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International Conference on Intelligent and Advanced Systems, ICIAS

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

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-nearest-neighbor 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： Clustering algorithms Algorithm design and analysis Correlation Approximation methods Independent component analysis Time series analysis Approximation algorithms

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A new improved model-based seizure detection using statistically optimal null filter

A new improved model-based seizure detection using statistic...

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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 (CENSIPCOM) Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

A patient-specific model-based seizure detection method using statistically optimal null filters (SONF) has been recently proposed to aid the review of long-term EEG [1, 2]. The method relies on the model of a priori known seizure (template pattern) for subsequent detection of similar seizures. Artifacts, non-epileptic EEG rhythms, and at times modeling errors lead to increased false or missed detections. In this paper, we present a new improved model-based seizure detection that introduces a pre-processing block for artifact rejection, an adaptive technique of modeling the template patterns, and a new evolution-based classifier. The proposed classifier tracks the temporal evolution of seizure to improve the classification accuracy. With the help of simulated EEG, we illustrate the significance and need for these modifications. Further, performance of the complete algorithm is tested on single channel depth EEG of seven patients, and compared with the previous approaches. In terms of sensitivity and specificity, the proposed method resulted in 84% and 100%, method of 65% and 84%, and method of, 84% and 90% respectively. An overall performance improvement is seen as enhanced detection sensitivity and reduced false positives. This is preliminary result on seven patient data.

关键词： Electroencephalography Brain modeling Rhythm Filters Monitoring Epilepsy Sampling methods Frequency USA Councils Testing

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Editorial

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Multidimensional Systems and signal processing 2008年第2期19卷 171-172页

作者： N. K. Bose The Spatial & Temporal Signal Processing Center Department of Electrical Engineering The Pennsylvania State University University Park USA

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The extended invariance principle applied to joint time-delay, frequency, and DOA estimation

The extended invariance principle applied to joint time-dela...

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Felix Antreich Josef A. Nossek Gonzalo Seco A. Lee Swindlehurst Institute for Communications and Navigation German Aerospace Center Wessling Germany Institute for Circuit Theory & Signal Processing Munich University of Technology Germany Department of Telecommunications & Systems Engineering Universitat Autonoma de Barcelona Spain Department of Electrical Engineering & Computer Science University of California Irvine CA USA

This paper deals with the joint estimation of temporal (time- delay, Doppler frequency) and spatial (direction-of-arrival, DOA) parameters of several replicas of a known signal in an unknown spatially correlated field. Unstructured and structured models have been proposed in the literature. The former suffers from a severe performance degradation in some scenarios, whereas the latter involves huge complexity. It is shown how the extended invariance principle (EXIP) can be applied to obtain estimates with the quality of those of the structured model, but with the complexity of the unstructured one. We present a method to improve the quality of the time- delay and Doppler estimates obtained with an unstructured spatial model when an estimate of the DOAs is available. Exemplarily, simulation results for time-delay estimation for GPS (global positioning system) are included and confirm that our proposal approaches the Cramer-Rao lower bound (CRLB) of the structured model even when suboptimal DOA estimates obtained by ESPRIT are introduced.

关键词： Frequency estimation Direction of arrival estimation Global Positioning System Delay estimation Data models Sensor arrays signal processing Gaussian noise Aerospace engineering Navigation

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Time delay estimation in a spatially structured model using decoupled estimators for temporal and spatial parameters

Time delay estimation in a spatially structured model using ...

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ITG Workshop on Smart Antennas

作者： Felix Antreich Josef A. Nossek Gonzalo Seco A. Lee Swindlehurst German Aerospace Center (DLR) Inst. for Communications and Navigation Wessling Germany Inst. for Circuit Theory & Signal Processing Munich University of Technology (TUM) Germany Department of Telecommunication & Systems Engineering Universitat Authnòma de Barcelona Spain Dept. of Telecommunications & Systems Engineering Universitat Autonoma de Barcelona (UAB) Spain Dept. of Electrical Engineering & Computer Science The University of California Irvine CA U.S.A.

This paper deals with the joint estimation of time-delay and spatial (direction-of-arrival, DOA) parameters of several replicas of a known signal in an unknown spatially correlated field. Unstructured and structured models have been proposed for maximum likelihood (ML) estimators in the literature. The former suffers from a severe performance degradation in some scenarios, whereas the latter involves huge complexity. It is shown how the extended invariance principle (EXIP) can be applied to obtain estimates with the quality of those of the structured model, but with the complexity of the unstructured one. We present a method to improve the quality of the time-delay estimates obtained with an unstructured spatial model when an estimate of the DOAs is available. Exemplarily, simulation results for time-delay estimation for GPS (Global Positioning System) are included and confirm that our proposal approaches the Cramer-Rao lower bound (CRLB) of the structured model even when suboptimal DOA estimates obtained by ESPRIT are introduced.

关键词： Delay estimation Delay effects

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Enhanced Biggs-Andrews asymmetric iterative blind deconvolution

Enhanced Biggs-Andrews asymmetric iterative blind deconvolut...

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作者： Chappalli, Mahesh B. Bose, N.K. Spatial and Temporal Signal Processing Center Department of Electrieal Engineering Pennsylvania State University University Park PA 16802 United States Department of Electrical Engineering Pennsylvania State University University Park Digital Media Solutions Laboratory Samsung Information Systems America Irvine CA Video Group Ittiam Systems Pvt. Ltd. Bangalore India

The main contribution of this paper is the introduction of a framework for estimation of multiple unknown blurs as well as their respective supports. Specifically, the Biggs-Andrews (B-A) multichannel iterative blind deconvolution (1BD) algorithm is modified to include the blur support estimation module and the asymmetry factor for the Richardson-Lucy (R-L) update-based IBD algorithm is calculated, A computational complexity assessment of the implemented modified IBD is made. Simulations conducted on real-world and synthetic images confirm the importance of accurate support estimation in the blind superresolution problem.

关键词： Iterative methods

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On the Sum-Rate of Broadcast Channels with Outdated 1-Bit Feedback

On the Sum-Rate of Broadcast Channels with Outdated 1-Bit Fe...

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Asilomar Conference on signals, Systems & computers

作者： Bo Niu Osvaldo Simeone Oren Somekh Alexander M. Haimovich Center for Wireless Communications and Signal Processing Research Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

In this paper, a single-input single-output (SISO) downlink channel with K users is analyzed in the presence of Rayleigh flat fading. A limited channel state information (CSI) feedback scheme is considered, where only an outdated 1-bit feedback per user is available at the base station for each fading block. A closed-form expression for the achievable ergodic sum- rate of the 1-bit feedback scheme is presented for any number of users, as a function of the fading temporal correlation coefficient, the threshold of the 1-bit CSI quantizer and the SNR. It is proved that the sum-rate scales with increasing number of users as log log K, which is the same scaling law achieved by the optimal non-delayed full CSI feedback scheme. In addition, the sum-rate degradation due to outdated CSI is evaluated in the asymptotic regimes of either large K or low SNR.

关键词： Broadcasting Feedback Fading Base stations Delay Rayleigh channels Downlink Degradation Feeds Optimal scheduling

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A factorization procedure for FIR paraunitary matrices

A factorization procedure for FIR paraunitary matrices

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2005 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP '05

作者： Lannes, Sarah Bose, N.K. Spatial and Temporal Signal Processing Center Department of Electrical Engineering Pennsylvania State University University Park PA 16802 United States

ISBN: (纸本)0780388747

A constructive factorization procedure for a polynomial paraunitary matrix as a product of atomic paraunitary matrices, each of lowest degree is given. The generic form of these paraunitary factors results from the use of projection matrices. In the univariate case each factor is of degree 1. In the multivariate case the generic factor is constructed based on the assumption of its existence. © 2005 IEEE.

关键词： FIR filters

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A factorization procedure for FIR paraunitary matrices

A factorization procedure for FIR paraunitary matrices

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： S. Lannes N.K. Bose The Spatial and Temporal Signal Processing Center Department of Electrical Engineering Pennsylvania State University University Park PA USA

A constructive factorization procedure for a polynomial paraunitary matrix as a product of atomic paraunitary matrices, each of lowest degree, is given. The generic form of these paraunitary factors results from the use of projection matrices. In the univariate case, each factor is of degree 1. In the multivariate case, the generic factor is constructed based on the assumption of its existence.

关键词： Finite impulse response filter Matrix decomposition Polynomials signal processing Arithmetic Filter bank Lattices

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ATOMIC FACTORIZATION PROBLEM FOR BIVARIATE PARAUNITARY MATRICES AND CONSEQUENCES

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IFAC Proceedings Volumes 2005年第1期38卷 43-46页

作者： N.K. Bose HRB-Systems Professor Spatial and Temporal Signal Processing Center Department of Electrical Engineering The Pennsylvania State University University Park PA 16802 U.S.A.

The property of losslessness, embraced by systems characterized by paraunitary matrices is crucial in robust design and numerical analysis of such systems. Here the paraunitary constraint is imposed on the bivariate polynomial matrix factorization algorithm of Guiver and Bose (1982), and an atomic factor ization problem is formulated to relate the existing results and get new results.

关键词： Paraunitary matrices Robust multidimension systems bivariate polynomial matrix factorization

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