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检索条件"任意字段=International Conference on Field Programmable Logic and Applications"

共 16769 条记录，以下是4871-4880 订阅

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Tradeoffs and Considerations in the Design of Accelerators for Database applications

Tradeoffs and Considerations in the Design of Accelerators f...

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IEEE 33rd international conference on Data Engineering (ICDE)

作者： Moussalli, Roger IBM Corp TJ Watson Res Ctr Accelerator Platforms Grp Yorktown Hts NY 10598 USA

ISBN: (纸本)9781509065431

General purpose processors have traditionally been favored over application-specific architectures due to the provided flexibility, standardized and simpler programming model, as well as significant reduction in development time. Fueled by the steady advances in transistor scaling, general purpose CPUs satisfied the performance needs of most applications. While CPUs were becoming ubiquitous, advances in digital storage technologies and sensing devices (cameras, microphones, etc) led to massive and sky-rocketing amounts of data being generated by devices of all scales. Extracting insights out of this Big Data introduces significant opportunities for business intelligence, though the growth of data volumes and complexity of query patterns has been increasing at a startling rate. With Moore's law ending, transistors' shrinking coming to a halt and CPU performance saturating, accelerator technologies are increasingly embraced to augment general purpose CPUs and to address performance concerns. Accelerators diverge from traditional CPU architectures in the way they utilize the available silicon resources. In particular, accelerators maximize the resources available for raw computing (ALUs, Floating Point Units) and push back the burden of correct program semantics and control to higher levels of the stack including the compiler and programming models, while focusing on a selected subset of applications. Accelerators include Application Specific Integrated Circuits (ASICs), field programmable Gate Arrays (FPGAs) and General Purpose Graphics Processing Units (GPGPUs), each with their programming model, advantages and challenges. FPGAs enable the deployment of deep custom pipelines, whereas GPGPUs provide hundreds of small processors executing in a massively parallel fashion. Compared to CPUs, accelerators attain higher performance out of the available transistors for a wide range of applications. This talk covers tradeoffs of accelerators (FPGA and GPGPU) specific to a set

关键词： accelerator acceleration hardware FPGA GPU database ConTutto CAPI NVLink

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A FPGA Based Two Level Optimized Local Filter Design for High Speed Image Processing applications

A FPGA Based Two Level Optimized Local Filter Design for Hig...

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international conference on Advances in Information and Communication Technology (ICTA)

作者： Kazmi, Majida Aziz, Arshad Akhtar, Pervez Ikram, Nassar Natl Univ Sci & Technol Dept Elect Engn PNEC H-12 Islamabad Pakistan

ISBN: (纸本)9783319490731;9783319490724

This work presents an efficient Feild programmable Gate Array (FPGA) based local filter design for portable and high speed image processing applications. It is highly optimized by using two level optimization. The first level optimization at design-level exploits tempo-spatial parallelism of filters by developing parallel/pipelined architecture. For exploiting spatial-parallelism, design computes partial results of multiple MACs in parallel and accumulates them via adder-tree for final result. Though it bears good performance aptitude but adder-tree incurs long critical path (4.713 ns) thus limits design performance. The critical path was reduced to 2.489 ns with temporal parallelism by pipelining the adder-tree. Design performance is further enhanced by deploying the second level optimization at post-implementation level where device aware floor-planning fine tunes the design. It aligns all utilized embedded resources of design on Xilinx Virtex-5 device and confines slice based logic across them. It results in packing the design within small area with reduced slice count and critical path (2.32 ns). After applying two levels of optimization, the design occupies 89 Slices, 3 DSP-Slices, 2 BRAM18 and achieves high frequency of 431.03 MHz.

关键词： Local filters Real time image processing FPGA XSG tool Floor planning

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Hacking Social Network Data Mining 15

Hacking Social Network Data Mining

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15th IEEE international conference on Intelligence and Security Informatics - Security and Big Data (ISI)

作者： Alufaisan, Yasmeen Zhou, Yan Kantarcioglu, Murat Thuraisingham, Bhavani Univ Texas Dallas Richardson TX 75083 USA

ISBN: (纸本)9781509067275

Over the years social network data has been mined to predict individuals' traits such as intelligence and sexual orientation. While mining social network data can provide many beneficial services to the user such as personalized experiences, it can also harm the user when used in making critical decisions such as employment. In this work, we investigate the reliability of applying data mining techniques on social network data to predict various individual traits. In spite of the preliminary success of such data mining applications, in this paper, we demonstrate the vulnerabilities of existing state of the art social network data mining techniques when they are facing malicious attacks. Our results indicate that making critical decisions, such as employment or credit approval, based solely on social network data mining results is still premature at this stage. Specifically, we explore Facebook likes data for predicting the traits of a Facebook user, including their political views and sexual orientation. We perform several types of malicious attacks on the predictive models to measure and understand their potential vulnerabilities. We find that existing predictive models built on social network data can be easily manipulated and suggest some countermeasures to prevent some of the proposed attacks.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Fuzzy c-Shape: A new algorithm for clustering finite time series waveforms

Fuzzy c-Shape: A new algorithm for clustering finite time se...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Fahiman, Fateme Bezdek, James C. Erfani, Sarah M. Palaniswami, Marimuthu Leckie, Christopher Univ Melbourne Dept Elect & Elect Engn Melbourne Vic Australia Univ Melbourne Dept Comp & Informat Syst Melbourne Vic Australia

ISBN: (纸本)9781509060344

The existence of large volumes of time series data in many applications has motivated data miners to investigate specialized methods for mining time series data. Clustering is a popular data mining method due to its powerful exploratory nature and its usefulness as a preprocessing step for other data mining techniques. This article develops two novel clustering algorithms for time series data that are extensions of a crisp c-shapes algorithm. The two new algorithms are heuristic derivatives of fuzzy c-means (FCM). Fuzzy c-Shapes plus (FCS+) replaces the inner product norm in the FCM model with a shape-based distance function. Fuzzy c-Shapes double plus (FCS++) uses the shape-based distance, and also replaces the FCM cluster centers with shape-extracted prototypes. Numerical experiments on 48 real time series data sets show that the two new algorithms outperform state-of-the-art shape-based clustering algorithms in terms of accuracy and efficiency. Four external cluster validity indices (the Rand index, Adjusted Rand Index, Variation of Information, and Normalized Mutual Information) are used to match candidate partitions generated by each of the studied algorithms. All four indices agree that for these finite waveform data sets, FCS++ gives a small improvement over FCS+, and in turn, FCS+ is better than the original crisp c-shapes method. Finally, we apply two tests of statistical significance to the three algorithms. The Wilcoxon and Friedman statistics both rank the three algorithms in exactly the same way as the four cluster validity indices.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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A Novel Measurement Processing Approach to the Parallel Expectation Propagation Unscented Kalman Filter 20

A Novel Measurement Processing Approach to the Parallel Expe...

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20th international conference on Information Fusion (Fusion)

作者： De Freitas, Allan Fritsche, Carsten Mihaylova, Lyudmila Gunnarsson, Fredrik Univ Sheffield Dept Automat Control & Syst Engn Sheffield S Yorkshire England Linkoping Univ Dept Elect Engn Linkoping Sweden Ericsson Res Linkoping Sweden

ISBN: (纸本)9780996452700

Advances in sensor systems have resulted in the availability of high resolution sensors, capable of generating massive amounts of data. For complex systems to run online, the primary focus is on computationally efficient filters for the estimation of latent states related to the data. In this paper a novel method for efficient state estimation with the unscented Kalman Filter is proposed. The focus is on applications consisting of a massive amount of data. From a modelling perspective, this amounts to a measurement vector with dimensionality significantly greater than the dimensionality of the state vector. The efficiency of the filter is derived from a parallel filter structure which is enabled by the expectation propagation algorithm. A novel parallel measurement processing expectation propagation unscented Kalman filter is developed. The primary advantage of the novel algorithm is in the ability to achieve computational improvements with negligible loses in filter accuracy. An example of robot localization with a high resolution laser rangefinder sensor is presented. A 47.53% decrease in computational time was exhibited for a scenario with a processing platform consisting of 4 processors, with a negligible loss in accuracy.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Efficient Modeling and Representation of Agreement in Interval-Valued Data

Efficient Modeling and Representation of Agreement in Interv...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Havens, Timothy C. Wagner, Christian Anderson, Derek T. Michigan Technol Univ Dept Elect & Comp Engn & Comp Sci Houghton MI 49931 USA Michigan Technol Univ Inst Comp & Cybersyst Houghton MI 49931 USA Univ Nottingham Sch Comp Sci LUCID Nottingham England Mississippi State Univ Dept Elect & Comp Engn Mississippi State MS 39762 USA

ISBN: (纸本)9781509060344

Recently, there has been much research into effective representation and analysis of uncertainty in human responses, with applications in cyber-security, forest and wildlife management, and product development, to name a few. Most of this research has focused on representing the response uncertainty as intervals, e.g., "I give the movie between 2 and 4 stars." In this paper, we extend upon the model-based interval agreement approach (IAA) for combining interval data into fuzzy sets and propose the efficient IAA (eIAA) algorithm, which enables efficient representation of and operation on the fuzzy sets produced by IAA (and other interval-based approaches, for that matter). We develop methods for efficiently modeling, representing, and aggregating both crisp and uncertain interval data (where the interval endpoints are intervals themselves). These intervals are assumed to be collected from individual or multiple survey respondents over single or repeated surveys;although, without loss of generality, the approaches put forth in this paper could be used for any interval-based data where representation and analysis is desired. The proposed method is designed to minimize loss of information when transferring the interval-based data into fuzzy set models and then when projecting onto a compressed set of basis functions. We provide full details of eIAA and demonstrate it on real-world and synthetic data.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Decoding Acute Pain with Combined EEG and Physiological Data 8

Decoding Acute Pain with Combined EEG and Physiological Data

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8th international IEEE/EMBS conference on Neural Engineering (NER)

作者： Lancaster, Jenessa Mano, Hiroaki Callan, Daniel Kawato, Mitsuo Seymour, Ben ATR Labs Kyoto Japan Natl Inst Informat & Commun Technol NICT Ctr Informat & Neural Networks CiNet Koganei Tokyo Japan Imperial Coll London London England Univ Cambridge Dept Engn Computat & Biol Learning Lab Cambridge England

ISBN: (纸本)9781509046034

Across neuroscience research, clinical diagnostics, and engineering applications in pain evaluation and treatment, there is a need for an objective measure of pain experience and detection when it occurs. This detector should be reliable in real-world settings using easily accessible, non-invasive data sources. We present a simple yet robust paradigm for decoding pain using neural and physiological data including electroencephalography (EEG), pulse, and skin conductance (GSR) measurements. The present study uses multivariate classification to distinguish painful events from non-painful multimodal sensory stimuli. To classify the pain response and detect relevant data attributes, we employed a sparse logistic regression (SLR) machine learning protocol with automatic feature selection. EEG input consisted of time-frequency changes under trial conditions, and physiological data included fluctuations and spikes in pulse and skin conductance. Classification averaged 70% accuracy and selected between 5 and 15 features. In our experiment, pain was induced by cold stimulation which became noxious with prolonged exposure. Due to the long, ramp-and-hold nature of the stimulus, along with individual variability in sensitivity to pain, we did not observe specific rapid evoked responses or time-locked events common across participants. However, this format more closely resembles the experience of pain conditions requiring intervention which could be facilitated by a decoding system. The results illustrate the feasibility of developing a wireless pain detection system and give insight to important temporal, spectral, and spatial EEG events and physiological indicators of pain states. Success of the classifier protocol using these parameters could lead to the creation of a closed-loop system for decoding and intervention which can be applied in engineering and medical contexts.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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PULSED POWER PROJECTS WITHIN THE NATIONAL IGNITION FACILITY 21

PULSED POWER PROJECTS WITHIN THE NATIONAL IGNITION FACILITY

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21st IEEE international conference on Pulsed Power (PPC)

作者： Le Galloudec, Bruno J. Arnold, Phillip A. Carroll, Evan G. James, Glen F. Runtal, Tony S. Acosta-Lech, Daisy M. Bettis, Tyron L. Foley, Joe D. Harkey, Allen Jones, Candace M. Lao, Norris Mcintosh, Michael E. Munguia, Miguel A. Nghiem, Huy V. Schwedler, Dave A. Taylor, Davis R. Lawrence Livermore Natl Lab Livermore CA 94551 USA AKIMA Infrastruct Serv LLC Livermore CA 94551 USA

ISBN: (纸本)9781509057481

The National Ignition Facility (NIF), the world's most energetic laser, focuses 192 laser beams onto a pea-sized target inside a 10-meter diameter target chamber. While relying on its three major pulsed power systems to generate more than 1.8 MJ of UV light, NIF benefits from several other pulsed power applications, ranging from the low power front end of the laser to diagnostics for a broad spectrum of physics experiments. In this paper, we will discuss our recent development efforts and provide a projection into the future of the NIF pulsed power projects, including a diode-pumped Nd: glass amplifier, an RF tool for monitoring the health of the amplifier capacitor banks and ongoing solid-state pulser development that allows reliable triple pulsing of the Plasma Electrode Pockels Cell (PEPC). We will also describe developments that may contribute to the success of the future physics experiments including the design of a pulsed power system that will provide a uniform 30-50 T magnetic field at the target, and a fast, gated cathode for streak cameras, permitting significant reduction in the effects of background light.

关键词： Capacitors Semiconductor lasers Switches Cameras logic gates Power lasers Plasmas

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Interactive Web Application for Exploring Matrices of Neural Connectivity 8

Interactive Web Application for Exploring Matrices of Neural...

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8th international IEEE/EMBS conference on Neural Engineering (NER)

作者： Caldwell, David J. Wu, Jing Casimo, Kaitlyn Ojemann, Jeffrey G. Rao, Rajesh P. N. Univ Washington Dept Bioengn Seattle WA 98105 USA CSNE Seattle WA 98105 USA Univ Washington Grad Program Neurosci Seattle WA 98105 USA Univ Washington Dept Neurol Surg Seattle WA 98105 USA Univ Washington Dept Comp Sci Seattle WA 98105 USA

ISBN: (纸本)9781509046034

We present here a browser-based application for visualizing patterns of connectivity in 3D stacked data matrices with large numbers of pairwise relations. Visualizing a connectivity matrix, looking for trends and patterns, and dynamically manipulating these values is a challenge for scientists from diverse fields, including neuroscience and genomics. In particular, high-dimensional neural data include those acquired via electroencephalography (EEG), electrocorticography (ECoG), magnetoencephalography (MEG), and functional MRI. Neural connectivity data contains multivariate attributes for each edge between different brain regions, which motivated our lightweight, open source, easy-to-use visualization tool for the exploration of these connectivity matrices to highlight connections of interest. Here we present a client-side, mobile-compatible visualization tool written entirely in HTML5/JavaScript that allows in-browser manipulation of user-defined files for exploration of brain connectivity. Visualizations can highlight different aspects of the data simultaneously across different dimensions. Input files are in JSON format, and custom Python scripts have been written to parse MATLAB or Python data files into JSON-loadable format. We demonstrate the analysis of connectivity data acquired via human ECoG recordings as a domain-specific implementation of our application. We envision applications for this interactive tool in fields seeking to visualize pairwise connectivity.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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Musculoskeletal Model for Simultaneous and Proportional Control of 3-DOF Hand and Wrist Movements from EMG Signals 8

Musculoskeletal Model for Simultaneous and Proportional Cont...

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8th international IEEE/EMBS conference on Neural Engineering (NER)

作者： Pan, Lizhi Crouch, Dustin Huang, He NC State Univ NCSU UNC Dept Biomed Engn Raleigh NC 27695 USA Univ North Carolina Chapel Hill Chapel Hill NC 27599 USA

ISBN: (纸本)9781509046034

Recently, we proposed a musculoskeletal model to simultaneously predict motion along metacarpophalangeal (MCP) and wrist flexion/extension degrees-of-freedom (DOFs) from surface electromyography (EMG) signals. Since wrist pronation/supination is also functionally important, we extended the musculoskeletal model to simultaneously estimate wrist pronation/supination in addition to wrist and MCP flexion/extension from surface EMG signals of six corresponding muscles. Kinematic data and surface EMG signals were acquired synchronously from an able-bodied subject. The subject was instructed to perform single-DOF movements at fixed or variable speed and simultaneous 3-DOF movements at variable speed during the experiment. The model included six Hill-type actuators, each with a contractile element and a parallel elastic element. Seven parameters were optimized for each of the six muscles. The average Pearson's correlation coefficient (r) between measured and estimated joint angles across all trials was 0.91, indicating high positive correlation. The results demonstrated that the proposed model could feasibly simultaneously estimate 3-DOF joint angles during either independent-DOF or simultaneous 3-DOF movements from EMG signals. Our results promote the potential of the EMG-driven musculoskeletal model for clinical applications, such as prosthesis control.

关键词： Estimation field programmable gate arrays OFDM Modulation Filtration Clocks Signal processing algorithms

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