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检索条件"主题词=detection Algorithms"

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Low-complexity detection and performance in multi-gigabit high spectral efficiency wireless systems

Low-complexity detection and performance in multi-gigabit hi...

引用

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

作者： Saif K. Mohammed A. Chockalingam B. Sundar Rajan Department of ECE Indian Institute of Science Bangalore India

Recently, we reported a low-complexity likelihood ascent search (LAS) detection algorithm for large MIMO systems with several tens of antennas that can achieve high spectral efficiencies of the order of tens to hundreds of bps/Hz. Through simulations, we showed that this algorithm achieves increasingly near SISO AWGN performance for increasing number of antennas in i.i.d. Rayleigh fading. However, no bit error performance analysis of the algorithm was reported. In this paper, we extend our work on this low-complexity large MIMO detector in two directions: i)We report an asymptotic bit error probability analysis of the LAS algorithm in the large system limit, where N t , N r rarr infin keeping N t = N r , where N t and N r are the number of transmit and receive antennas, respectively. Specifically, we prove that the error performance of the LAS detector for V-BLAST with 4-QAM in i.i.d. Rayleigh fading converges to that of the maximum-likelihood (ML) detector as N t ,N r rarr infin keeping N t = N r . ii)We present simulated BER and nearness to capacity results for V-BLAST as well as high-rate non-orthogonal STBC from Division Algebras (DA), in a more realistic spatially correlated MIMO channel model. Our simulation results show that a) at an uncoded BER of 10 -3 , the performance of the LAS detector in decoding 16 times16 STBC from DA with N t = N r =16 and 16-QAM degrades in spatially correlated fading by about 7 dB compared to that in i.i.d. fading, and b) with a rate-3/4 outer turbo code and 48 bps/Hz spectral efficiency, the performance degrades by about 6 dB at a coded BER of 10 -4 . Our results further show that providing asymmetry in number of antennas such that N r > N t keeping the total receiver array length same as that for N r = N t , the detector is able to pick up the extra receive diversity thereby significantly improving the BER performance.

关键词： Detectors Bit error rate MIMO Rayleigh channels Receiving antennas Degradation Fading detection algorithms AWGN Performance analysis

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Efficient Clustering-Based Outlier detection Algorithm for Dynamic Data Stream

Efficient Clustering-Based Outlier Detection Algorithm for D...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Manzoor Elahi Kun Li Wasif Nisar Xinjie Lv Hongan Wang Intelligence Engineering Laboratory Institute of Software of Chinese Academy of Sciences Beijing China Chinese Academy of Sciences Beijing China COMSATS institute of information Technology Islamabad Pakistan

Anomaly detection is currently an important and active research problem in many fields and involved in numerous applications. Most of the existing methods are based on distance measure. But in case of data stream these methods are not very efficient as computational point of view. Most of the exiting work on outlier detection in data stream declare a point as an outlier/inlier as soon as it arrive due to limited memory resources as compared to the huge data stream, to declare an outlier as it arrive often can lead us to a wrong decision, because of dynamic nature of the incoming data. In this paper we introduced a clustering based approach, which divide the stream in chunks and cluster each chunk using k-mean in fixed number of clusters. Instead of keeping only the summary information, which often used in case of clustering data stream, we keep the candidate outliers and mean value of every cluster for the next fixed number of steam chunks, to make sure that the detected candidate outliers are the real outliers. By employing the mean value of the clusters of previous chunk with mean values of the current chunk of stream, we decide better outlierness for data stream objects. Several experiments on different dataset confirm that our technique can find better outliers with low computational cost than the other exiting distance based approaches of outlier detection in data stream.

关键词： detection algorithms Data mining Databases Information technology Nearest neighbor searches Fuzzy systems Data engineering Knowledge engineering Application software Computational efficiency

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Reduced Complexity ML detection for Differential Unitary Space-Time Modulation with Carrier Frequency Offset

Reduced Complexity ML Detection for Differential Unitary Spa...

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IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference

作者： Feifei Gao A. Nallanathan Chintha Tellambura Institute for Infocomm Research Singapore Division of Engineering King''s College London UK Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada

Recently, a maximum likelihood (ML) detection rule for differential unitary space time modulation (DUSTM) under the existence of unknown carrier frequency offset (CFO) has been derived. However, the ML detection is based on the exhaustive search over all the unitary group codes. In this paper, we design an efficient detection algorithm for newly derived ML rule, by modifying the bound intersection detector (BID). Our proposed algorithm is seen as a generalization of the existing BID that is known to be an optimal detector for the conventional DUSTM. The simulation results show that the proposed algorithm can save a large portion of the computational complexity compared to the naive searching method.

关键词： Frequency modulation Detectors Transmitting antennas Maximum likelihood detection Frequency conversion Educational institutions Maximum likelihood estimation Algorithm design and analysis detection algorithms Computational modeling

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A Novel Window-Based Corner detection Algorithm for Gray-Scale Images

A Novel Window-Based Corner Detection Algorithm for Gray-Sca...

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Indian Conference on Computer Vision, Graphics & Image Processing (ICVGIP)

作者： Ambar Dutta Avijit Kar B.N. Chatterji Department of CSE Birla Institute of Technology and Science Kolkata India Department of CSE Jadavpur University Kolkata India Department of ECE B. P. Poddar Institute of Management and Technology Kolkata India

In computer vision, the corners of an object play an important role in shape representation and analysis. In this paper, we describe a new approach to corner detection in a digital image based on the assumption that corners are image points with high information content, and hence corners in an image exist in the regions having considerably high intensity variations. Consequently, a complex corner response function (CRF) is computed only within the regions with considerable high intensity variation instead of entire image reducing the computational cost of the whole procedure. Experiments are conducted with the help of a few images showed the efficiency of the technique, both in terms of execution time and false positive corners.

关键词： detection algorithms Gray-scale Detectors Computer vision Image edge detection Shape Image segmentation Performance evaluation Pixel Image analysis

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Statistical analysis of RR interval irregularities for detection of atrial fibrillation

Statistical analysis of RR interval irregularities for detec...

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Computers in Cardiology (CinC)

作者： A. Ghodrati S. Marinello Draeger Medical Systems Inc. Andover MA USA

We compare two Atrial Fibrillation (AFIB) detection methods from surface ECG, based on RR interval variability in a statistical framework. We obtain the histogram of normalized RR differences for AFIB and non-AFIB episodes using MIT-BIH Arrhythmia database. Two probability density functions (pdf) are employed to model the histograms: Gaussian and Laplace. We then use Neyman-Pearson (NP) detection approach to obtain criteria for AFIB detection. The performance of the two methods is compared using Receiver Operating Curves (ROC) over the different databases. The result shows that the Laplace pdf approximates the histogram of normalized RR differences better than the Gaussian pdf and leads to better AFIB detection performance.

关键词： Statistical analysis Atrial fibrillation Databases Hidden Markov models Histograms Electrocardiography Rail to rail inputs Random variables Patient monitoring detection algorithms

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A novel parallel iterative cycle QR decomposition detection algorithm in VBLAST-OFDM system

A novel parallel iterative cycle QR decomposition detection ...

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IEEE International Symposium on Information (IT) in Medicine and Education, ITME

作者： Yong-jie Li Hong-liang Fu Coll. of Inf. Sci. & Eng. Henan Univ. of Technol. Zhengzhou

A novel parallel iterative cycle QR decomposition detection algorithm in VBLAST-OFDM system is proposed in this paper. In order to overcome the disadvantage of the poor performance of the first detected layer in IQRD algorithm, the parallel detection is applied to the IQRD algorithm and the performance is improved effectively. Simulation results show that the proposed P-IQRD algorithm is superior to the IQRD algorithm.

关键词： detection algorithms Iterative algorithms Transmitting antennas Receiving antennas Frequency-selective fading channels Information science Educational technology OFDM Transmitters Matrix decomposition

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An Adaptive Kernel Method for Anomaly detection in Hyperspectral Imagery

An Adaptive Kernel Method for Anomaly Detection in Hyperspec...

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International Symposium on Intelligent Information Technology Application, IITA

作者： Feng Mei Chunhui Zhao Hanjun Huo Yan Sun College of Information and Communication Engineering Harbin Engineering of Technology Harbin Heilongjiang China College of Electrical & Information Engineering Heilongjiang Institute of Science and Technology Harbin Heilongjiang China

An adaptive kernel method is proposed for anomaly detection in hyperspectral imagery. The conventional RX anomaly detector suffers from high false alarm rates and low probability of detection due to the assumptions that the local background is Gaussian and homogeneous. Many kernel base anomaly detector are of good nonlinear detection performance, but parameter estimation of the kernel function is difficult for these methods. In this paper, we proposed a adaptive parameter estimation method based on the sum of each spectral band standard deviation for the background clutter pixels and applied it in the kernel RX detector. The kernel function parameters estimation can be obtained along with the shifting of the background clutter pixels automatically so we can avoid a large number of experiments for the parameters determination. Numerical experiments are conducted on real hyperspectral imagery collected by the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS). Using receiver operating characteristic (ROC) curves, the results show the improved performance and reduction in the false-alarm rate.

关键词： Kernel Hyperspectral imaging Detectors Hyperspectral sensors Parameter estimation detection algorithms Educational institutions Information technology Adaptive signal detection Signal to noise ratio

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Voice Activity detection Algorithm with Low Signal-to-Noise Ratios Based on Spectrum Entropy

Voice Activity Detection Algorithm with Low Signal-to-Noise ...

引用

International Symposium on Universal Communication, ISUC

作者： Kun-Ching Wang Yi-Hsing Tasi Department of Information Technology & Communication Shih Chien University Taiwan Information & Communications Research Laboratories Industrial Technology and Research Institute Taiwan

This letter presents a robust voice activity detection (VAD) algorithm for detecting voice activity in noisy environments. The presented robust VAD utilizes the entropy measurement defined in band-splitting spectrum domain to exploit the formant frequency representation as a highly efficient, compact representation of the time-varying characteristics of speech. Additionally, Teager energy operator (TEO) can be employed to provide a better representation of formant information resulting in high performance of classification of speech/non-speech priori to entropy-based measurement. The results show that the proposed algorithm has an overall better performance than the standard ITU-T G.729B VAD and Shen's entropy-based VAD.

关键词： detection algorithms Signal to noise ratio Entropy Speech Acoustic noise Frequency measurement Energy measurement Robustness Frequency estimation Information technology

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Breast contour detection with shape priors

Breast contour detection with shape priors

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IEEE International Conference on Image Processing

作者： Ricardo Sousa Jaime S. Cardoso J. F. Pinto da Costa M. J. Cardoso INESC Porto Faculdade de Ciências Universidade do Porto Portugal INESC Porto Faculdade de Engenharia Universidade do Porto Portugal Faculdade de Ciências Universidade do Porto Portugal INESC Porto Faculdade de Medicina Universidade do Porto Portugal

Breast cancer conservative treatment (BCCT) is considered the gold standard of breast cancer treatment. However, aesthetic results are heterogeneous and difficult to evaluate in a standardised way. The limited reproducibility of subjective aesthetic evaluation in BCCT forced the research on objective methods. A recent computer system was developed to objectively and automatically evaluate the aesthetic result of BCCT. In this system, the detection of the breast contour on the digital photograph of the patient is necessary to extract the features subsequently used in the evaluation process. In this paper we extend an algorithm based on the shortest path on a graph to detect automatically the breast contour. The advantage of graph algorithms is that they are guaranteed to find the global optimum of the problem; the difficulty is that they make it hard to enforce shape constraints. We define and compare different techniques to introduce the a priory knowledge of the mammary contour. Experimental results show that the proposed techniques consistently outperform the base method.

关键词： Shape Image edge detection Breast cancer Reproducibility of results Feature extraction Medical treatment Surgery Skin detection algorithms Pixel

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Commentary Paper 1 on "Automatic detection of Adverse Weather Conditions in Traffic Scenes"

Commentary Paper 1 on "Automatic Detection of Adverse Weathe...

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IEEE Conference on Advanced Video and Signal Based Surveillance (AVSS)

作者： Andrea Prati Di.S.M.I. University of Modena and Reggio Emilia and INFM Reggio Emilia Italy

This paper describes two solutions for detecting snow and fog, respectively, in traffic scenes. The former weather condition is detected by modeling the video luminance with a mixture of Gaussians (MoG), while the lat... 详细信息

关键词： Layout Snow Traffic control Videoconference Surveillance Gaussian processes Harmonic analysis detection algorithms Frequency domain analysis Cameras

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