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Titlebook: Evolvable Systems: From Biology to Hardware; 6th International Co J. Manuel Moreno,Jordi Madrenas,Jordi Cosp Conference proceedings 2005 Sp

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书目名称Evolvable Systems: From Biology to Hardware
副标题6th International Co
编辑J. Manuel Moreno,Jordi Madrenas,Jordi Cosp
视频video
丛书名称Lecture Notes in Computer Science
图书封面Titlebook: Evolvable Systems: From Biology to Hardware; 6th International Co J. Manuel Moreno,Jordi Madrenas,Jordi Cosp Conference proceedings 2005 Sp
描述The flying machines proposed by Leonardo da Vinci in the fifteenth century, the se- reproducing automata theory proposed by John von Neumann in the middle of the twentieth century and the current possibility of designing electronic and mechanical systems using evolutionary principles are all examples of the efforts made by humans to explore the mechanisms present in biological systems that permit them to tackle complex tasks. These initiatives have recently given rise to the emergent field of b- inspired systems and evolvable hardware. The inaugural workshop, Towards Evolvable Hardware, took place in Lausanne in October 1995, followed by the successive events of the International Conference on Evolvable Systems: From Biology to Hardware, held in Tsukuba (Japan) in October 1996, in Lausanne (Switzerland) in September 1998, in Edinburgh (UK) in April 2000, in Tokyo (Japan) in October 2001, and in Trondheim (Norway) in March 2003. Following the success of these past events the sixth international conference was aimed at presenting the latest developments in the field, bringing together researchers who use biologically inspired concepts to implement real systems in artificial intellige
出版日期Conference proceedings 2005
关键词ant colony systems; architecture; bio-inspired computing; bioinformatics; embryonic hardware; evolution; e
版次1
doihttps://doi.org/10.1007/11549703
isbn_softcover978-3-540-28736-0
isbn_ebook978-3-540-28737-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2005
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Consensus-Based Evaluation for Fault Isolation and On-line Evolutionary Regenerationbility can be achieved by exploiting population diversity during all phases of the fault handling process. A new paradigm for online EH regeneration using Genetic Algorithms (GAs) called Consensus Based Evaluation (CBE) is developed where the performance of individuals is assessed based on broad con
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Hardware Fault-Tolerance Within the POEtic Systemf a hardware platform capable of implementing bio-inspired systems, in digital hardware. In particular, the final hardware device, while similar to other FPGAs, was designed with a number of novel features which facilitate faulttolerance. These include dynamic reconfiguration and on-chip re-programm
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Evolvable Hardware System at Extreme Low Temperaturesment (EE). In addition to hardening-by-process and hardening-bydesign, “hardening-by-reconfiguration”, when applicable, could be used to mitigate drifts, degradation, or damage on electronic devices (chips) in EE, by using re-configurable devices and an adaptive self-reconfiguration of their circuit
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Intrinsic Evolution of Sorting Networks: A Novel Complete Hardware Implementation for FPGAsion are also implemented on the same FPGA. We evolved sorting networks up to N = 28. The evolution of the largest sorting networks requires 10 hours in FPGA running at 100 MHz. The experiments were performed using COMBO6 card.
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An Evolvable Image Filter: Experimental Evaluation of a Complete Hardware Implementation in FPGAve an image filter in a few seconds if corrupted and original images are supplied by user. The architecture is generic and can easily be modified to realize other evolvable systems. COMBO6 card with Xilinx Virtex xc2v3000 FPGA is used as a target platform.
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Operational Amplifiers: An Example for Multi-objective Optimization on an Analog Evolvable Hardware g FPTA. A multi-objective evolutionary algorithm is developed, in order to be able to include various specifications of an operational amplifier into the process of circuit synthesis. Additionally, the presented algorithm is designed to preserve the diversity within the population troughout evolutio
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