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IEEE International Symposium on Biomedical Imaging

作者： Rafal Zdunek Zhaoshui He Andrzej Cichocki Institute of Telecommunications Teleinformatics and Acoustics Wroclaw University of Technology Wroclaw Poland Laboratory for Advanced Brain Signal Processing RIKEN Brain Science Institute Saitama Japan

In tomographic image reconstruction from limited-view projections the underlying inverse problem is ill-posed with the rank-deficient system matrix. The minimal-norm least squares solution may considerably differs from the true solution, and hence a priori knowledge is needed to improve the reconstruction. In our approach, we assume that the true image presents sparse features with uniform spacial smoothness. The sparsity constraints are imposed with the lscr p diversity measure that is minimized with the FOCUSS algorithm. The spacial smoothness is enforced with the adaptive Wiener noise removing implemented in each FOCUSS iterations. The simulation results demonstrate the benefits of the proposed approach.

关键词： Tomography Image reconstruction Wiener filter Focusing Iterative algorithms Inverse problems Least squares methods signal processing algorithms Acoustics Electronic mail

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Naïve Bayes classification of adaptive broadband wireless modulation schemes with higher order cumulants

Naïve Bayes classification of adaptive broadband wireless m...

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International Conference on signal processing and Communication Systems, ICSPCS

作者： M. L. Dennis Wong Sie King Ting Asoke K. Nandi Information and Security Research Laboratory School of Engineering and Science Swinburne University of Technology Sarawak Malaysia Signal Processing and Communication Group University of Liverpool Liverpool UK

Adaptive modulation schemes have been proposed to optimize Shannon's channel capacity in recent orthogonal frequency division multiplexing (OFDM) based broadband wireless standard proposals. By adapting the modulation type (effectively changing the number of bits per symbol) at the transmitter end one can improve the bit error rate (BER) during transmission at designated SNR. blind detection of the transmitted modulation type is desirable to optimise the bandwidth available at the receivers. Hence, there is a need for an intelligent modulation classification engine at the receiver end. In this work, we evaluate some higher order statistical measures coupled with a classical Naive Bayes classifier for fast identification of adaptive modulation schemes. We also benchmark the experimental results with the optimal Maximum Likelihood Classifier, and Support Vector Machine based Classifier using the same feature set.

关键词： OFDM modulation Bit error rate Channel capacity Proposals Transmitters Bit rate Machine intelligence Engines Couplings Maximum likelihood detection

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Cryptanalysis of the Chaotic-based Key Agreement Protocols

Cryptanalysis of the Chaotic-based Key Agreement Protocols

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2008 International Symposium on Biometrics and Security Technologies (ISBAST'08)

作者： Xianfeng Guo Jiashu Zhang College of Computer Science and Technology Southwest University of Nationalities of China Chengdu China Sichuan Key Laboratory of Signal and Information Processing Southwest Jiaotong University Chengdu China

Recently, Han-Chang showed that Xiao-Liao-Deng's key agreement protocol based on chaotic maps is vulnerable to man-in-the-middle attack and proposed two improved schemes. One works in clock synchronization, and the other can work without synchronization. They claimed that their schemes are secure against replaying attacks and can establish a shared session key. However, we point out that all the aforementioned schemes are Non-contributory, i.e. the malicious party can predetermine the shared session key by the vice of several Chebyshev polynomials passing through the same point. In particular, we demonstrate that the asynchronous key agreement protocol can't resist replaying attack. Therefore, the use of these schemes for secure applications may be discouraged.

关键词： Chaos Key agreement Chebyshev Semi-group Property Contributory nature

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TerraSAR-X: Complex Image Inversion for Feature Extraction

TerraSAR-X: Complex Image Inversion for Feature Extraction

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Matteo Soccorsi Mihai Datcu Dusan Gleich German Aerospacec Center Remote Sensing Technology Institute Wessling Germany Laboratory for Signal Processing and Remote Control Faculty of Electrical Engineering and Computer Science University of Maribor Slovenia

In this paper we present two algorithms for information extraction from Single Look Complex (SLC) Synthetic Aperture Radar (SAR) images. The first algorithm is based on Tikhonov regularization with Total Variation (TV) and a Point-Based Feature (PBF) term. Based on the equivalence of Tikhonov and the Bayesian estimate, the second algorithm is a Maximum A Posteriori (MAP) estimation with a complex-valued Gauss-Markov Random Field (GMRF) in addition to the TV prior. The first algorithm produces a despeckled image preserving fine details and texture. The second algorithm gives a denoised image and in addition the estimated feature parameter vector thetas.

关键词： Feature extraction Synthetic aperture radar signal processing algorithms TV Bayesian methods Image restoration Adaptive filters Cost function Anisotropic magnetoresistance Speckle

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A Comprehensive Comparison of Routing Metrics for Wireless Mesh Networks

A Comprehensive Comparison of Routing Metrics for Wireless M...

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IEEE International Conference on Networking, Sensing and Control

作者： Hui Liu Wei Huang Xu Zhou X. H. Wang School of Communication and Information Engineering University of Electronic Science and Technology China National Laboratory of Radar Signal Processing Xidian University Xi'an China Institute of Advanced Telecommunications Swansea University Swansea UK

It is well-known that finding paths with minimum hop count leads to poor performance in wireless mesh networks (WMN) because the assumption of the same transmission failure probability in all links may not be true. A routing metric can assist traditional routing protocol in selecting better paths by explicitly taking the interference, delay etc. into account. This paper presents a thorough review and a comparison of 10 kinds of routing metrics designed for diverse QoS requirements in WMN. Meanwhile, this paper classifies these routing metrics into three basic types, ETX-based metrics, mETX, and some other metrics less attractive to WMN routing layer, for better understanding and future applications. To the best of our knowledge, no paper except this one has such a comprehensive review of routing metrics utilized in WMN.

关键词： Wireless mesh networks Routing protocols Interference Costs Disaster management Electronic mail Delay Intelligent networks technology management Telecommunication traffic

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An algorithm for estimating number of components of Gaussian mixture model based on penalized distance

An algorithm for estimating number of components of Gaussian...

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International Conference on Neural Networks and signal processing

作者： Daming Zhang Hui Guo Bin Luo Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui University of Science and Technology Hefei China Department of Mathematics & Physics Beijing University of Posts and Telecommunications Hefei China University of New South Wales Sydney NSW Australia

ISBN: (纸本)9781424423101

The expectation-maximization (EM) algorithm is a popular approach for parameter estimation of finite mixture model (FMM). A drawback of this approach is that the number of components of the finite mixture model is not known in advance, nevertheless, it is a key issue for EM algorithms. In this paper, a penalized minimum matching distance-guided EM algorithm is discussed. Under the framework of Greedy EM, a fast and accurate algorithm for estimating the number of components of the Gaussian mixture model (GMM) is proposed. The performance of this algorithm is validated via simulative experiments of univariate and bivariate Gaussian mixture models.

关键词： Finite mixture model Number of components Penalized minimum matching distance Greedy EM Parzen window expectation-maximisation algorithm Mixture models Parameter estimation Gauss algorithms Univariate

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Method of image reconstruction based on sub-Gaussian random projection

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2008年第8期45卷 1402-1407页

作者： Fang, Hong Zhang, Quanbing Wei, Sui Key Laboratory of Intelligent Computing and Signal Processing Anhui University Hefei 230039 China College of Science Hefei University of Technology Hefei 230009 China

In this paper, sub-Gaussian random projection is introduced into compressed sensing (CS) theory and two new kinds of CS measurement matrix;sparse projection matrix and very sparse projection matrix are presented. By the tail bounds for sub-Gaussian random projections, the proof of how these new matrices satisfy the necessary condition for CS measurement matrix is provided. Then, it is expatiated that owing to their sparseness, new kinds of matrices greatly simplify the projection operation during image reconstruction, which simultaneously greatly improves the speed of reconstruction. Further, it can be easily proved that Gaussian matrix and Bernoulli matrix are special matrices obeying sub-Gaussian random distribution, which indicates that new measurement matrices extend the current results on CS measurement matrix. Both the results of simulated and real experiments show that with a certain number of measurements, new matrices have good measurement effect and can acquire exact reconstruction. Finally, the comparison and analysis of reconstruction results respectively adopting new matrices and Gaussian measurement matrix is conducted. Compared with Gaussian measurement matrix, new matrices have lesser average over-sampling factor, which indicates lower complexity of reconstruction.

关键词： Compressed sensing

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A dual threshold method to independently control spatial resolution and sensitivity in β imaging

A dual threshold method to independently control spatial res...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： J. Cabello A. Bailey I. Kitchen R. Turchetta K. Wells Centre for Vision Speech and Signal Processing Faculty of Engineering and Physical Sciences University of Surrey Guildford Surrey UK Pharmacology Group Faculty of Health and Medical Sciences University of Surrey Guildford Surrey UK Technology Department Rutherford Appleton Laboratory Science and Technology Facilities Council Didcot Oxfordshire UK

A wide variety of digital alternatives have been presented to replace traditional film emulsion as detection medium in β- Autoradiography. The main claim of most of the alternatives is higher sensitivity. On the other hand, spatial resolution remains the main problem to solve to be able to offer a sensible alternative to film. Solid state detectors, mainly made of silicon, are being used very actively in many disciplines in Medicine and Biology. Spatial resolution is significantly dependant on the pixel size for digital detectors. If charge deposition from impinging β- particles causes cross-talk between neighbour pixels, and accurate charge deposited is measured, sub-pixel resolution can be obtained, therefore potentially obtaining spatial resolution comparable to traditional film. In order to investigate this, a dual threshold approach is presented here, validated with Monte Carlo simulations. Using this approach better charge measurement is obtained, and even some background events are discarded, reducing the global noise level of the detector.

关键词： Spatial resolution Detectors Charge measurement High-resolution imaging Solid state circuits Silicon Biomedical imaging Current measurement Particle measurements Noise level

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Distributed Autocorrelation-Based Sequential Detection of OFDM signals in Cognitive Radios

Distributed Autocorrelation-Based Sequential Detection of OF...

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3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008)

作者： Sachin Chaudhari Visa Koivunen H. Vincent Poor SMARAD CoE Signal Processing Laboratory Helsinki University of Technology Finland School of Engineering and Applied Science Princeton University USA

ISBN: (纸本)9781424423019

This paper addresses the problem of collaborative spectrum sensing using sequential detection (SD) in cognitive radios. The goal of sequential processing is to reduce the delay and amount of data needed in identifying underutilized spectrum. Each secondary user (SU) employs a simple and computationally efficient autocorrelation-based detector for Orthogonal Frequency Division Multiplexing (OFDM) signals of the primary user (PU). The decision statistics from individual detectors are combined in a fusion center that may be a separate node or one of the secondary users. The statistical properties of the decision statistics are established. The performance of the scheme is studied by theory and simulations. A comparison of the SD scheme with the Neyman-Pearson Fixed Sample Size (FSS) test for the same false alarm and missed detection probabilities is also carried out.

关键词： Orthogonal frequency division multiplexing Cognitive radio sequential detection Sequential processes Missed Detection False alarms signals

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Optimized symplectic scheme for electromagnetic simulations

Optimized symplectic scheme for electromagnetic simulations

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Asia-Pacific Conference on Microwave

作者： Bo Wu Zhi-Xiang Huang Wei Sha Ming-Sheng Chen Hong Dai School of physical science and technology Yunnan University China Key Laboratory of Intelligent Computing & Signal Processing Anhui University China Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China Department of Physics and Electronic Engineering Hefei Teachers College China

Classical finite-difference time-domain (FDTD) method has been widely used in computational electromagnetics, but for electrically large domains and for late-time analysis, FDTD method begins to show its limitations due to the accumulation of phase errors. To solve this problem, several methods have been proposed such as high-order schemes and four-stage Runge-Kutta integrator. Recently, the symplectic methods have been adopted for using in computational electromagnetics. In this paper, the concentration is on the derivation of an optimized fourth-order symplectic scheme in electromagnetic simulations.

关键词： Computational modeling Finite difference methods Permittivity Permeability Maxwell equations Electromagnetic propagation Differential equations Optimization methods Physics computing signal processing

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