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检索条件"主题词=detection algorithms"

共 7380 条记录，以下是31-40 订阅

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Novel SISO detection algorithms for Nonlinear Satellite Channels

Novel SISO Detection Algorithms for Nonlinear Satellite Chan...

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54th Annual IEEE Global Telecommunications Conference (GLOBECOM)

作者： Colavolpe, Giulio Piemontese, Amina Univ Parma Dipartimento Ingn Informaz Viale GP Usberti 181-A I-43100 Parma Italy

ISBN: (纸本)9781424492688

We propose novel detection algorithms for linear modulations transmitted over nonlinear satellite channels, also impaired by additive white Gaussian noise. These algorithms are derived by using a Volterra-series expansion of the useful signal and by applying the sum-product algorithm to a suitably-designed factor graph. Being soft-input soft-output (SISO) in nature, the proposed detectors can be adopted in turbo processing without additional modifications. Typical linear modulations employed in satellite transmissions are considered in the numerical results. When compared with the optimal detection algorithm for these channels, whose complexity is exponential in the channel memory, the proposed schemes result very appealing in terms of tradeoff between performance and computational complexity. Particularly, the proposed schemes can approach the optimal performance with a complexity only linear in the channel memory.

关键词： Complexity theory detection algorithms Detectors Gaussian noise Gaussian noise Phase shift keying SISO detection algorithms Satellite broadcasting Satellites Volterra equations Volterra-series expansion channel memory computational complexity computational complexity linear modulations nonlinear satellite channels optimal detection algorithm optimisation satellite communication satellite transmissions soft-input soft-output detection algorithm suitably-designed factor graph sum-product algorithm turbo processing wireless channels

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The Analysis of detection algorithms in UWB Spatial Multiplexing System

The Analysis of Detection Algorithms in UWB Spatial Multiple...

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2nd International Conference on Instrumentation and Measurement, Computer, Communication and Control (IMCCC)

作者： Wu Xuan-li Sun Lu-kuan Wang Ruo-nan Harbin Inst Technol Sch Elect & Informat Engn Harbin 150006 Peoples R China Harbin Inst Technol Sch Foreign Languages Harbin 150006 Peoples R China

ISBN: (纸本)9780769549354

In order to satisfy the requirement for higher data rates, the UWB spatial multiplexing system that combines MB-OFDM UWB and V-BLAST scheme is presented in this paper. And then, various detection algorithms are studied and simulated in this system for the sake of a better performance. Simulation results show that MMSE-BLAST is an appropriate one among the conventional suboptimal algorithms, and the accuracy of the first detected layer determines the degree of error propagation. At last, a modified algorithm with the combination of ML and MMSE-BLAST is employed to reduce error propagation in the UWB channel with rich multipath.

关键词： ultra-wideband spatial multiplexing detection algorithms MMSE-BLAST error propagation

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An Exploratory Study of Periodicity detection algorithms for Energy Theft Prevention in Smart Grids 8

An Exploratory Study of Periodicity Detection Algorithms for...

引用

IEEE PES/IAS PowerAfrica Conference

作者： Ayogu, Ikechukwu I. Ogu, Reginald E. Fed Univ Technol Owerri Dept Comp Sci Owerri Nigeria Fed Univ Technol Owerri Dept Software Engn Owerri Nigeria

ISBN: (纸本)9781665403115

The sophistry evolved by dishonest consumers to thwart consumption measurement systems continues to increase in scope and dimension such that the utilitarian value of power sectors across the world is diminished as a result. This paper proposes a hybrid model for efficient periodicity analysis without incurring the computational overload that is often experienced with the Dynamic Time Warping (DTW) algorithm. Autocorrelation function was used to screen candidate periods from an FFT-generated periodogram to obtain a single, accurate period for use by the DTW algorithm to determine the similarity or otherwise of each of the data instance to its shifted version. The resulting, segregated data, either normal or theft, was then employed to construct machine learning models for electricity theft detection. A Decision tree classifier (DTC), two tree-based ensembles - Random Forest (RFC) and Extremely randomized tree classifiers (ETC) and an SVM model were trained on two separate categories of data- daily and mean weekly consumption data. The results show that the periodicity detection approach was promising. The ETC model produced the highest AUC of 95 % and 98 respectively on the daily and mean weekly data.

关键词： Anomaly detection Time series Classification algorithms Supervised learning Periodicity detection Intelligent systems Internet of Things Pattern recognition detection algorithms

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An Evaluation Framework for Inter-Domain Link Congestion detection algorithms 14

An Evaluation Framework for Inter-Domain Link Congestion Det...

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14th International Symposium on Pervasive Systems, algorithms and Networks (I-SPAN) / 11th International Conference on Frontier of Computer Science and Technology (FCST) / 3rd International Symposium of Creative Computing (ISCC)

作者： Phillips, Alex Zhu, Yingwu Seattle Univ Dept Comp Sci & Software Engn Seattle WA 98122 USA

ISBN: (纸本)9781538608401

Inter-domain link congestion can be caused by either under-provision or peer disputes. TSLP and M-Lab are two representative network-tomographic methods to detect congestion on inter-domain links. In this work, we propose a performance-cost framework to evaluate and compare the two methods via a simulator built atop NS-3. Via detailed simulations, we obtained some insights on the two approaches and hope they can benefit further study in this area. Our experimental results have shown that TSLP is more responsive to link congestion and consumes less measurement bandwidth while M-Lab is capable of associating congestion direction to a congested link. Moreover, M-Lab may produce false positives due to its massive measurement traffic and underpinned TCP congestion control. Our simulator source code is also available online for the research community.

关键词： Delays Bandwidth Throughput Servers Computer science detection algorithms Internet

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Measurement-based evaluation of data-parallelism for OpenCV feature-detection algorithms 42

Measurement-based evaluation of data-parallelism for OpenCV ...

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42nd Annual IEEE-Computer-Society Computers, Software and Applications (COMPSAC) Conference - Staying Smarter in a Smartening World

作者： Danielsson, Jakob Jagemar, Marcus Behnam, Moris Sjodin, Mikael Seceleanu, Tiberiu Malardalen Univ Vasteras Sweden Ericsson AB Stockholm Sweden

ISBN: (纸本)9781538626672

We investigate the effects on the execution time, shared cache usage and speed-up gains when using data-partitioned parallelism for the feature detection algorithms available in the OpenCV library. We use a data set of three different images which are scaled to six different sizes to exercise the different cache memories of our test architectures. Our measurements reveal that the algorithms using the default settings of OpenCV behave very differently when using data-partitioned parallelism. Our investigation shows that the executions of the algorithms SURF, Dense and MSER correlate to L3-cache usage and they are therefore not suitable for data-partitioned parallelism on multi-core CPUs. Other algorithms: BRISK, FAST, ORB, HARRIS, GFTT, SimpleBlob and SIFT, do not correlate to L3-cache in the same extent, and they are therefore more suitable for data-partitioned parallelism. Furthermore, the SIFT algorithm provides the most stable speed-up, resulting in an execution between 3 and 3.5 times faster than the original execution time for all image sizes. We also have evaluated the hardware resource usage by measuring the algorithm execution time simultaneously with the L3-cache usage. We have used our measurements to conclude which algorithms are suitable for parallelization on hardware with shared resources.

关键词： Feature extraction detection algorithms Parallel processing Detectors Multicore processing Hardware Libraries

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Pre-Coding using Different detection algorithms in MIMO System 3

Pre-Coding using Different Detection Algorithms in MIMO Syst...

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International Conference on Current Trends in Computer, Electrical, Electronics and Communication (CTCEEC)

作者： Sharma, Purnima K. Sharma, Dinesh Gupta, Akansha SVEC ECE Dept Tadepalligudem India GE Univ CSE Dept Dehra Dun India

ISBN: (纸本)9781538632437

Pre-coding is a general understanding of beam-forming to achieve the transmission diversity of the signal. Basically transmitter sends the information which is already coded according to the known knowledge about the channel conditions to the receiver. The pre-coding technique leads to achieve a good performance by eliminating the degradation effects even in the correlation environment upon the channel in the communication system. In this paper, the different detection algorithms: Zero forcing (ZF), Minimum mean square error (MMSE) and Block diagonalization (BD) are used in pre-coding. Many solutions have been proposed for the Co-Channel Interference problem. The main aim of this paper is to select the most suitable Coding techniques to adopt. The analysis is carried by assuming the channel as Rayleigh and modulation scheme is QPSK with 4x4 MIMO system.

关键词： Pre-coding detection algorithms Channel state information (CSI) Zero forcing (ZF) Minimum mean square error (MMSE) Block diagonalization (BD)

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Efficiency of Gas detection algorithms Using Fluctuation Enhanced Sensing

Efficiency of Gas Detection Algorithms Using Fluctuation Enh...

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International Conference on Noise and Fluctuations

作者： Lentka, L. Smulko, J. Ionescu, R. Gdansk Univ Technol Fac ETI PL-80233 Gdansk Poland Rovira & Virgily Univ Dept Elect Tarragona Spain

ISBN: (纸本)9781467383356

Efficiency of various gas detection algorithms by applying fluctuation enhanced sensing method was discussed. We have analyzed resistance noise observed in resistive WO3-nanowires gas sensing layers. Power spectral densities of the recorded noise were used as the input data vectors for two algorithms: the principal component analysis (PCA) and the support vector machine (SVM). The data were used to determine gas concentration by regression methods. Additionally, the SVM algorithm used the slope of 1/f noise estimated for consecutive low frequency bands only to reduce the volume of computation by limiting the input data vector size. The results show that the SVM method gives the best results when the input vector is a power spectral density.

关键词： Gas sensors detection algorithms Fluctuaction Enhanced Sensing Principal Component Analysis Support Vector Machine

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Optimizing Mobile Radio Access Network Spectrum Refarming Using Community detection algorithms 42

Optimizing Mobile Radio Access Network Spectrum Refarming Us...

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42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

作者： Budic, D. Skracic, K. Bodrusic, I. Ericsson Nikola Tesla Zagreb Croatia

ISBN: (纸本)9789532330984

Radio spectrum refarming is a cost-effective way to increase capacity for UMTS/LTE without the need to acquire new spectrum. Therefore, it is an important process for today's mobile operators. As radio access networks (RAN) became more complex, the process of choosing which radio sites to refarm has become complex and time-consuming if done manually. This paper proposes the use of community detection algorithms for automating the process of RAN spectrum refarming. The problem of RAN spectrum refarming can be modeled as a graph in which one needs to isolate nodes which are densely connected. In RAN spectrum refarming it is crucial to keep the interference between sites and technologies at a minimum. Several community detection algorithms were tested for RAN spectrum refarming. Girvan-Newman algorithm showed most accurate results and was used for implementation of optimization solution. In this paper, the authors provided a benchmark of various network and cluster sizes. Result showed that RAN spectrum refarming can be optimized from one to several weeks to roughly few hours per cluster.

关键词： Clustering algorithms detection algorithms Benchmark testing Image edge detection Partitioning algorithms Interference Radio access networks

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Hybrid neonatal EEG seizure detection algorithms achieve the benchmark of visual interpretation of the human expert 41

Hybrid neonatal EEG seizure detection algorithms achieve the...

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41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Stevenson, Nathan Tapani, Karoliina Vanhatalo, Sampsa QIMR Berghofer Med Res Inst 300 Herston Rd Brisbane Qld 4006 Australia Aalto Univ Otakaari 1 Espoo 02150 Finland Helsinki Univ Hosp Dept Neurophysiol Yliopistonkatu 4 Helsinki 00100 Finland Univ Helsinki Yliopistonkatu 4 Helsinki 00100 Finland

ISBN: (纸本)9781538613115

Neonatal EEG seizure detection algorithms (NS-DAs) have an upper bound of performance related to the agreement between visual interpretation of human experts. No published algorithms have reported performance that has reached this upper bound. In this paper, we combined two recently developed NSDAs in order to improve detection performance. An outlier detection stage was also added to improve robustness in the presence of unseen data. A large database of EEG from 79 term infants labeled by three independent human experts was used to develop and test the sufficiency of the hybrid NSDA. The inter-observer agreement (IOA) between experts was high (kappa = 0.757, 95%CI: 0.665-0.836, n=79). The area under the receiver operator characteristic of the NSDA compared to the consensus annotation of the human experts was 0.952 (95%CI: 0.0927-0.971). The IOA of seizure detection between the NSDA and human experts was not significantly less than the IOA among human experts (Delta kappa = 0.022, 95%CI: -0.020 to 0.072) and was further improved by increasing the minimum seizure duration from 10s to 30s (Delta kappa = -0.002, 95%CI: -0.073 to 0.055). Automated methods of neonatal EEG seizure detection have sufficient accuracy to replace human interpretation, potentially, providing reliable interpretations for clinicians in the neonatal intensive care unit.

关键词： Electroencephalography Pediatrics Support vector machines Feature extraction Anomaly detection Training detection algorithms

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Proposed New Requirements for Testing and Reporting Performance Results of Arrhythmia detection algorithms

Proposed New Requirements for Testing and Reporting Performa...

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40th Annual Meeting on Computing in Cardiology (CinC)

作者： Wang, John Philips Healthcare Andover MA 01810 USA

ISBN: (纸本)9781479908844

Several arrhythmia performance measures as specified in the current AAMI recommended practice document do not adequately reflect actual clinical experience in real-time patient monitoring. Additional reporting requirements that are more clinical relevant are thus needed: 1) Due to the large number of QRS complexes that need to be analyzed, even an algorithm with high specificity will generate a large number of false positives, which is not directly reflected by the reported false positive rate. A new recommendation is to report the actual number of false positives. 2) Due to the low PVC prevalence in most monitored patients, the high positive predictive values (PPV) reported using databases with high PVC prevalence are not clinically relevant. A proposed recommendation is to report PPVs at much lower PVC rates. 3) Arrhythmia performance measures as specified in the recommended practice do not include performance bounds. A new proposal is to use the bootstrap method with sample replacement to generate the mean values and 95% confident intervals for all the reported arrhythmia performance measures. Conclusions: Additional performance measures are proposed to further improve the clinical relevance of the reported results. These measures should be considered for inclusion as part of the standard reporting.

关键词： Cardiac Arrhythmias False-positives bootstrapping PIGMENT VOLUME CONCENTRATION Polyvinyl Chloride detection algorithms p-phenyl vinyl sampling with replacement

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