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IEEE International Conference on RFID

作者： G. Matthew Ezovski Steve E. Watkins Adaptive Communications and Signal Processing Group Electrical and Computer Engineering Cornell University Ithaca NY USA Department of Electrical and Computer Engineering University of Missouri Rolla Rolla MO USA

ISBN: (纸本)1424410126;1424410134

Passports and other identification documents may be enhanced using recent advancements in technology. Various national and international bodies are pursuing machine-readable approaches with biometric information. In particular, the international civil aviation organization (ICAO) has adopted standards whereby passports can store biometric identifiers. Countries that participate in the visa waiver program (VWP) began issuing electronic passports in 2006. However, the selection of technologies remains questionable due to privacy and security concerns. This paper examines policy regarding these electronic approaches and developments toward electronic data storage and transmission. Radio-frequency identification (RFID) devices for electronic passports and other existing identity documents are discussed.

关键词： Radiofrequency identification Terrorism Biometrics Standards organizations Integrated circuit technology Privacy Data security Radio frequency National security Pipelines

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Carrier frequency offset estimation and I/Q imbalance compensation for OFDM systems

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Eurasip Journal on Advances in signal processing 2007年 2007卷

作者： Yan, Feng Zhu, Wei-Ping Ahmad, M. Omair Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal Que. H3G 1M8 Canada

Two types of radio-frequency front-end imperfections, that is, carrier frequency offset and the inphase/quadrature (I/Q) imbalance are considered for orthogonal frequency division multiplexing (OFDM) communication systems. A preamble-assisted carrier frequency estimator is proposed along with an I/Q imbalance compensation scheme. The new frequency estimator reveals the relationship between the inphase and the quadrature components of the received preamble and extracts the frequency offset from the phase shift caused by the frequency offset and the cross-talk interference due to the I/Q imbalance. The proposed frequency estimation algorithm is fast, efficient, and robust to I/Q imbalance. An I/Q imbalance estimation/compensation algorithm is also presented by solving a least-square problem formulated using the same preamble as employed for the frequency offset estimation. The computational complexity of the I/Q estimation scheme is further reduced by using part of the short symbols with a little sacrifice in the estimation accuracy. computer simulation and comparison with some of the existing algorithms are conducted, showing the effectiveness of the proposed method.

关键词： Orthogonal frequency division multiplexing

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Blind Extraction of Microsleep Events

Blind Extraction of Microsleep Events

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International Conference on Digital signal processing (DSP)

作者： Wai Yie Leong Danilo P. Mandic Martin Golz David Sommer Communications and Signal Processing Group Electronics and Electrical Engineering Imperial College London UK Department of Computer Science University of Applied Sciences Schmalkalden Schmalkalden Germany

The aim of this study is to detect the occurrence of microsleep events in an overnight driving task. We propose a biosignal analysis method for the detection and extraction of microsleep events. This is achieved by employing blind source extraction method based on a cascaded nonlinear estimator to extract the relevant microsleep events. The cascaded nonlinear estimator jointly estimates the kurtosis and measure the nonlinearity and noise effects within the biosignal. This proposed method was applied to the electroencephalogram and electroculogram recorded of 12 young volunteers while performing monotonic overnight driving in a real car driving simulation laboratory. The extracted microsleep signals can then be used for driving simulation pilot studies for alertness monitoring, and to trigger the activation of alertness countermeasures.

关键词： Brain modeling Electroencephalography Detectors Event detection State estimation Diseases Data mining Fatigue Electrooculography Magnetic heads

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A New Vector Sensor Receiver for Underwater Acoustic Communication

A New Vector Sensor Receiver for Underwater Acoustic Communi...

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2007 OCEANS, vol.2

作者： Ali Abdi Huaihai Guo Patchara Sutthiwan Center of Wireless Communication and Signal Processing Research Electrical and Computer Engineering Department New Jersey Institute of Technology Newark NJ USA

ISBN: (纸本)9780933957374

In this paper we have shown that by taking advantage of the acoustic particle velocity, in addition to the acoustic pressure, multichannel reception can be accomplished in underwater channels. Theoretical formulation and Monte Carlo simulations are provided for a vector sensor equalizer that measures the pressure and the velocity at a single point in space. These results demonstrate the usefulness of a compact vector sensor as a multichannel equalizer.

关键词： Underwater communication Acoustic vector sensor Acoustic communication Multichannel equalization Acoustic particle velocity

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A new segmentation algorithm combined with transient frames power for text independent speaker verification

A new segmentation algorithm combined with transient frames ...

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2007 IEEE International Conference on Acoustics, Speech and signal processing, ICASSP '07

作者： Saeidi, R. Sadegh Mohammadi, H.R. Rodman, R.D. Kinnunen, T. Research Center for Intelligent Signal Processing Shariati Ave. Tehran Iran Iranian Research Institute for Electrical Engineering Narmak Tehran Iran Department of Computer Science North Carolina State University Raleigh NC 27695-8206 United States Institute for Infocomm Research Singapore Singapore

ISBN: (纸本)1424407281

In this paper we propose a new segmentation algorithm called Delta MFCC based Speech Segmentation (DMFCC-SS), with application to speaker recognition systems. We show that DMFCC-SS can separate the regions of speech that result from similar likelihood scores using models such as a Gaussian Mixture Model (GMM), and can therefore be used to identify the regions of speech between two transitional states in a speech signal. By combining this segmentation algorithm with the discriminative power of transient frames in speaker recognition, we can investigate the tradeoff in speed-up rates that result from DMFCC-SS, with speaker verification equal error rates that result from representatives of each segment. We use a Universal Background Model - Gaussian Mixture Model (UBM-GMM) as a baseline system. The proposed speed-up algorithm, working in the pre-processing stage, performs well while having no computational load compared to the main GMM system. Experimental results show the superior performance of this pre-processing method in comparison with other algorithms working in the pre-processing stage of a UBM-GMM system. © 2007 IEEE.

关键词： Speech recognition

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Combined inter-frame and intra-frame fast scoring methods for efficient implementation of GMM-based speaker verification systems

Combined inter-frame and intra-frame fast scoring methods fo...

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2007 IEEE International Conference on Acoustics, Speech and signal processing, ICASSP '07

作者： Sadegh Mohammadi, H.R. Saeidi, R. Rohani, M.R. Rodman, R.D. Iranian Research Institute for Electrical Engineering No. 166 Heidarkhani Ave. Narmak Tehran Iran Research Center of Intelligent Signal Processing Shariati Ave. Tehran Iran Department of Computer Science North Carolina State University Raleigh NC 27695-8206 United States

ISBN: (纸本)1424407281

In this paper a new inter-frame fast scoring scheme is proposed for Gaussian mixture model universal background model (GMM-UBM) speaker verification systems. It is combined with a recently introduced intra-frame efficient scoring method called the sorted Gaussian mixture model (SGMM) classifier which itself uses a sorted UBM known as the sorted background model (SBM). To enhance the performance of the system a GMM identifier is applied as a post-processing block. Experimental results show that the performance of this combined method compares favorably with the baseline GMM-UBM system, while the computational load of the proposed system is greatly less than that of the baseline system. © 2007 IEEE.

关键词： Speech intelligibility

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Data-Dependent Superimposed Training for Noncoherent Channels

Data-Dependent Superimposed Training for Noncoherent Channel...

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Asilomar Conference on signals, Systems & computers

作者： Jingnong Yang Douglas B. Williams John M. Cioffi Amicus Wireless Technology Sunnyvale CA USA Center for Signal and Image Processing School of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Electrical Engineering University of Stanford Stanford CA USA

This paper focuses on noncoherent coding design for fast fading channels, where the receiver does not have reliable channel state information. Unitary space-time codes and training based schemes have been proposed historically. We propose a data-dependent superimposed training scheme to improve the performance of training based codes. The transmitter is equipped with multiple training sequences and dynamically selects a training sequence for each data sequence to minimize channel estimation error. The set of training sequences are optimized to minimize pairwise error probability between codewords.

关键词： Fading Transmitters Channel estimation Transmitting antennas Paper technology Image coding Space time codes Decoding Additive white noise AWGN

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Time-frequency analysis of heart rate variability for neonatal seizure detection

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Eurasip Journal on Advances in signal processing 2007年 2007卷

作者： Malarvili, M.B. Mesbah, Mostefa Boashash, Boualem Perinatal Research Centre School of Medicine University of Queensland Herston QLD 4029 Australia Signal Processing Research Center Department of Electrical and Computer Engineering College of Engineering P.O. Box 27272 Sharjah United Arab Emirates

There are a number of automatic techniques available for detecting epileptic seizures using solely electroencephalogram (EEG), which has been the primary diagnosis tool in newborns. The electrocardiogram (ECG) has been much neglected in automatic seizure detection. Changes in heart rate and ECG rhythm were previously linked to seizure in case of adult humans and animals. However, little is known about heart rate variability (HRV) changes in human neonate during seizure. In this paper, we assess the suitability of HRV as a tool for seizure detection in newborns. The features of HRV in the low-frequency band (LF: 0.03-0.07 Hz), mid-frequency band (MF: 0.07-0.15 Hz), and high-frequency band (HF: 0.15-0.6 Hz) have been obtained by means of the time-frequency distribution (TFD). Results of ongoing time-frequency (TF) research are presented. Based on our preliminary results, the first conditional moment of HRV which is the mean/central frequency in the LF band and the variance in the HF band can be used as a good feature to discriminate the newborn seizure from the nonseizure.

关键词： signal detection

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Combined Inter-Frame and Intra-Frame Fast Scoring Methods for Efficient Implementation of GMM-Based Speaker Verification Systems

Combined Inter-Frame and Intra-Frame Fast Scoring Methods fo...

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

作者： H. R. Sadegh Mohammadi R. Saeidi M. R. Rohani R. D. Rodman Iranian Research Institute of Electrical Engineering Tehran Iran Research Center for Intelligent Signal Processing Tehran Iran Department of Computer Science North Carolina State University Raleigh NC USA

关键词： Computational efficiency Degradation Optimization methods Speech System testing signal processing computer science Computational complexity Intelligent structures Support vector machines

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An ARMA System Identification Scheme in the Presence of Noise

An ARMA System Identification Scheme in the Presence of Nois...

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IEEE North-East Workshop on Circuits and Systems (IEEE-MWCAS'07)

作者： S. A. Fattah W. P. Zhu M. O. Ahmad Centre for Signal Processing and Communications Department of Electrical and Computer Engineering Concordia University Montreal QUE Canada

This paper presents a scheme for the identification of minimum-phase autoregressive moving average (ARMA) systems in the presence of noise. For the identification of the AR part, we propose to repeat the correlation operation on an enhanced autocorrelation function of the observed signal based on a decision criterion and then employ the resultant to an extended form of Yule-Walker equations. A frequency domain noise-compensation scheme is introduced which operates on the noise-contaminated residual signal. The MA parameters are then estimated via the spectral factorization performed on the power spectrum of the noise-compensated residual signal. computer simulations exhibit a superior estimation performance even at low levels of signal-to-noise ratio (SNR).

关键词： System identification Working environment noise signal processing Equations Frequency domain analysis Parameter estimation Autocorrelation signal to noise ratio Noise reduction signal processing algorithms

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