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检索条件"主题词=Algorithm design and analysis"

共 82948 条记录，以下是571-580 订阅

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An on-chip ADC BIST solution and the BIST enabled calibration scheme 48

An on-chip ADC BIST solution and the BIST enabled calibratio...

引用

IEEE International Test Conference (ITC)

作者： Jin, Xiankun Chen, Tao Jain, Mayank Barman, Arun Kumar Kramer, David Garrity, Doug Geiger, Randall Chen, Degang NXP Semicond Eindhoven Netherlands Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA

ISBN: (纸本)9781538634134

This paper presents a complete on-chip ADC BIST solution based on a segmented stimulus error identification algorithm known as USER-SMILE. By adapting the algorithm for efficient hardware realization, the solution is implemented towards a 1Msps 12-bit SAR ADC on a 28nm CMOS automotive microcontroller. While sufficient test accuracy is demonstrated, the solution is further extended to correct linearity errors of ADC. The entire BIST and calibration circuitry occupies 0.028mm(2) silicon area while enabling more than 10 times tester time reduction and >10dB THD/SFDR performance improvement over an existing structural capacitor-weight-identification calibration scheme. The added die cost is estimated to be 1/8 of the saved test cost from tester time reduction alone.

关键词： Built-in self-test Mathematical model Hardware System-on-chip Calibration Linearity algorithm design and analysis

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Applied Research Of Circuit Fault Diagnosis System Base On SAT Satisfying The algorithm 2

Applied Research Of Circuit Fault Diagnosis System Base On S...

引用

2017 IEEE 第2届先进信息技术,电子与自动化控制国际会议(IAEAC 2017)

作者： CAI Li-sha ZENG Wei-peng Hainan Software Profession Institute

In order to make the circuit fault diagnosis system more intelligent, *** DS decision algorithm is presented b ased on the process of model-based diagnosis. Model-based circ uit fault diagnos

ISBN: (纸本)9781467389808

In order to make the circuit fault diagnosis system more intelligent, *** DS decision algorithm is presented b ased on the process of model-based diagnosis. Model-based circ uit fault diagnos

关键词： algorithm design and analysis Circuit faults Fault diagnosis Logic gates Integrated circuit modeling Software algorithms Cognition

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Pairwise Ranking Aggregation by Non-interactive Crowdsourcing with Budget Constraints 37

Pairwise Ranking Aggregation by Non-interactive Crowdsourcin...

引用

37th IEEE International Conference on Distributed Computing Systems (ICDCS)

作者： Cai, Changjiang Sun, Haipei Dong, Boxiang Zhang, Bo Wang, Ting Wang, Hui (Wendy) Stevens Inst Technol Hoboken NJ 07030 USA Montclair State Univ Montclair NJ USA Lehigh Univ Bethlehem PA 18015 USA

ISBN: (纸本)9781538617915

Crowdsourced ranking algorithms ask the crowd to compare the objects and infer the full ranking based on the crowdsourced pairwise comparison results. In this paper, we consider the setting in which the task requester is equipped with a limited budget that can afford only a small number of pairwise comparisons. To make the problem more complicated, the crowd may return noisy comparison answers. We propose an approach to obtain a good-quality full ranking from a small number of pairwise preferences in two steps, namely task assignment and result inference. In the task assignment step, we generate pairwise comparison tasks that produce a full ranking with high probability. In the result inference step, based on the transitive property of pairwise comparisons and truth discovery, we design an efficient heuristic algorithm to find the best full ranking from the potentially conflictive pairwise preferences. The experiment results demonstrate the effectiveness and efficiency of our approach.

关键词： Crowdsourcing algorithm design and analysis Heuristic algorithms Noise measurement Inference algorithms Reliability Smoothing methods

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An L1-Minimization Based algorithm to Measure the Redundancy of State Estimators in Large Sensor Systems 13

An L1-Minimization Based Algorithm to Measure the Redundancy...

引用

13th IEEE Conference on Automation Science and Engineering (IEEE CASE)

作者： Vijayaraghavan, Vishnu Kianfar, Kiavash Ding, Yu Parsaei, Hamid Texas A&M Univ Dept Ind & Syst Engn College Stn TX 77843 USA Texas A&M Univ Qatar Dept Mech Engn POB 23874 Doha Qatar

ISBN: (纸本)9781509067817

Linear models have been successfully used to establish the connections between sensor measurements and system states in sensor networks. Finding the degree of redundancy for structured linear systems is proven to be NP-hard. Previously bound-and-decompose, 0-1 mixed integer programming and hybrid algorithms embedding 0-1 mixed integer feasibility checking within a bound-and-decompose framework have all been proposed and compared in the literature. In this paper, we exploit the computational efficiency of linear programs to present a novel heuristic algorithm which solves a series of l(1)-norm minimization problems in a specific framework to find extremely good solutions to this problem in remarkably small runtime.

关键词： Redundancy Sensor systems algorithm design and analysis Signal processing algorithms Q measurement Sparse matrices Compressed sensing

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The Application of Deep Learning in Computer Vision

The Application of Deep Learning in Computer Vision

引用

Chinese Automation Congress (CAC)

作者： Wu, Qing Liu, Yungang Li, Qiang Jin, Shaoli Li, Fengzhong Shandong Univ Sch Control Sci & Engn Jinan 250061 Shandong Peoples R China

ISBN: (纸本)9781538635247

As the deep learning exhibits strong advantages in the feature extraction, it has been widely used in the field of computer vision and among others, and gradually replaced traditional machine learning algorithms. This paper first reviews the main ideas of deep learning, and displays several related frequently-used algorithms for computer vision. Afterwards, the current research status of computer vision field is demonstrated in this paper, particularly the main applications of deep learning in the research field.

关键词： Machine learning Computer vision Training Gallium nitride Feature extraction algorithm design and analysis

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Particle Swarm Optimization for Large-Scale Clustering on Apache Spark

Particle Swarm Optimization for Large-Scale Clustering on Ap...

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IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Sherar, Matthew Zulkernine, Farhana Queens Univ Sch Comp Kingston ON Canada

ISBN: (纸本)9781538627266

We present a particle swarm optimization (PSO) clustering algorithm implemented in Apache Spark to achieve parallel big data clustering. Apache Spark is an in-memory big data analytics framework which uses parallel distributed processing to analyze large amount of data faster than most other existing data analytic tools. Spark's library of data analytic functions does not include the PSO algorithm. PSO is an evolutionary computing technique that has shown to produce more compact clusters than other partitional clustering techniques for a wide range of data. In addition PSO is a paralellizable and customizable algorithm well suited for multi-objective clustering problems. In this paper we present our implementation of a hybrid K-Means PSO (KMPSO) clustering algorithm in Apache Spark and demonstrate the performance gained in Spark by comparing our implementation with an implementation of KMPSO in MATLAB. We demonstrate that KMPSO can produce better clustering results than Spark's built-in clustering algorithms, and that Apache Spark enables efficient scaling of resources to handle large and complex workloads.

关键词： Clustering algorithms Sparks Particle swarm optimization Convergence algorithm design and analysis Optimization Machine learning algorithms

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Real-time Clustering algorithm that Adapts to Dynamic Changes in Neural Recordings 50

Real-time Clustering Algorithm that Adapts to Dynamic Change...

引用

IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Davila-Montero, Sylmarie Barsakcioglu, Deren Y. Jackson, Andrew Constandinou, Timothy G. Mason, Andrew J. Michigan State Univ Dept Elect & Comp Engn E Lansing MI 48824 USA Imperial Coll London Dept Elect & Elect Engn Ctr Bioinspired Technol London England Newcastle Univ Inst Neurosci Newcastle Upon Tyne NE1 7RU Tyne & Wear England

ISBN: (纸本)9781467368537

This work presents a computationally efficient real-time adaptive clustering algorithm that recognizes and adapts to dynamic changes observed in neural recordings. The algorithm consists of an off-line training phase that determines initial cluster positions and an on-line operation phase that continuously tracks drifts in clusters and periodically verifies acute changes in cluster composition. analysis of chronic recordings from non-human primates shows that adaptive clustering achieves an improvement of 14% in classification accuracy and demonstrates an ability to recognize acute changes with 78% accuracy, with significantly improved computational efficiency compared to the state-of-the-art. The presented algorithm is suitable for long-term chronic monitoring of neural activity in many applications of neuroscience research and control of neural prosthetics and assistive devices.

关键词： Clustering algorithms Real-time systems Classification algorithms algorithm design and analysis Sorting Measurement Heuristic algorithms

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A Connected Dominating Set Construction algorithm Based on Power Selection 6

A Connected Dominating Set Construction Algorithm Based on P...

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6th IEEE International Conference on Computer, Information and Telecommunication Systems (IEEE CITS)

作者： Yan, Jiangbao Guo, Yu Mi, Zhenqiang Yang, Yang Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing Peoples R China

ISBN: (纸本)9781509059577

With the rapid development of Internet of things, Wireless Sensor Networks (WSN) has received growing interests. As the virtual backbone of WSN, connected dominating set (CDS) plays an important role in supporting data communication, reducing routing overhead and enhancing the scalability of the network. Attribute to the rapid development of microprocessor and electronic technology, communication radius of sensor nodes can be changed accordingly to save the energy consumption. In this paper, we take the adjustable radius feature of WSN into consideration and propose an efficient distributed CDS construction algorithm, namely Power Selection algorithm (PSA), to optimize the CDS construction based on local information. Simulation results show that PSA can build a virtual backbone of WSN with smaller CDS and less energy consumption, thus improving the performance of the network.

关键词： Wireless sensor networks Energy consumption Cost function Approximation algorithms algorithm design and analysis Wireless communication Network topology

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Automated Selection of Offloadable Tasks for Mobile Computation Offloading in Edge Computing 13

Automated Selection of Offloadable Tasks for Mobile Computat...

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13th AMC/IEEE/IFIP International Conference on Network and Service Management (CNSM)

作者： Zanni, Alessandro Yu, Se-young Bellavista, Paolo Langar, Rami Secci, Stefano Univ Bologna Dept Comp Sci & Engn DISI Bologna Italy UPMC Univ Paris 06 Sorbonne Univ LIP6 UMR 7606 Paris France Northwestern Univ Int Ctr Adv Internet Res iCAIR Evanston IL 60208 USA Univ Paris Est Marne La Vallee LIGM UMR 8049 Champs Sur Marne France

ISBN: (纸本)9783901882982

Mobile computation offloading has recently attracted much interest and first offloading solutions have been developed. However, the relevant technical challenge of how to automatically determine offloadable sections of Android applications has not been adequately investigated so far. This paper proposes an innovative task selection algorithm that can parse an Android application autonomously and classify all the methods based on their offloadability by adopting a fine-grained and multi-steps analyzer. The reported experimental results show the effectiveness of our solution when applied to the top 25 most downloaded Android apps on the Google Play store, by showing its accuracy in identifying offloadable methods and demonstrating the potential benefits of automated mobile computation offloading.

关键词： Androids Humanoid robots Mobile communication algorithm design and analysis Heuristic algorithms Java

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Exploiting digital DNA for the analysis of similarities in Twitter behaviours 4

Exploiting digital DNA for the analysis of similarities in T...

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4th IEEE / ACM / ASA International Conference on Data Science and Advanced Analytics (DSAA)

作者： Cresci, Stefano Di Pietron, Roberto Petrocchi, Marinella Spognardi, Angelo Tesconi, Maurizio Natl Res Council IIT CNR Inst Informat & Telemat Pisa Italy Nokia Bell Labs Paris France Sapienza Univ Roma Dept Comp Sci Rome Italy Univ Padua Dept Math Padua Italy

ISBN: (纸本)9781509050048

Recently, DNA-inspired online behavioral modeling and analysis techniques have been proposed and successfully applied to a broad range of tasks. In this paper, we employ a DNA-inspired technique to investigate the fundamental laws that drive the occurrence of similarities among Twitter users. The achieved results are multifold. First, we demonstrate that, despite apparently showing little to no similarities, the online behaviors of Twitter users are far from being uniformly random. Then, we perform a set of simulations to benchmark different behavioral models and to identify the models that better resemble human behaviors in Twitter. Finally, we demonstrate that the number and the extent of behavioral similarities within a group of Twitter users obey a log-normal distribution. Our results shed light on the fundamental properties that drive behaviors of groups of Twitter users, through the lenses of DNA-inspired behavioral modeling techniques. Our datasets are publicly available to the scientific community to further explore analytics of online behaviors.

关键词： DNA Twitter Biological information theory Analytical models Benchmark testing algorithm design and analysis

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