检索结果-内蒙古大学图书馆

2010 International Conference on Reconfigurable Computing and FPGAs, ReConFig 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9780769543147

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. However, the PSO algorithm suffers from premature convergence and high elapsed time when solving multimodal and large scale engineering problems. This problem becomes an evident drawback for embedded applications in which the microcontrollers often operates at low computational capacity. This paper proposes a hardware implementation of a parallel self-adaptive PSO algorithm based on an attractive-repulsive scheme and using the efficient floating-point arithmetic which performs computations with large dynamic range and high precision. The parallel capabilities of the PSO are exploited by implementing parallel particles directly in hardware in order to decrease the running time. In addition, the attractive-repulsive technique avoids the premature convergence problem by self-adapting the swarm behavior according to its diversity. Synthesis and simulation results for benchmark test problems were performed, demonstrating the correctness of the proposed architectures. Finally, an elapsed time comparison between the hardware and software implementations shows the suitableness of the proposed architecture for embedded applications. © 2010 IEEE.

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

Hardware-based parallel firefly algorithm for embedded applications

Hardware-based parallel firefly algorithm for embedded appli...

引用

2013 NASA/ESA Conference on Adaptive Hardware and systems, AHS 2013

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos Santos Coelho, Leandro Ayala-Rincón, Mauricio Electronics Engineering Graduate Program Faculty of Gama University of Brasilia Brasilia DF Brazil Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia DF Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Departments of Computer Science and Mathematics University of Brasilia Brasilia DF Brazil

ISBN: (纸本)9781467363839

The firefly algorithm (FA) is a new population-based metaheuristic bioinspired on the behavior of the flashing characteristics of fireflies. As a population-based algorithm, the FA suffers from large execution times specifically for embedded optimization problems with computational limitations. For reducing execution times we propose a hardware parallel architecture of the FA algorithm that facilitates the implementation in Field programmable Gate Arrays (FPGAs). In addition, this work proposes the application of the opposition-based learning (OBL) approach to the FA algorithm. The respective hardware implementation (HPOFA) was mapped into a Virtex5 FPGA device and numerical experiments using four well-known benchmark problems demonstrate that the opposition-based approach allows the FA algorithm to improve its functionality, preserving the swarm diversity and avoiding the premature convergence problem. Synthesis results point out that the HPOFA architecture is effectively mapped in hardware and is suitable for embedded applications. © 2013 IEEE.

关键词： Parallel architectures

来源：评论

学校读者我要写书评

暂无评论

Hardware Particle Swarm Optimization with passive congregation for embedded applications

Hardware Particle Swarm Optimization with passive congregati...

引用

Southern Conference on programmable Logic

作者： Muñoz, Daniel M. Llanos, Carlos H. Coelho, Leandro Dos S. Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424488483

Achieving high performance optimization algorithms for embedded applications can be very challenging, particularly when several requirements such as high accuracy computations, short elapsed time, area cost, low power consumption and portability must be accomplished. This paper proposes a hardware implementation of the Particle Swarm Optimization algorithm with passive congregation (HPPSOpc), which was developed using several floating-point arithmetic libraries. The passive congregation is a biological behavior which allows the swarm to preserve its integrity, balancing between global and local search. The HPPSOpc architecture was implemented on a Virtex5 FPGA device and validated using two multimodal benchmark problems. Synthesis, simulation and execution time results demonstrates that the passive congregation approach is a low cost solution for solving embedded optimization problems with a high performance. © 2011 IEEE.

关键词： Digital arithmetic

来源：评论

学校读者我要写书评

暂无评论

Accelerating the Shuffled Frog Leaping algorithm by parallel implementations in FPGAs

Accelerating the Shuffled Frog Leaping algorithm by parallel...

引用

2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACG University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Meta-heuristics are efficient techniques for solving large scale optimization problems in which traditional mathematical techniques are impractical or provide sub-optimal solutions. The Shuffled Frog Leaping algorithm (SFLA) is a stochastic iterative method, bio-inspired on the memetic evolution of a group of frogs when seeking for food, which combines the social behavior-based of the particle swarm optimization technique (PSO) and the global information exchange of memetic algorithms. However, the SFLA algorithm suffers on large execution times, being this problem clearly evident when solving complex optimization problems for embedded applications. This drawback can be overcome by exploiting the parallel capabilities of the SFLA. This paper proposes a hardware parallel implementation of the SFLA algorithm (HPSFLA) using FPGAs (Field programmable gate Arrays) and the efficient floating-point arithmetic. The proposed architecture allows the SFLA to improve the functionality of the algorithm as well as to decrease the execution times by implementing parallel frogs and parallel memeplexes. Three well-known benchmark problems have been used to validate the implemented algorithm and simulation results demonstrate that the HPSFLA speeds-up by factors of 362, 727 and 211 a C-code implementation using an embedded microprocessor for the Sphere, Rastrigin and Rosenbrock benchmarks problems, respectively. Synthesis, simulation and execution time results demonstrate the effectiveness of the proposed HPSFLA architecture for embedded optimization systems. © 2010 IEEE.

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

Fast image compression using over-complete ICAMM

Fast image compression using over-complete ICAMM

引用

作者： Peng, Chih-Cheng Kao, Chih-Hong Hsieh, Sheng-Ping Program in Electrical and Communications Engineering Feng Chia University Taichung Taiwan Aeronautical Systems Research Division Chung-Shan Institute of Science and Technology Taiwan Department of Electrical Engineering National Chung-Hsing University Taichung Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9781424474530

This paper presents a new over complete ICAMM to make decomposition the basis for low-bit high-speed image compression on image sub-blocks. Although the over complete independent component analysis basic number is much larger than the original data dimension, most of the coefficients will be zero after performing the basis transform so that this algorithm reaches the low bit-rate compression goal. The over complete independent component effect approximates the wavelet basis functions. This is different from the discrete cosine function and wavelet function in that the independent component is relevant to the data itself. When using the over complete independent component analysis to decompose the image sub-blocks, it can divide self-adaptive learning into several subgroups based on the different characteristics of the text images. Each subgroup has a set of corresponding over complete independent components. In this way, it can be more efficient to reduce the bit rate use. At the same time the information in the subgroup can also be used in image transmission based on the different encodings. The experimental results show that our proposed approach achieves low bit-rate image compression. ©ICROS.

关键词： Image compression

来源：评论

学校读者我要写书评

暂无评论

Opposition-based shuffled PSO with passive congregation applied to FM matching synthesis

Opposition-based shuffled PSO with passive congregation appl...

引用

IEEE Congress on Evolutionary Computation

作者： Munoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincon, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424478347

Synthesis of musical instruments or human voice is a time consuming process which requires theoretical and experimental knowledge about the synthesis engine. Commonly, performers need to deal with synthesizer interfaces and a process of trial and error for creating musical sounds similar to a target sound. This drawback can be overcome by adjusting automatically the synthesizer parameters using optimization algorithms. In this paper a hybrid particle swarm optimization (PSO) algorithm is proposed to solve the frequency modulation (FM) matching synthesis problem. The proposed algorithm takes advantage of a shuffle process for exchanging information between particles and applies the selective passive congregation and the opposition-based learning approaches to preserve swarm diversity. Both approaches for injecting diversity are based on simple operators, preserving the easy implementation philosophy of the particle swarm optimization. The proposed hybrid particle swarm optimization algorithm was validated for a three-nested FM synthesizer, which represents a 6-dimensional multimodal optimization problem with strong epistasis. Simulation results revealed that the proposed algorithm presented promising results in terms of quality of solutions. © 2011 IEEE.

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

Comparison between two FPGA implementations of the particle swarm optimization algorithm for high-performance embedded applications

Comparison between two FPGA implementations of the particle ...

引用

2010 IEEE 5th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2010

作者： Muñoz, Daniel M. Llanos, Carlos H. Dos S. Coelho, Leandro Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGPES Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781424464388

Particle Swarm Optimization (PSO) algorithms have been proposed to solve engineering problems that require to find an optimal point of operation. There are several embedded applications which requires to solve online optimization problems with a high performance. However, the PSO suffers on large execution times, and this fact becomes evident when using Reduced Instruction Set Computer (RISC) microprocessors in which the operational frequencies are low in comparison with the high operational frequencies of traditional personal computers (PCs). This paper compares two hardware implementations of the parallel PSO algorithm using an efficient floating-point arithmetic which perform computations with large dynamic range and high precision. The full-parallel and the partially-parallel PSO architectures allow the parallel capabilities of the PSO to be exploited in order to decrease the running time. Three well-known benchmark test functions have been used to validate the hardware architectures and a comparison in terms of cost in logic area, quality of the solution and performance is reported. In addition, a comparison of the execution time between the hardware and two C-code software implementations, based on a Intel Core Duo at 1.6GHz and a embedded Microblaze microprocessor at 50MHz, are presented. © 2010 IEEE.

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

Accelerating the artificial bee colony algorithm by hardware parallel implementations

Accelerating the artificial bee colony algorithm by hardware...

引用

2012 IEEE 3rd Latin American Symposium on Circuits and systems, LASCAS 2012

作者： Muñoz, Daniel M. Llanos, Carlos H. Coelho, Leandro Dos S. Ayala-Rincón, Mauricio Department of Mechanical Engineering Automation and Control Group/GRACO University of Brasilia Brasilia D.F. Brazil Industrial and Systems Engineering Graduate Program LAS/PPGEPS Pontifical Catholic University of Parana Curitiba Parana Brazil Department of Computer Science and Mathematics University of Brasilia Brasilia D.F. Brazil

ISBN: (纸本)9781467312080

Artificial bee colony (ABC) is an optimization algorithm inspired on the intelligent behavior of honey bee swarms. It is suitable to be applied when mathematical techniques are impractical or provide suboptimal solutions. As a population-based algorithm, the ABC suffers on large execution times specifically for embedded optimization problems with computational limitations. For that we propose a hardware parallel architecture of the opposition-based ABC algorithm (HPOABC) that facilitates the implementation in Field programmable Gate Arrays (FPGAs). Numerical simulations using four well-known benchmark problems demonstrate that the opposition-based approach allows the algorithm to improve its functionality, preserving the swarm diversity. Additionally, synthesis results point outs that the HPOABC architecture is effectively mapped in hardware and is suitable for embedded applications. © 2012 IEEE.

关键词： Global optimization

来源：评论

学校读者我要写书评

暂无评论

Optimizing Deployment of Multiple Decoys to Enhance Ship Survivability

Optimizing Deployment of Multiple Decoys to Enhance Ship Sur...

引用

2008 American control Conference (ACC), vol.5

作者： K.R. Akhil D. Ghose S. Koteswara Rao Systems Engineering Program Cornell University USA Guidance Control and Decision Systems laboratory (GCDSL) Department of Aerospace Engineering Indian Institute of Science Bangalore India NSTL Vizag India

In this paper we model a scenario where a ship uses decoys to evade a hostile torpedo. We address the problem of enhancing ship survivability against enemy torpedoes by using single and multiple decoy deployments. We incorporate deterministic ship maneuvers and realistic constraints on turn rates, field of view, etc in the model. We formulate the objective function to quantify and maximize the survivability of the ship in terms of maximizing the intercept time. We introduce the concept of optimal deployment regions, same side deployment, and zig-zag deployment strategies. Finally, we present simulation results.

关键词： Marine vehicles Equations Acceleration Weapons Intelligent systems Underwater tracking Protection Geometry Solid modeling Radio frequency

来源：评论

学校读者我要写书评

暂无评论

Asymptotic behavior of the indicator function in the inverse problem of the wave equation for media with multiple types of cavities

arXiv

引用

arXiv 2024年

作者： Kawashita, Mishio Kawashita, Wakako Mathematics Program Graduate School of Advanced Science and Engineering Hiroshima University Higashihiroshima739-8526 Japan Electrical Systems and Control Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University Higashihiroshima739-8527 Japan

In this paper, the inverse problem of the wave equation by the enclosure method for a medium with multiple types of cavities is discussed. In the case considered here, the sign of the indicator function of the enclosure method is not determined and sign cancellation may occur, resulting in loss of information. By examining the top terms of the indicator function in detail, we show that the shortest distance to the cavities can be obtained even in such a *** Codes 35R30, 35L05, 35B40, 78A46 Copyright © 2024, The Authors. All rights reserved.

关键词： Wave equations

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：