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检索条件"主题词=detection algorithms"

共 7428 条记录，以下是4141-4150 订阅

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Low-power robust beat detection in ambulatory cardiac monitoring

Low-power robust beat detection in ambulatory cardiac monito...

引用

IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Iñaki Romero Bernard Grundlehner Julien Penders Jos Huisken Yahya H. Yassin Holst Centre IMEC Eindhoven Netherlands Department of Electronics and Telecommunications Norwegian University of Science and Technology Trondheim Norway

With new advances in ambulatory monitoring new challenges appear due to degradation in signal quality and limitations in hardware requirements. Existing signal analysis methods should be re-evaluated in order to adapt to the restrictive requirements of these new applications. With this motivation, we chose a robust beat detection algorithm and optimized it further to be running in an embedded platform within a cardiac monitoring sensor node. The algorithm was designed in floating point in Matlab and evaluated in order to study its performance under a wide range of conditions. The initial PC version of the algorithm obtained a good performance under a wide variety of conditions (Se = 99.65% and + P = 99.79% on the MIT/BIH arrhythmia database and Se = 99.88%, + P = 99.93% on our own database with ambulatory data). In this study, the algorithm is adapted and further optimized to work in real time on an embedded digital processor, while keeping this performance without degradation. The run-time memory usage of the application was of 150 KB with an execution time of 1.5 million cycles and an average power consumption of 494 ¿W for an ECG of 3 seconds length and sampling frequency of 198 Hz. The algorithm implementation in a general purpose processor will put significant limits on the performance in terms of power consumption. We propose possible specifications for an application-optimized processor for more efficient ECG analysis.

关键词： Robustness Monitoring Degradation Databases Energy consumption Electrocardiography Hardware Signal analysis detection algorithms Algorithm design and analysis

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A simplification in integral frequency offset estimation based on joint detection algorithm for WiMAX 802.16e

A simplification in integral frequency offset estimation bas...

引用

National Conference on Radio Science (NSRC)

作者： Ahmed Ahmedin Sarah Rashad Mahmoud Fayez Marwa Abdel Raouf Mostafa Sayed Hossam Fahmy Ahmed Sultan Mahmoud Hamed Nile University Egypt Cairo University Egypt Nile University

Initial downlink synchronization for orthogonal frequency division multiple access (OFDMA) network access involves timing and frequency synchronization. The frequency offset is produced by oscillator drifts and time-varying Doppler shifts. In mobile WiMAX 802.16e carrier frequency offset (CFO) can be divided into: integral carrier frequency offset (ICFO) and fractional carrier frequency offset (FCFO). There are mainly three methods for CFO estimation: data-aided method, blind and semi-blind. This paper is based on the semi-blind method presented in ldquoJoint detection of integral carrier frequency offset and preamble index in OFDMA WiMAX downlink synchronizationrdquo, IEEE, 2007, see [2]. We simplify the algorithm presented in that paper by (a) using an adder-subtractor instead of using squares to estimate power and (b) by using a XNOR instead of complex multiplier; thereby reducing hardware gates by a factor of 676. Simulation results show only a slight degradation in performance with a considerable reduction in complexity.

关键词： Frequency estimation detection algorithms WiMAX Frequency conversion Frequency synchronization Downlink Timing Oscillators Doppler shift Hardware

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Localization by superposing beats: Laboratory experiments and detection algorithm

Localization by superposing beats: Laboratory experiments an...

引用

IEEE International Symposium on Intelligent Signal Processing

作者： Matthias Schneider Ralf Salomon University of Rostock Rostock Germany

ISBN: (纸本)9781424450572

Many everyday life activities require precise localization information. Navigation by means of the global positioning system (GPS) is a well-known example. Despite its broad usage, this localization method cannot be utilized in all application areas. Logistics, factory and laboratory automation, as well as warehouse management, for example, require the low-cost localization of various objects with a precision of a few centimeters, particularly in indoor environments. For this application domain, this paper proposes a new localization procedure that is based on the superposition of particularly parameterized beats. In addition, this paper also presents a preliminary theoretical analysis as well as some laboratory experiments.

关键词： Laboratories detection algorithms Global Positioning System Shape Production facilities Indoor environments Electromagnetic measurements Signal resolution Radio transmitters Detectors

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A FPGA-Based Dual-Pixel Processing Pipelined Hardware Accelerator for Feature Point detection Part in SIFT

A FPGA-Based Dual-Pixel Processing Pipelined Hardware Accele...

引用

International Joint Conference on INC, IMS and IDC, NCM

作者： Jingbang Qiu Tianci Huang Takeshi Ikenaga Graduate School of IPS Waseda University Kitakyushu Japan

SIFT is regarded as one of the most robust feature point detection algorithms in CV field. The feature point detection part, allocating final positions of all feature points, majorly defines the accuracy and stability of the whole system. In this paper, we propose an FPGA-implementable hardware accelerator for this part. By introducing dual-pixel processing and the 3-stage-interpolation pipelined architecture with use of dual-port DDR2 memory access, we achieve to further improve process speed, meanwhile keeping high accuracy. By experiment, our system proves to reach max clock frequency of 145.0 MHz, processing up to 40 VGA images including memory operations. Compared with conventional work, hardware cost is slightly increased as trade-off for accelerated speed. High efficiency as 98.72% and high cover rate as 92.85% are kept by our proposal. Our proposal is suitable as a real-time SIFT system structure.

关键词： Hardware Computer vision Proposals Robustness detection algorithms Stability Clocks Frequency Costs Acceleration

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Anomaly detection Using Improved Hierarchy Clustering

Anomaly Detection Using Improved Hierarchy Clustering

引用

International Conference on Artificial Intelligence and Computational Intelligence (AICI)

作者： Liang Hu Weiwu Ren Fei Ren Department of Computer Science and Technology Jilin University Changchun China

Most anomaly detection methods can not be fit for the changing and complex network. High noise and updating normality profiles not in time will lead to high false alarm rate. In this paper, a new anomaly detection algorithm using improved hierarchy clustering, called ADIHC, is proposed in this paper. It applies an improved hierarchy clustering tree to organize clusters which are obtained by density-based partitioning method. We extend the clustering algorithm and apply branch and bound method for filtering noise. With the help of two advantages: filtering noise and updating normality profiles at any time, our algorithm is suitable for the changing and complex network. A series of experimental results on well known KDD Cup 1999 dataset indicate that ADIHC has superior performance of detection and meets more real-time requirements of intrusion detection system.

关键词： Clustering algorithms Intrusion detection Partitioning algorithms Complex networks detection algorithms Filtering algorithms Clustering methods Artificial intelligence Computational intelligence Computer science

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Community detection in Large-Scale Bipartite Networks

Community Detection in Large-Scale Bipartite Networks

引用

IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Xin Liu Tsuyoshi Murata Department of Computer Science Graduate School of Information Science and Engineering Tokyo Institute of Technology Tokyo Japan

Community detection in networks receives much attention recently. Most of the previous works are for unipartite networks composed of only one type of nodes. In real world situations, however, there are many bipartite networks composed of two types of nodes. In this paper, we propose a fast algorithm called LP&BRIM for community detection in large-scale bipartite networks. It is based on a joint strategy of two developed algorithms -- label propagation (LP), a very fast community detection algorithm, and BRIM, an algorithm for generating better community structure by recursively inducing divisions between the two types of nodes in bipartite networks. Through experiments, we demonstrate that this new algorithm successfully finds meaningful community structures in large-scale bipartite networks in reasonable time limit.

关键词： Large-scale systems Intelligent agent Intelligent networks detection algorithms Conferences Computer science Information science Electronic mail Complex networks Particle measurements

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Automatic defects detection in industrial C/C++ software

Automatic defects detection in industrial C/C++ software

引用

Central and Eastern European Software Engineering Conference in Russia (CEE-SECR)

作者： Vladimir Itsykson Mikhail Moiseev Vadim Tsesko Alexey Zakharov Saint Petersburg State Polytechnical University Russia

The solution to the problem of automatic defects detection in industrial software is covered in this paper. The results of the experiments with the existing tools are presented. These results stand for inadequate efficiency of the implemented analysis. Existing source code static analysis methods and defects detection algorithms are covered. The program model and the analysis algorithms based on existing approaches are proposed. The problems of co-execution of different analysis algorithms are explored. The ways for improvement of analysis precision and algorithms performance are proposed. Advantages of the approaches developed are: soundness of a solution, full support of the features of target programming languages and analysis of the programs lacking full source code using annotations mechanism. The algorithms proposed in the paper are implemented in the automatic defects detection tool.

关键词： Computer industry Algorithm design and analysis detection algorithms Performance analysis Computer languages

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Joint channel estimation and data detection for OFDM systems over doubly selective channels

Joint channel estimation and data detection for OFDM systems...

引用

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

作者： Lanlan He Shaodan Ma Yik-Chung Wu Tung-Sang Ng Department of Electrical and Electronic Engineering University of Hong Kong Hong Kong China

In this paper, a joint channel estimation and data detection algorithm is proposed for OFDM systems under doubly selective channels (DSCs). After representing the DSC using Karhunen-Loe¿ve basis expansion model (K-L BEM), the proposed algorithm is developed based on the expectation-maximization (EM) algorithm. Basically, it is an iterative algorithm including two steps at each iteration. In the first step, the unknown coefficients in K-L BEM are first integrated out to obtain a function which only depends on data, and meanwhile, a maximum a posteriori (MAP) channel estimator is obtained. In the second step, data are directly detected by a novel approach based on the function obtained in the first step. Moreover, a Bayesian Cramer-Rao Lower Bound (BCRB) which is valid for any channel estimator is also derived to evaluate the performance of the proposed channel estimator. The effectiveness of the proposed algorithm is finally corroborated by simulation results.

关键词： Channel estimation OFDM Iterative algorithms detection algorithms Time-varying channels Detectors Intersymbol interference Helium Data engineering Multiaccess communication

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A New Type of Automatic Ship detection Method

A New Type of Automatic Ship Detection Method

引用

International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Zhuo Chen Coll. of Inf. Sci. & Technol. Qingdao Univ. of Sci. & Technol. Qingdao China

A new type of automatic ship detection algorithm is proposed in this paper. By determining whether the local area is heterogeneous, simplex two-parameter CFAR algorithm based on Gauss-distribution or both two-parameter CFAR algorithm based on Gauss-distribution and two-parameter CFAR verification algorithm based on K-distribution are used to detect targets. This new type of algorithm keeps both the ability of traditional two-parameter CFAR algorithm' good features, such as small computation quantity, easy to implement and so on, and the detection accuracy in complex sea conditions at the same time.

关键词： Marine vehicles Signal processing algorithms Clutter Sea surface detection algorithms Radar detection Gaussian distribution Synthetic aperture radar Surface treatment Weibull distribution

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Theoretically Optimal Distributed Anomaly detection

Theoretically Optimal Distributed Anomaly Detection

引用

IEEE International Conference on Data Mining Workshops (ICDM Workshops)

作者： Aleksandar Lazarevic Nisheeth Srivastava Ashutosh Tiwari Josh Isom Nikunj Oza Jaideep Srivastava United Technologies Corporation Hartford CT USA Department of Computer Science University of Minnesota MN USA NASA Ames Research Center Moffett Field CA USA

A novel general framework for distributed anomaly detection with theoretical performance guarantees is proposed. Our algorithmic approach combines existing anomaly detection procedures with a novel method for computing global statistics using local sufficient statistics. Under a Gaussian assumption, our distributed algorithm is guaranteed to perform as well as its centralized counterpart, a condition we call `zero information loss'. We further report experimental results on synthetic as well as real-world data to demonstrate the viability of our approach.

关键词： Data mining Distributed algorithms Statistical distributions detection algorithms Monitoring Conferences Space technology Computer science NASA Data privacy

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