signal Processing and Communications CENSIPCOMM Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

Most of the automatic seizure detection schemes reported in the literature are complex for detecting seizures that are of (a) short duration, (b) minimal amplitude evolution, or (c) non-rhythmic mixed frequency epileptic activity. We present a novel morphology-based classifier to detect epileptic seizures for intracranial EEG recording. The method characterizes epileptic seizure by detecting continual presence of sharp half-waves in the EEG. Performance is evaluated on single channel intracranial EEG of seven patients, and compared to two previously developed methods for intracranial EEG recordings by our research group. The method detects seizure of varying types (rhythmic, non-rhythmic, short- and long- seizures) with a sensitivity of 100%, a false detection rate of 0.1/h and an average onset delay of 9.1 s. The method outperforms the two previously developed methods and is computationally simple for real-time application. Preliminary results on seven patients data are very promising.

关键词： Electroencephalography Delay Feature extraction Sensitivity Filtering Monitoring Brain modeling

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Local spectrum sensing in non-Gaussian noise

Local spectrum sensing in non-Gaussian noise

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International Conference on Telecommunications (ICT)

作者： Sayed Jalal Zahabi Ali. A. Tadaion Statistical Signal Processing Laboratory Department of Electrical and Computer Engineering Yazd University Yazd Iran

This paper deals with the local spectrum sensing problem in non-Gaussian noise. It is of great importance to reliably detect the presence of licensed users in cognitive radio. This task highly depends on the noise distribution, thus it is important to characterize the noise behavior as best as possible. Although Gaussian assumption for noise is of interest due to many reasons, it sometimes fails to model the behavior of noise in practice. In this paper we present a local spectrum sensing scheme in a broad family of non-Gaussian noise. We reasonably assume that the Primary User (PU) signal is Phase Shift Keying (PSK) modulated, where the number of constellation points, M, and the symbol code sequence are unknown to the Secondary Users (SU), as in practice. We also assume that the SUs are unaware of the PU signal complex amplitude and the non-Gaussian noise variance. Within this framework, we obtain the Generalized Likelihood Ratio Test (GLRT) as our spectrum sensing scheme and propose an approximate implementation of the resulting GLRT. Simulation results show that our proposed scheme has an acceptable performance.

关键词： Gaussian noise Phase shift keying Cognitive radio Testing Phase modulation Modulation coding Constellation diagram signal processing Laboratories Gaussian distribution

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Wideband DOA estimation using two sensors

Wideband DOA estimation using two sensors

引用

International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2010

作者： Gu, Jian-Feng Li, Nan-Jun Wei, Ping Tai, Heng-Ming Department of Electronic Engineering University of Electronic Science and Technology of China Chengdu Sichuan 610054 China Centre for Signal Processing and Communications Dept. of Electrical and Computer Engineering Concordia University Montreal QC H3G 1M8 Canada Department of Electrical Engineering University of Tulsa Tulsa OK 74104 United States

ISBN: (纸本)9780769539621

This paper proposes an efficient direction-of-arrival (DOA) estimation algorithm for wideband signals from data collected using two sensors. Like the traditional wideband methods, this algorithm first decomposes wideband sources into narrowband bins. At each frequency bin, the cross-correlation between sensors is estimated to construct a Toeplitz matrix, which contains all angle information. Thus the physical size between two sensors is independent of the frequency bins and relies more on the inter-frequency bin difference. The proposed method is flexible in the design of the sensor array without inducing ambiguities. Simulation results confirm the ability of the proposed method that provides reliable estimates in multiple wideband signal environments. © 2010 IEEE.

关键词： Array processing

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Frame Interpolation Method Based on Adaptive Threshold and Adjacent Pixels

Frame Interpolation Method Based on Adaptive Threshold and A...

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International Conference on Intelligent Information Hiding and Multimedia signal processing (IIHMSP)

作者： Hyeongchul Oh Joohyun Lee Changki Min Jechang Jeong Image Communication and Signal Processing Laboratory Department of Electrical and Computer Engineering Hanyang University Seoul South Korea

This paper presents a frame interpolation algorithm using the motion information of some object within the estimated blocks. The proposed algorithm uses two initial frames that are generated based on the backward and forward frames using the motion vectors. In this process, the occlusion regions are occurred in two initial frames since the optimal block is only selected by threshold. Furthermore, the regions are irregularly appeared because of that the selected block is interpolated on half position between the estimated motion vectors. Two initial frames are merged to interpolate the occlusion regions. Also, the occlusion areas, which are still existence in the merged frame, are interpolated by using the neighboring pixel information and the available data in the occlusion block. In this paper, the experimental results show that the performance of the proposed algorithm has better PSNR and the visual quality than the conventional algorithms.

关键词： Pixel PSNR Interpolation Visualization Motion compensation Algorithm design and analysis Motion estimation

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A fast image registration algorithm for Digital Subtraction Angiography

A fast image registration algorithm for Digital Subtraction ...

引用

Iranian Conference of Biomedical engineering (ICBME)

作者： Mansour Nejati Rassoul Amirfattahi Saeed Sadri Digital Signal Processing Research Laboratory Department of Electrical and Computer Engineering Isfahan University of Technology Isfahan Iran

Digital Subtraction Angiography (DSA) is a powerful technique for the visualization of blood vessels. The major problem encountered in DSA images is the presence of motion artifacts which arise from the misalignment of successive images in the sequence. In this paper, a fast registration algorithm for coronary angiographic images is proposed. It involves a feature-based selection of control points for which the displacement is computed by means of template matching, and the complete displacement vector field is constructed by means of interpolation. To reduce the computational cost of the template matching procedure, an iterative hill-climbing approach is used for optimization and for handling the local misalignments, the image warping is performed based on multilevel B-spline interpolation.

关键词： Image edge detection Artificial neural networks Interpolation Pixel

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A signal perturbation free semi-blind MRT MIMO channel estimation approach

A signal perturbation free semi-blind MRT MIMO channel estim...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Chung Chen Wei-Ping Zhu Qingmin Meng Institute of Signal Processing and Transmission Nanjing University of Posts and Telecommunications Nanjing China Center of Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

In this paper, an efficient signal-perturbation-free semi-blind approach is proposed for flat-fading channel estimation of multiple-input multiple-output (MIMO) systems with maximum ratio transmission (MRT). A novel transmit scheme is developed based on the eigenvalue decomposition of the correlation matrix of the transmitted signal. The new scheme is to send a small volume of data bearing the information of the correlation matrix to the receiver for the cancellation of the signal perturbation error. computer simulations show that the proposed approach significantly outperforms the closed-form semiblind estimation method (CFSB) in terms of the MSE of the beamforming vector estimate.

关键词： MIMO Channel estimation signal processing Array signal processing Matrix decomposition Transmitters Eigenvalues and eigenfunctions computer errors Random variables Receiving antennas

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