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检索条件"任意字段=Conference on High Performance Algorithms and Software for Nonlinear Optimization"

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An Adaptive Filter Based Fuzzy Logic Controller Incorporating MTPA for IPMSM Drives

An Adaptive Filter Based Fuzzy Logic Controller Incorporatin...

引用

Pacific-Asia conference on Knowledge Engineering and software Engineering (KESE)

作者： Hanan M. Dawood Habbi Muhammad Ilyas Menhas Huang Surong Department of Automation and Control Shanghai University Shanghai China

This paper presents an adaptive filter for fuzzy-logic controller for vector controlled based speed controller incorporating with a maximum torque per ampere (MTPA) of an interior permanent magnet synchronous motor (IPMSM) drive to minimize the torque ripple. The design and optimization of the FLC, infinite impulse response (IIR) filter and the adaptation algorithms are presented. Different operating conditions have been studied including various speed commands with nominal and changes in the load torque. A fuzzy logic controller (FLC) for the IPMSM drive has been found to maintain high performance standards with a much simpler and less computation implementation. An open loop adaptive filter is used to give a fast response while retaining a good noise canceling properties. The simulation was done by using Matlab/Simulink. The simulated results confirmed that the considerable torque ripple reduction can be achieved by utilizing an adaptive filter with FLC.

关键词： Adaptive filters Fuzzy logic Torque control IIR filters Computational modeling Permanent magnet motors Algorithm design and analysis Design optimization Magnetic separation Open loop systems

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A high performance algorithm for scheduling and hardware-software partitioning on MPSoCs

A high performance algorithm for scheduling and hardware-sof...

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International conference on Design and Technology of Integrated Systems in Nanoscale Era (DTIS)

作者： Hassan Youness Mohammed Hassan Keishi Sakanushi Yoshinori Takeuchi Masaharu Imai Ashraf Salem Abdel-Moniem Wahdan Mohammed Moness Department of Information Systems Engineering Osaka University Osaka Japan Mentor Graphics Cairo Egypt Department of Computers and Systems Engineering Ain Shams University Cairo Egypt Minia University Minia Egypt

Multi-processor system-on-chip (MPSoC) is an integrated circuit containing multiple cores that implements most of the functionality of a complex electronic system and some other components like FPGA/ASIC on single chip. The most crucial things in such like these systems are the performance, energy, power and area optimization. Moreover, scheduling the tasks of an application on to the processors (cores) and HW/SW partitioning are inter-dependent in the traditional design space exploration process. In this paper, we propose an algorithm to produce the optimality of scheduling and optimize the number of cores that can be used and also reduce the overall execution time and number of buses on the chip by using efficient hardware-software co-design partitioning technique. The viability and potential of the proposed algorithm is demonstrated by extensive experimental results to conclude that the proposed algorithm is an efficient scheme to obtain the optimality of scheduling and partitioning with hard and large task graph problems.

关键词： Partitioning algorithms Scheduling algorithm Processor scheduling Optimal scheduling Hardware software performance Systems engineering and theory System-on-a-chip Field programmable gate arrays software tools

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Towards User-centric Network optimization Engine

Towards User-centric Network Optimization Engine

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IEEE Annual Communications Society Sensor, Mesh and Ad Hoc Communications and Networks SECON Workshops

作者： Elena Meshkova Andreas Achtzehn Janne Riihijarvi Petri Mahonen Department of Wireless Networks RWTH Aachen University Aachen Germany

The increasing diversity of applications as well as the introduction of new wireless last-mile techniques imposes additional challenges on both terminals and entire networks. A user- and application-centric approach to networking is expected result in better user satisfaction and allow for new market opportunities for network infrastructure providers. However, this architectural view leads to increased network complexity and, therefore, requires new autonomic network management and optimization techniques. In this article we focus on one aspect of this domain: network protocol stack optimization for wireless access networks. We provide a design of an autonomic engine that aims to select and adjust parameters of the communication stack in order to achieve high user satisfaction using minimal reconfiguration time. It relies on two basic constructs: utility-based performance assessment, and metaheuristic algorithms for fast optimization. We demonstrate that such an engine allows for efficient autonomous switching between different wireless access methods and consequently significantly improves the performance of the user device using cross-layer parameter optimization.

关键词： Engines Access protocols Runtime Application software Wireless application protocol Wireless networks Wireless sensor networks Wireless mesh networks Market opportunities Communication switching

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Hardware-aware model of sigma-delta cellular neural network

Hardware-aware model of sigma-delta cellular neural network

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European conference on Circuit Theory and Design, ECCTD

作者： Hisashi Aomori Yuki Naito Tsuyoshi Otake Nobuaki Takahashi Ichiro Matsuda Susumu Itoh Mamoru Tanaka Department of Electrical Engineering Tokyo University of Science Noda Chiba Japan Department of Information and Communication Sciences Sophia University Chiyoda Tokyo Japan Department of Software Science Tamagawa University Machida Tokyo Japan

The sigma-delta cellular neural network (SD-CNN) is a complete framework of a spatial domain sigma-delta modulator, and has a very high image reconstruction (AD-to-DA) performance. In this architecture, the A-template, given by a 2D low pass filter (LPF), is used for a digital to analogue converter (DAC), the C-template works as an integrator, and the nonlinear output function is for the bilevel output. By exploiting to the nonlinear optimization ability of CNN spatio-temporal dynamics, optimal binary and reconstruction image can be obtained. However, in the conventional SD-CNN, the Gaussian LPF, whose coefficients are real number, is used as the A-template. This filter coefficients requirement is one of major factors that restricts a hardware implementation. In this paper, a SD-CNN having hardware-friendly filter coefficients is proposed. Moreover its AD and DA performance is confirmed by some experiments.

关键词： Delta-sigma modulation Cellular neural networks Noise shaping Quantization Image reconstruction Hardware Neural networks Filters Signal reconstruction Image processing

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Comparing fine-grained performance on the Ambric MPPA against an FPGA

Comparing fine-grained performance on the Ambric MPPA agains...

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International conference on Field Programmable Logic and Applications

作者： Brad Hutchings Brent Nelson Stephen West Reed Curtis NSF Center of High-Performance Reconfigurable Computing (CHREC) Department of Electrical and Computer Engineering Brigham Young University Provo UT USA

A simple image-processing application is implemented on the Ambric MPPA and an FPGA, using a similar implementation for both devices. FPGAs perform extremely well on this kind of application and provide a good benchmark for comparison. The Ambric implementation starts out with a naive implementation and proceeds through several design optimizations until it reaches a maximum frame rate of 164 FPS (512 times 512 images) which turns out to be approximately 7times slower than the FPGA. The final Ambric implementation uses only 18 of 336 available processors, achieves more than sufficient performance for realtime embedded applications, and has excess processors to use for implementing additional algorithms. After introducing the image processing application and its implementation on both devices, the paper compares and contrasts the intrinsic, general characteristics of Ambric MPPA and FPGA devices.

关键词： Field programmable gate arrays Random access memory Application specific integrated circuits Application software Digital signal processing Read-write memory Bandwidth Integrated circuit interconnections high performance computing Design optimization

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Real-Time Task Assignment in Heterogeneous Distributed Systems with Rechargeable Batteries

Real-Time Task Assignment in Heterogeneous Distributed Syste...

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International conference on Advanced Information Networking and Applications (AINA)

作者： Jian Lin Albert M.K. Cheng Rashmi Kumar Department of Computer Science University of Houston TX USA

ISBN: (纸本)9781424440009

Real-time systems are one of the fields of computing where major benefits are expected from the increasing availability of multiprocessor technology. Heterogeneous computing environments, which utilize different high-performance machines interconnected via a high speed communication system, are well suited to the large, computation intensive, real-time or non-real-time applications. Nowadays, many of the systems in these environments are powered by rechargeable batteries. Scheduling real-time tasks on these rechargeable systems is an important issue which has been studied in the literatures. In this paper, we explore the task assignment problem on heterogeneous distributed system with rechargeable batteries. Our techniques to solve the problem are based on four heuristics, namely Minimum Schedule Length (MSL), min-min schedule length (MmSL), genetic algorithm (GA), and ant colony optimization (ACO). While the modifications of the MSL, MmSL and GA approaches from their original implementation are somewhat straight-forward, we design a novel structure using ACO. The performance comparisons of these four techniques are performed and the results are discussed. This paper not only gives a suggestion on which heuristic is best suited for the specific problem, but also provides a new direction to solve similar problems.

关键词： Real time systems Batteries Processor scheduling Distributed computing Application software Computer science Computer networks Power system interconnection Genetic algorithms Ant colony optimization

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Low Power Embedded Speech Enhancement System Based on a Fixed-Point DSP

Low Power Embedded Speech Enhancement System Based on a Fixe...

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IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Yu Cai Jianping Yuan Xiaochuan Ma Chaohuan Hou Laboratory of digital system integration Institute of Acoustics Chinese Academy and Sciences Beijing China

In this paper, we introduce a practical real-time speech enhancement system based on the TI TMS320VC5509A digital signal processor (DSP). A stereo audio codec is used as the analog input/output (I/O). The algorithm for noise reduction is an improved and optimized spectral-subtraction method. The detailed design of the hardware and software is described and the experiments show an improved performance. Low power consumption and high efficiency make the whole system suitable for portable devices.

关键词： Speech enhancement Digital signal processing Real time systems Digital signal processors Codecs Signal processing algorithms Noise reduction optimization methods Design methodology Hardware

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Genetic adaptive scheme design for high initial gain problems in a L2-gain state feedback controller

Genetic adaptive scheme design for high initial gain problem...

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IEEE conference on Control Technology and Applications (CCTA)

作者： Yao-Chu Hsueh Shun-Feng Su Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan

This paper is a study of a genetic adaptive scheme design for L 2 -gain state feedback controllers. It is known that the design of the initial gain producer of the L 2 -gain state feedback controller (LC) is a difficult problem. The derivative-free optimization, the genetic algorithm, is utilized to resolve the high initial gain problem of LC for a class of nonlinear systems. It is a novel approach for robust control and can be considered as a special application of genetic algorithms. A real-value genetic algorithm with on-line characteristics is designed to search a suitable control gain of LC under auxiliary searching conditions and a specific cost function. The specific cost function is designed under Lyapunov stable theory. Since the system has the L 2 -gain control properties, then the system states are bounded in an assignable region so that the stability of the initial system is guaranteed. Thus, the system stability of any searched results is guaranteed. Besides, due to the assignable L 2 -gain attenuation level, the search space of the genetic algorithm is definable. The search target of the genetic algorithm is to find a suitable set of the initial gain so that the system can have required initial control performance. The simulation results indeed demonstrate the effectiveness of the proposed approach.

关键词： Genetic algorithms State feedback Cost function Control systems Stability Programmable control Adaptive control nonlinear systems Robust control Algorithm design and analysis

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Particle Swarm Optimized Unscented Particle Filter for Target Tracking

Particle Swarm Optimized Unscented Particle Filter for Targe...

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Congress on Image and Signal Processing, CISP

作者： Shuying Yang Qin Ma Wenjuan Huang Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Key Laboratory of Computer Vision and System Ministry of Education Tianjin University of Technology Tianjin China

In this paper, a novel particle swarm optimized (PSO) unscented particle filter (PSO-UPF) algorithm is proposed for target tracking. Unscented particle filter (UPF) can obtain the better sequential importance sampling than the traditional PF algorithm. Then we use PSO to optimize the state equation of UPF. So that the particle set can tend to the high likelihood region before the weights updated, thereby the impoverishment of particles can be overcome. While, the optimization process makes the particles which far away from the true state tend to the region where the true state has a greater probability of emergence, it can enhance the effect of each particle. Experiment results show that our modified particle filter algorithm uses fewer particles than the general particle filters and its performance outperforms them. And the accuracy of video tracking is improved.

关键词： Particle swarm optimization Particle filters Target tracking Signal processing algorithms Educational technology Monte Carlo methods nonlinear dynamical systems Laboratories Computer vision Equations

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Semi-Supervised Random Forests

Semi-Supervised Random Forests

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International conference on Computer Vision (ICCV)

作者： Christian Leistner Amir Saffari Jakob Santner Horst Bischof Institute for Computer Graphics and Vision Graz University of Technology Austria

Random Forests (RFs) have become commonplace in many computer vision applications. Their popularity is mainly driven by their high computational efficiency during both training and evaluation while still being able to achieve state-of-the-art accuracy. This work extends the usage of Random Forests to Semi-Supervised Learning (SSL) problems. We show that traditional decision trees are optimizing multi-class margin maximizing loss functions. From this intuition, we develop a novel multi-class margin definition for the unlabeled data, and an iterative deterministic annealing-style training algorithm maximizing both the multi-class margin of labeled and unlabeled samples. In particular, this allows us to use the predicted labels of the unlabeled data as additional optimization variables. Furthermore, we propose a control mechanism based on the out-of-bag error, which prevents the algorithm from degradation if the unlabeled data is not useful for the task. Our experiments demonstrate state-of-the-art semi-supervised learning performance in typical machine learning problems and constant improvement using unlabeled data for the Caltech-101 object categorization task.

关键词： Semisupervised learning Iterative algorithms Computer vision Application software Computational efficiency Decision trees Annealing Error correction Machine learning algorithms Degradation

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