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2013 IFIP/IEEE 21st International Conference on Very Large Scale Integration, VLSI-SoC 2013

作者： Artes, Antonio Ayala, Jose L. Fasthuber, Robert Raghavan, Praveen Catthoor, Francky Computer Architecture and Automation Department Complutense University of Madrid Madrid Spain Smart Systems and Energy Technology Unit IMEC Leuven Belgium

ISBN: (纸本)9781479905249

The reduction of the energy consumption in the domain of the embedded systems is becoming the most important design goal due to the increasing use of battery powered consumer devices. Previous research has pointed out the instruction memory organisation as one of the major sources of energy consumption of the embedded systems. Due to this fact, the introduction of any enhancement in this component of the system becomes crucial in order to decrease this energy bottleneck. The purpose of this paper is to present a highlevel energy analysis of the loop buffer schemes that exist in the embedded systems. The crucial energy analysis that is presented in this paper not only proposes a method to evaluate different loop buffer schemes for a certain application, but also guides embedded systems designers to make the correct decision in the trade-offs that exist between the energy budget, the required performance, and the area cost of the embedded system. Experimental results used in this analysis show that, the search of energy savings (up to 76%) has to take into account the performance penalty, the area cost, and the impact of the implementation technology in order to choose the most suitable enhancement that has to be introduced in the instruction memory organisation from the point of view of the energy consumption. © 2013 IEEE.

关键词： Embedded systems

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Synchronization of fractional-order chaotic systems based on the fractional-order sliding mode controller

Synchronization of fractional-order chaotic systems based on...

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第三十二届中国控制会议

作者： YAN Xiaomei SHANG Ting ZHAO Xiaoguo Faculty of Automation and Information Engineering Xi'an University of Technology School of Mechanical and Electrical Engineering Xi'an University of Architecture and Technology Department of Electrical and Computer Engineering The Ohio State UniversityColumbus 43210USA

ISBN: (纸本)9789881563835

For synchronization of fractional-order chaotic systems,this paper presents a novel fractional-order sliding mode controller,in which fractional calculus is introduced to the sliding mode *** on Lyapunov stability theory and fractional-order system's stability theorem,stability analysis is *** examples are given respectively,which include synchronization of two identical fractional-order systems(Chen-Chen) and synchronization of two non-identical fractional-order systems(Chen-Liu).Numerical simulations illustrate the effectiveness of the proposed controller.

关键词： Synchronization fractional-order chaotic system sliding mode control

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An evolutionary methodology for automatic design of finite state machines

An evolutionary methodology for automatic design of finite s...

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15th Annual Conference on Genetic and Evolutionary Computation, GECCO 2013

作者： Manuel Colmenar, J. Cuesta-Infante, Alfredo Risco-Martín, José L. Hidalgo, J. Ignacio C.E.S. Felipe II Complutense University of Madrid 28300 Aranjuez Spain Dept. of Computer Architecture and Automation Complutense University of Madrid 28040 Madrid Spain

ISBN: (纸本)9781450319645

We propose an evolutionary flow for finite state machine in- ference through the cooperation of grammatical evolution and a genetic algorithm. This coevolution has two main ad- vantages. First, a high-level description of the target prob- lem is accepted by the flow, being easier and affordable for system designers. Second, the designer does not need to de- fine a training set of input values because it is automatically generated by the genetic algorithm at run time. Our exper- iments on the sequence recognizer and the vending machine problems obtained the FSM solution in 99.96% and 100% of the optimization runs, respectively.

关键词： Genetic programming

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Construction of multi-scale common brain networks based on DICCCOL

Construction of multi-scale common brain networks based on D...

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23rd International Conference on Information Processing in Medical Imaging, IPMI 2013

作者： Ge, Bao Guo, Lei Zhu, Dajiang Zhang, Tuo Hu, Xintao Han, Junwei Liu, Tianming College of Physics and Information Technology Shaanxi Normal University Xi'an China School of Automation Northwestern Polytechnical University Xi'an China Cortical Architecture Imaging and Discovery Lab. Department of Computer Science University of Georgia Athens GA United States

ISBN: (纸本)9783642388675

Modeling the human brain as a network has been widely considered as a powerful approach to investigating the brain's structural and functional systems. However, many previous approaches focused on a single scale of brain network and the multi-scale nature of brain networks has been rarely explored yet. This paper put forward a novel framework to construct multi-scale common networks of brains via multi-scale spectral clustering of fiber connections among DICCCOLs. Specifically, the recently developed and publicly released DICCCOLs provide the nodal structural and functional correspondence across individuals, and thus the employed multi-scale spectral clustering algorithm divided the DICCCOL landmarks and their connections into sub-networks with correspondences on multiple scales. Experimental results showed the promise of the constructed multi-scale networks in applications of structural and functional connectivity mapping. As an application example, these multi-scale networks are used to guide the identification of multi-scale common fiber bundles across individuals and to facilitate the bundle's functional role analysis, which could enable other tract-based and network-based analyses in the future. © 2013 Springer-Verlag.

关键词： Clustering algorithms

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Energy impact in the design space exploration of loop buffer schemes in embedded systems

Energy impact in the design space exploration of loop buffer...

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IFIP International Conference on Very Large Scale Integration (VLSI-SoC)

作者： Antonio Artes Jose L. Ayala Robert Fasthuber Praveen Raghavan Francky Catthoor Computer Architecture and Automation Department Complutense University of Madrid Madrid Spain Smart Systems and Energy Technology Unit IMEC Leuven Belgium

关键词： Energy consumption Embedded systems Benchmark testing Memory management Parallel processing Discrete wavelet transforms Hardware

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Very short term pitch angle optimization in wind turbines: A machine learning approach

Very short term pitch angle optimization in wind turbines: A...

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2013 4th International Conference on Power Engineering, Energy and Electrical Drives, POWERENG 2013

作者： Yesilbudak, Mehmet Kabalci, Ersan Sagiroglu, Seref Colak, Ilhami Department of Electronics and Automation Vocational College of Haci Bektas Veli Nevsehir University Nevsehir Turkey Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nevsehir University Nevsehir Turkey Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey Department of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Turkey

ISBN: (纸本)9781467363921

This paper proposes a pitch angle forecasting model based on the k-nearest neighbor classification. Air temperature, atmosphere pressure, wind direction, wind speed, rotor speed and wind power parameters were represented as a 6-dimensional attribute tuple in the forecasting model. Euclidean, Manhattan and Minkowski distance metrics for measuring the proximity between training and test tuples, mean absolute, mean absolute percentage, and normalized root mean square error metrics for measuring the forecasting accuracy were embedded into the forecasting model. The k-nearest neighbor classifier with Manhattan distance metric for k=1 achieved MAE, MAPE and NRMSE as 0.001°, 0.245% and 0.324%, respectively as the best forecasting accuracy. However, as the worst forecasting accuracy, MAE, MAPE and NRMSE were achieved as 0.015°, 3.236% and 2.613%, respectively for Minkowski distance metric and k=10. © 2013 IEEE.

关键词： Wind turbines

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Free weight exercises recognition based on dynamic time Warping of acceleration data

Communications in Computer and Information Science

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Communications in computer and Information Science 2013年 355卷 178-185页

作者： Li, Chuanjiang Fei, Minrui Hu, Huosheng Qi, Ziming School of Mechanical Engineering and Automation Shanghai Key Laboratory of Power Station Automation Technology Shanghai University 200072 China College of Information Mechanical and Electrical Engineering Shanghai Normal University Shanghai 200234 China Department of Computer Science University of ESSEX Colchester CO4 3SQ United Kingdom School of Architecture Building and Eng. Otago Polytechnic Dunedin 9054 New Zealand

To maximize training effects in free weight exercises, people need to remember repetitions of each type of exercises, which is tedious and difficult. Recognizing exercises type and counting automatically can overcome this problem, and multiple accelerometers were used in the existing exercises recognition. This paper presents a new recognition method based on one triaxial accelerometer, in which a filtered acceleration data stream is divided into time series with unequal length for peak analysis instead of conventional fixed length window. Based on this time series, Dynamic Time Warping (DTW) is deployed to recognize weight exercise types. 3D Euclidean distance and Itakura parallelogram constraint region are used to improve recognition performance. A reference template is set up for each class based on many examples instead of one in the conventional way. The proposed procedures are compared with other popular methods with both the user-dependent protocol and the userindependent protocol. Results show that proposed approach is feasible and can achieve good performance. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Accelerometers

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Very short term pitch angle optimization in wind turbines: A machine learning approach

Very short term pitch angle optimization in wind turbines: A...

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International Conference on Power Engineering, Energy and Electrical Drives, POWERENG

作者： Mehmet Yesilbudak Ersan Kabalci Seref Sagiroglu Ilhami Colak Department of Electronics and Automation Vocational College of Haci Bektas Veli Nevsehir University Nevsehir Turkey Department of Electrical and Electronics Engineering Faculty of Engineering and Architecture Nevsehir University Nevsehir Turkey Department of Computer Engineering Faculty of Engineering Gazi University Ankara Turkey Department of Electrical and Electronics Engineering Faculty of Technology Gazi University Ankara Turkey

关键词： Forecasting Measurement Wind turbines Predictive models Wind speed Atmospheric modeling Control systems

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Fault diagnosis of gearbox based on wavelet transforms and neural networks

Fault diagnosis of gearbox based on wavelet transforms and n...

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2011 International Conference on Mechanical Engineering, Materials and Energy, ICMEME 2011

作者： Zhang, Guangbin Ge, Yunjian Liu, Yongjiu Department of Automation University of Science and Technology of China Hefei 230026 China Institute of Intelligent Machines Chinese Academy of Sciences Hefei 230031 China Department of Computer Engineering Anhui University of Architecture Hefei 230601 China

ISBN: (纸本)9783037853405

In this paper, an actual system based on wavelet transform and artificial neural networks was established to diagnose different types of fault in a gearbox. As a key step, biorthogonal wavelet was used to denoise in feature extraction of signals because of its properties of compact support, high vanishing moment and symmetry. Consequently, a multi-layer perceptron network were designed to diagnose the fault status with feature vectors as inputs. In order to improve the network learning speed and stability, Levenberg-Marquardt algorithm was used to train the network. The present classification accuracy indicates the effectiveness of gearbox failure diagnosis. © (2012) Trans Tech Publications, Switzerland.

关键词： Failure analysis

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Minimum Time Search for Lost Targets using Cross Entropy Optimization

Minimum Time Search for Lost Targets using Cross Entropy Opt...

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IEEE/RSJ International Conference on Intelligent Robotics and Systems

作者： Pablo Lanillos Eva Besada-Portas Gonzalo Pajares José J. Ruz Computer Architecture and Automation Department (DACYA) Complutense University Madrid Spain Software Engineering and Artificial Intelligence Department Complutense University Madrid Spain

ISBN: (纸本)9781467317375

This paper formulates and proposes a discrete solution for the problem of finding a lost target under uncertainty in minimum time (Minimum Time Search). Given a searching region where some information about the target is known but uncertain (i.e. location and dynamics), and a searching agent with constrained dynamics, we provide two decision making algorithms that optimizes the agent actions to find the target in a minimum time. The problem is faced as a discrete optimization: the actions and the sensor are discrete, and the target probabilistic model is described over a graph, where each vertex contains the target's location probability information and each edge defines the agent possible actions. We revisit the mathematical model of the optimal search problem and we propose a novel approach to include the time into the decision making by reinterpreting it as a maximum discounted time reward problem. The optimal decision plan for the agent is obtained by solving this non convex discrete problem using the cross entropy method. By performing statistical simulations we show how the target is found in minimum time.

关键词： Lost Targets using a searching agent is obtained Cross Entropy Targets Agents PROBLEM SOLUTION discrete element decision making

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