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Novel channel and polarization assignment schemes for 2-11 GHz fixed-broadband wireless access networks

Novel channel and polarization assignment schemes for 2-11 G...

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作者： Ntagkounakis, Konstantinos Sharif, Bayan Dallas, Panagiotis School of Electrical Electronic and Computer Engineering University of Newcastle Mertz Court Newcastle upon Tyne NE1 7RU United Kingdom Emerging Technologies and Markets INTRACOM S.A. 19.5 Km Markopoulou Ave. 19002 Peania Greece University of Newcastle United Kingdom INTRACOM S.A. Department of Communications Signal Processing Research Group School of Electrical Electronic and Computer Engineering IEE INTRACOM Advanced Communications Technologies Branch Emerging Technologies and Markets Department

The scarcity of available spectrum in the 2-11 GHz frequency range and the continuously increasing number of users that require broadband communication services suggest that emerging fixed-broadband wireless access (F-BWA) networks will be deployed with aggressive frequency re-use to cope with capacity demands. In this context, co-channel interference may arise in high levels compromising the system's capacity and robust operation. Interference is further increased when limited directionality terminal antennas are employed to support non line-of-sight operation and in the case where an adaptive-time division duplex is selected for efficient radio resource management in asymmetric and time-varying traffic conditions. In this paper frequency channel assignment (CA) and antenna polarization assignment (PA) are considered as a means of mitigating interference. Two novel CA schemes that consider the distinct characteristics of F-BWA are proposed;the rotated-interleaved channel assignment and the non-uniform channel assignment. According to statistical interference simulation analysis the proposed schemes are more efficient in suppressing interference, achieving higher capacity compared to existing schemes while incurring no further complexity. In addition, instead of exploiting the performance of CA and PA schemes independently a framework for a joint CA-PA consideration is presented, where for a particular CA scheme an optimized PA pattern is developed. Results show that this approach improves the CA-PA interoperability increasing the overall performance. The efficiency of the proposed schemes is investigated for both FDD and adaptive-TDD schemes and is verified for various sectorization, frequency re-use and terminal antenna directivity configurations to ensure compatibility with different deployment scenarios. © Springer 2006.

关键词： Wireless telecommunication systems

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Cardiovascular signal Decomposition and Estimation with the Extended Kalman Smoother

Cardiovascular Signal Decomposition and Estimation with the ...

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

作者： James McNames Mateo Aboy Biomedical Signal Processing Laboratory Department of Electrical and Computer Engineering Portland State University Portland OR USA Oregon Institute of Technology Beaverton OR USA Biomedical Signal Processing Laboratory Portland State University USA

Cardiovascular signals such as arterial blood pressure (ABP), pulse oximetry (S p O 2 ), and central venous pressure (CVP) contain useful information such as heart rate, respiratory rate, and pulse pressure variation (PPV). We present a statistical state-space model of cardiovascular signals that can be used with the extended Kalman filter or smoother to simultaneously estimate and track many cardiovascular parameters of interest. We demonstrate the algorithm's tracking capabilities with a real ABP signal

关键词： Cardiology signal resolution Kalman filters State estimation Frequency estimation Power harmonic filters Heart rate signal processing algorithms Amplitude modulation Pulse modulation

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Analysis of P300 Classifiers in Brain computer Interface Speller

Analysis of P300 Classifiers in Brain Computer Interface Spe...

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

作者： H. Mirghasemi R. Fazel-Rezai M. B. Shamsollahi BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran Brain Image and Signal Processing BISP Laboratory Department of Electrical and Computer Engineering University of Manitoba Winnipeg MAN Canada

In this paper, the performance of five classifiers in P300 speller paradigm are compared. Theses classifiers are Linear Support Vector Machine (LSVM), Gaussian Support Vector Machine (GSVM), Neural Network (NN), Fisher Linear Discriminant (FLD), and Kernel Fisher Discriminant (KFD). In classification of P300 waves, there has been a trend to use SVM classifiers. Although they have shown a good performance, in this paper, it is shown that the FLD classifiers outperform the SVM classifiers. FLD classifier uses only ten channels of the recorded electroencephalogram (EEG) signals. This makes them a very good candidate for real-time applications. In addition, FLD approach does not need any optimization similar to other methods. In addition, in this paper, it is shown that the efficiency of using Principal Component Analysis (PCA) for feature reduction results in decreasing the time for the classification and increasing the accuracy

关键词： Brain computer interfaces Electroencephalography Support vector machines Support vector machine classification Principal component analysis Band pass filters Digital filters computer interfaces Cities and towns USA Councils

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Adaptive Steganographic System for Binary Images using Variable Block Embedding Rate

Adaptive Steganographic System for Binary Images using Varia...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Sos. S. Agaian Ravindranath C. Cherukuri Mobile and Multimedia Signal processing Laboratory Department of Electrical and Computer Engineering University of Texas San Antonio San Antonio TX USA

Due to the rapid developments in multimedia, the demand for binary media (such as signatures, scanned documents and images) based steganographic system has enhanced. In this paper, we present a new data-hiding system that could hide considerable amount of data into a binary digital media. The system modifies the maximum flippable pixels in each block based on certain statistics constraints and characteristic measure of the block. Thus equalizing, the uneven distribution of the flippable pixels through out the embeddable image blocks. We also discuss various issues surrounding the variable block embedding rate and the solution to those issues to make it feasible. The embedded information can be reconstructed without prior knowledge of the cover. The performance of the proposed embedding system with respect to the security and robustness is also discussed. Comparisons with the commonly used embedding systems are also presented for maximum capacity and visual distortion.

关键词： Adaptive systems Steganography Pixel Data security Mobile computing Digital signal processing Laboratories Electronic mail Mobile communication Data encapsulation

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Iterative Channel Estimation for Multiuser OFDM Systems in the Presence of Power Amplifier Nonlinearities

Iterative Channel Estimation for Multiuser OFDM Systems in t...

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IEEE International Symposium on Personal, Indoor and Mobile Radio communications (PIMRC)

作者： Fernando H. Gregorio Stefan Werner Juan E. Cousseau Timo I. Laakso Signal Processing Laboratory Helsinki University of Technology Finland Department of Electrical and Computer Engineering Universidad Nacional del Sur Bahia Blanca Argentina

This paper proposes a new channel estimation approach for MIMO-OFDM systems subject to power amplifier nonlinearities. The harmful effect of nonlinear distortion on the system performance can be reduced by applying an iterative distortion cancellation technique. However, such an approach requires accurate channel estimates to yield good performance. In our approach, initial channel estimation is carried out in frequency domain (FD) followed by time domain (TD) processing of the received signal. In the TD step, the equalized signals from the FD processing is used to remove the nonlinear distortion and to improve the initial channel estimate. Simulations verify that the combined channel estimation and nonlinear cancellation strategy has a performance close to the case of perfectly known channel. Furthermore, a substantial improvement in the system performance is achieved with the proposed technique when compared with conventional methods in terms of mean square error and BER

关键词： Channel estimation OFDM Power amplifiers Nonlinear distortion System performance signal processing Yield estimation Frequency domain analysis Mean square error methods Bit error rate

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Assessment of Preprocessing on Classifiers Used in the P300 Speller Paradigm

Assessment of Preprocessing on Classifiers Used in the P300 ...

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

作者： H. Mirghasemi M. B. Shamsollahi R. Fazel-Rezai BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran BDP laboratory Department of Electrical Engineering Sharif University of Technology Tehran Iran Department of Electrical and Computer Engineering Brain Image and Signal Processing Laboratory University of Manitoba Winnipeg MAN Canada

Artifact removal is an essential part in electroencephalogram (EEG) recording and the raw EEG signals require preprocessing before feature extraction. In this work, we implemented three filtering methods and demonstrated their effects on the performance of different classifiers. Bandpass digital filtering, median filtering and facet method are three preprocessing approaches investigated in this paper. We used data set lib from the BCI competition 2003 for training and testing phase. Our accuracy varied between 80% and 96%. In our work, we demonstrated that the problems of choosing the classifier and preprocessing methods are not independent of each other. Two of our approaches could achieve the 96% accuracy i.e. 31 of 32 characters were predicted correctly. These two approaches have different classifier and different preprocessing method. It means that the performance of each classifier can be enhanced with a specific preprocessing method. In our approach, we used only three electrodes of 64 applied electrodes. Therefore it can noticeably reduce the time and cost of EEG measurement

关键词： Electroencephalography Band pass filters Filtering Electrodes Testing Noise reduction Feature extraction Principal component analysis Digital filters Cities and towns

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Support Vector Clustering Applied to Digital communications

Support Vector Clustering Applied to Digital Communications

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International Joint Conference on Neural Networks (IJCNN)

作者： C.A.M. Lima R. Ferrari H. Knidel C. Junqueira R.R.F. Attux J.M.T. Romano F.J. Von Zuben Laboratory of Bioinformatics and Bio-inspired Computing (LBiC) School of Electrical and Computer Engineering (FEEC) State University of Campinas-UNICAMP Sao Paulo Brazil Laboratory of Signal Processing for Communications (DSPCom) School of Electrical and Computer Engineering (FEEC) State University of Campinas-UNICAMP Sao Paulo Brazil

Support vector clustering (SVC) is a recently proposed clustering methodology with promising performance for high-dimensional and noisy datasets, and for clusters with arbitrary shape. This work addresses the application of SVC, a kernel-based method, in a context in which the channel equalization problem is conceived as a clustering task. The main challenge, in this case, is to perform unsupervised clustering aiming at the design of an optimal Bayesian or a blind prediction-based receiver without resorting to a priori information about the transmission medium. The proposed technique employs a two-stage procedure -a combination between the use of SVC to obtain a first set of clusters and an auxiliary heuristic to help separating eventual multiple clouds contained in a single cluster and attribute centers to them via an iterated local search (ILS) algorithm. The obtained results indicate that kernel methods can be successfully applied to the field of signal processing.

关键词： Digital communication Static VAr compensators signal processing algorithms Noise shaping Shape Context Bayesian methods Clouds Clustering algorithms Kernel

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A Hybrid Unsupervised Clustering Algorithm for Channel Equalization

A Hybrid Unsupervised Clustering Algorithm for Channel Equal...

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IEEE Workshop on Machine Learning for signal processing

作者： Helder Knidel Rafael Ferrari Leonardo T. Duarte Ricardo Suyama Romis R. F. Attux Leandro Nunes De Castro Fernando Jose Von Zuben Joao Marcos T. Romano Laboratory of Bioinformatics and Bio-inspired Computing (LBiC)-School of Electrical and Computer Engineering (FEEC) State University of Campinas-UNICAMP Sao Paulo Brazil Laboratory of Signal Processing for Communications (DSPCom)-School of Electrical and Computer Engineering (FEEC) State University of Campinas-UNICAMP Sao Paulo Brazil Catholic University of Santos Sao Paulo Brazil

In this work, we propose and analyze the applicability of a novel unsupervised data clustering technique in the problem of channel equalization. The proposal combines two different methods, a neuro-immune network called RABNET [1] and the iterated local search algorithm (ILS) [2], to produce a tool that, in contrast to classical solutions like the k-means algorithm, does not require a priori knowledge about the number of clusters to be found and, moreover, possesses mechanisms to avoid local convergence. Simulation results attest both the viability and efficiency of the proposal in scenarios conceived to highlight certain aspects that can be decisive insofar as real-world applications are concerned.

关键词： Clustering algorithms Bayesian methods signal processing algorithms Laboratories Data engineering Proposals Blind equalizers Bioinformatics Biomedical signal processing signal analysis

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Rate-Distortion Optimized Image Compression Using Generalized Principal Component Analysis

Rate-Distortion Optimized Image Compression Using Generalize...

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

作者： Dohyun Ahn Chang-Su Kim Sang-Uk Lee Signal Processing Laboratory School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea Department Electronics Eng. Korea University Seoul South Korea

A novel image compression algorithm based on generalized principal component analysis (GPCA) is proposed in this work. Each image block is first classified into a subspace and is represented with a linear combination of the basis vectors for the subspace. Therefore, the encoded information consists of subspace indices, basis vectors and transform coefficients. We adopt a vector quantization scheme and a predictive partial matching scheme to encode subspace indices and basis vectors, respectively. We also propose a rate-distortion optimized quantizer to encode transform coefficients efficiently. Simulation results demonstrate that the proposed algorithm provides better compression performance than JPEG, especially at low bitrates

关键词： Rate-distortion Image coding Principal component analysis Clustering algorithms signal processing algorithms Vector quantization Bit rate Entropy computer science Transform coding

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FPGA implementation of point multiplication on Koblitz curves using kleinian integers 1

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8th International Workshop on Cryptographic Hardware and Embedded Systems, CHES 2006

作者： Dimitrov, V.S. Järvinen, K.U. Jacobson Jr., M.J. Chan, W.F. Huang, Z. Department of Electrical and Computer Engineering University of Calgary 2500 University Drive NW Calgary Alta. T2N 1N4 Canada Signal Processing Laboratory Helsinki University of Technology Otakaari 5A 02150 Espoo Finland Department of Computer Science University of Calgary 2500 University Drive NW Calgary Alta. T2N 1N4 Canada

ISBN: (数字)9783540465614

ISBN: (纸本)3540465596

We describe algorithms for point multiplication on Koblitz curves using multiple-base expansions of the form k = Σ±τa(τ - 1)b and k = Σ±τa(τ - 1) b(τ2 - τ -1)c. We prove that the number of terms in the second type is sublinear in the bit length of k, which leads to the first provably sublinear point multiplication algorithm on Koblitz curves. For the first type, we conjecture that the number of terms is sublinear and provide numerical evidence demonstrating that the number of terms is significantly less than that of τ-adic non-adjacent form expansions. We present details of an innovative FPGA implementation of our algorithm and performance data demonstrating the efficiency of our method. © International Association for Cryptologic Research 2006.

关键词： Field programmable gate arrays

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