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检索条件"主题词=detection algorithms"

共 7380 条记录，以下是61-70 订阅

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Experimental Comparison of Hardware-Amenable Spike detection algorithms for iBMIs 9

Experimental Comparison of Hardware-Amenable Spike Detection...

引用

9th IEEE/EMBS International Conference on Neural Engineering (NER)

作者： Shaikh, Shoeb So, Rosa Libedinsky, Camilo Basu, Arindam Nanyang Technol Univ Singapore Singapore Inst Infocomm Res Singapore Singapore Natl Univ Singapore SiNAPSE Singapore Singapore

ISBN: (纸本)9781538679210

This paper presents an experiment based comparison of absolute threshold (AT) and non-linear energy operator (NEO) spike detection algorithms in intra-cortical Brain Machine Interfaces (iBMIs). Results show an average increase in decoding performance of approximate to 5% in monkey A across 28 sessions recorded over 6 days and approximate to 2% in monkey B across 35 sessions recorded over 8 days when using NEO over AT. To the best of our knowledge, this is the first ever reported comparison of spike detection algorithms in an iBMI experimental framework involving two monkeys. Based on the improvements observed in an experimental setting backed by previously reported improvements in simulation studies, we advocate switching from state of the art spike detection technique - AT to NEO.

关键词： Decoding Brain-computer interfaces Electrodes Standards Sorting detection algorithms Hardware

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Automatic Generation of Deadlock detection algorithms for a Family of Microarchitecture Description Languages of Communication Fabrics

Automatic Generation of Deadlock Detection Algorithms for a ...

引用

17th IEEE International High Level Design Validation and Test Workshop (HLDVT)

作者： Verbeek, Freek Schmaltz, Julien Radboud Univ Nijmegen Inst Comp & Informat Sci POB 9010 NL-6500 GL Nijmegen Netherlands Open Univ Netherlands Sch Comp Sci NL-6401 DL Heerlen Netherlands

ISBN: (纸本)9781467328975;9781467328982

In the multi-core era, ensuring deadlock freedom of communication fabrics is an important challenge. Intel proposed xMAS, a microarchitecture description language (MaDL), to support the formal modelling and verification of communication fabrics. The xMAS language is restricted to eight basic primitives. Using this restriction, an efficient deadlock detection technique has been defined. This technique is tailored to the eight primitives, which are not sufficient to model many realistic designs. We exhibit two primitives, namely, an adaptive switch and a synchronization barrier, that cannot be expressed or analyzed using the current xMAS language and tools. Our main contribution is to automatically generate an efficient deadlock detection algorithm tailored to a given set of primitives. We define a set of core primitives and extension mechanisms for user-defined primitives. This creates a family of MaDL's together with a family of tailored and efficient deadlock detection algorithms. We prove that the automatically generated algorithms are correct by construction, i.e., they correctly detect deadlocks in all fabrics defined in the language for which they are generated. These algorithms handle message dependencies, counters, virtual channels, parametric buffer sizes, and many other aspects of micro-architectural models. The effectiveness of our approach is demonstrated on models with adaptive switches and synchronization barriers. Our approach automatically provides efficient deadlock detection for a large family of MaDL's.

关键词： detection algorithms Textile fabrics autogeneration fabric Language family Microarchitecture Communication Research AUTOMATIC large family

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Scalable Generation of Graphs for Benchmarking HPC Community-detection algorithms 19

Scalable Generation of Graphs for Benchmarking HPC Community...

引用

International Conference for High Performance Computing, Networking, Storage and Analysis (SC)

作者： Slota, George M. Berry, Jonathan W. Hammond, Simon D. Olivier, Stephen L. Phillips, Cynthia A. Rajamanickam, Siva Rensselaer Polytech Inst Troy NY 12181 USA Sandia Natl Labs Livermore CA 94550 USA

ISBN: (数字)9781450362290

ISBN: (纸本)9781450362290

Community detection in graphs is a canonical social network analysis method. We consider the problem of generating suites of terascale synthetic social networks to compare the solution quality of parallel community-detection methods. The standard method, based on the graph generator of Lancichinetti, Fortunato, and Radicchi (LFR), has been used extensively for modest-scale graphs, but has inherent scalability limitations. We provide an alternative, based on the scalable Block Two-Level Erdos-Renyi (BTER) graph generator, that enables HPC-scale evaluation of solution quality in the style of LFR. Our approach varies community coherence, and retains other important properties. Our methods can scale real-world networks, e.g., to create a version of the Friendster network that is 512 times larger. With BTER's inherent scalability, we can generate a 15-terabyte graph (4.6B vertices, 925B edges) in just over one minute. We demonstrate our capability by showing that label-propagation community-detection algorithm can be strong-scaled with negligible solution-quality loss.

关键词： Social networking (online) Scalability Image edge detection High performance computing Software algorithms Coherence Generators Software detection algorithms Standards

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Comparison of two detection algorithms for pipeline leaks

Comparison of two detection algorithms for pipeline leaks

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IEEE Conference on Control Applications

作者： Begovich, O. Navarro, A. Sanchez, E. N. Besancon, G. Natl Polytech Inst Res & Adv Studies Ctr Guadalajara Jalisco Mexico ENSIEG Control Syst Dept ex LAG GIPSA Lab St Martin Here F-4638402 Grenoble France

ISBN: (纸本)9781424404421

The aim of this paper is to compare two analytic detection algorithms for pipeline leaks in order to assess their effectivity. Parameters such as precision and velocity to detect and locate a leak, algorithm complexity, and application facilities are evaluated, with the purpose of finding the most useful algorithm for a future real-time implementation on a Mexican aqueduct.

关键词： detection algorithms Leaks pipeline Leakage (fluid) Algorithmic complexity Precision

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A CFAR optimization for low frequency UWB SAR change detection algorithms 37

A CFAR optimization for low frequency UWB SAR change detecti...

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37th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2017

作者： Fabrin, Ana C. F. Molin, Ricardo D. Alves, Dimas I. Machado, Renato Bayer, Fabio M. Pettersson, Mats I. Federal University of Santa Maria - UFSM Santa Maria - RS97105-900 Brazil Federal University of PAMPA - UNIPAMPA Alegrete - RS97546-550 Brazil Blekinge Institute of Technology - BTH KarlskronaSE-371 79 Sweden

ISBN: (纸本)9781509049516

This paper presents a study on the constant false alarm rate (CFAR) filter design for change detection algorithms (CDA). More specifically, we are interested in CFAR filters used in CDA for low frequency ultra-wideband (UWB) synthetic aperture radar (SAR) systems. The filter design performance was evaluated in terms of false alarm rate (FAR) and probability of detection (PD). For evaluation purposes, we considered a set of SAR images obtained with the CARABAS-II system. The results are compared with the ones presented in [1], where the same CDA was considered, except for the CFAR filter. The results show that relevant FAR performance improvements can be obtained by just modifying the CFAR filter parameters taking into account the image resolution and target characteristics. © 2017 IEEE.

关键词： Synthetic aperture radar Change detection algorithms detection algorithms Algorithm design and analysis Image resolution

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detection algorithms for physical network coding

Detection algorithms for physical network coding

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International Conference on Communications and Networking in China (CHINACOM)

作者： Chengkang Pan Jianjun Liu Zhenping Hu China Mobile Research Institute Beijing China

This paper investigates multi-user detection (MUD) as well as virtual single-user detection (VSUD) for denoising-based physical network coding in two-way relay channels. In MUD, the two source messages are detected separately and then mapped into a relaying message. In VSUD, the relaying message is obtained directly by detecting the received signal. Maximum likelihood (ML) algorithm and linear algorithms are considered for both single-antenna case and multi-antenna case with and without transmit power and phase control. Suboptimal detection algorithms with lower complexity are also proposed for VSUD. Simulation results show that ML VSUD can achieve better BER performance than ML MUD. The proposed detection algorithms can achieve similar BER performance to ML VSUD .

关键词： detection algorithms Multiuser detection Relays Bit error rate Phase control Network coding Detectors

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detection algorithms and Information Rates for Bit-Patterned Media Storage Systems with Written-in Errors

Detection Algorithms and Information Rates for Bit-Patterned...

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IEEE International Symposium on Information Theory

作者： Jun Hu Tolga M. Duman Erozan M. Kurtas M. Fatih Erden Department of Electrical Engineering Arizona State University Tempe AZ USA Seagate Technologies Inc. Pittsburgh PA USA

ISBN: (纸本)9781424413973;1424413974

This paper studies bit-patterned media recording channels when there exist written-in errors. Using a signal processing point of view, we consider an abstract model for the overall recording channel, incorporating errors occurred during the write process. Based on the resulting channel model, we develop various trellis structures, and propose several detection algorithms for data recovery. Furthermore, we investigate the achievable information rates for patterned media recording systems with different levels of write error probability, which provide an information theoretical performance assessment for such systems.

关键词： detection algorithms Information rates Writing Computer errors Signal processing algorithms Error probability System performance Delay Fabrication Magnetic heads

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detection algorithms for hyperspectral imaging applications: a signal processing perspective

Detection algorithms for hyperspectral imaging applications:...

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IEEE Workshop on Advances in Techniques for Analysis of Remotely Sensed Data

作者： D. Manolakis MIT Lincoln Laboratories Lexington MA USA

The purpose of this paper is to present a unified, simplified, and concise, overview of spectral target detection algorithms for hyperspectral imaging applications. We focus on detection algorithms derived using established statistical techniques and whose performance is predictable under reasonable assumptions about hyperspectral imaging data. The emphasis on a signal processing perspective helps to, better understand the strengths and limitations of each algorithm, avoid unrealistic performance expectations, and apply an algorithm properly and sensibly.

关键词： detection algorithms Hyperspectral imaging Signal processing algorithms Object detection Reflectivity Detectors Testing Hyperspectral sensors Sensor phenomena and characterization Electromagnetic measurements

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detection algorithms based on prediction error - additive noise - data orthogonality

Detection algorithms based on prediction error - additive no...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： M. Ibrahim C. Goutis Department of Electrical and Electronic Engineering University of Newcastle UK

Two new iterative algorithms for AR parameter estimation are presented. The first minimizes the sum of the prediction error energy and the cross covariance between prediction error and additive noise, and models the noise covariance matrix with a separate AR filter whose reflection coefficient are constrained to be sufficiently small. The second algorithm minimizes the cross covariance between the prediction error and the data. In both algorithm a steepest descent updating procedure is employed and stability of the AR filter for the stohastic processes is ensured by constraining the corresponding reflection coefficients to be less than one.

关键词： detection algorithms Additive noise Covariance matrix Iterative algorithms Filters Acoustic reflection Predictive models Additive white noise White noise Gaussian noise

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COMPARISON OF ON-LINE CHATTER detection algorithms IN TURNING

COMPARISON OF ON-LINE CHATTER DETECTION ALGORITHMS IN TURNIN...

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International Symposium on Flexible Automation (ISFA)

作者： Vinh Nguyen Melkote, Shreyes Deshamudre, Amar Khanna, Maneesh Walker, Dan Georgia Inst Technol 801 Ferst Dr Atlanta GA 30332 USA Siemens Energy Inc 5101 Westinghouse Blvd Charlotte NC 28273 USA

ISBN: (纸本)9781509034673

Dynamic instability in the form of chatter is a highly undesirable phenomenon that occurs during machining, resulting in poor surface finish and reduced tool life. Though analytical models exist for identifying conditions that avoid chatter, they do not account for process uncertainties or they require extensive cutting tests. Therefore, an on-line chatter detection algorithm is required to detect chatter before irreversible damage to the cutting tool or workpiece occurs. This paper evaluates the performance of three chatter detection algorithms in detecting chatter in the turning process with the eventual goal of developing embedded sensor-based process monitoring automation. Cutting force data are gathered from a number of turning scenarios with varying workpiece geometries. Of the chatter detection algorithms evaluated, spectral analysis is found to be the most robust and capable of detecting dynamic instability before tool or workpiece damage occurs.

关键词： Force Correlation Heuristic algorithms Feeds Turning detection algorithms Dynamics

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