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Evolvable Systems: From Biology to Hardware

Overview of attention for book
Cover of 'Evolvable Systems: From Biology to Hardware'

Table of Contents

  1. Altmetric Badge
    Book Overview
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    Chapter 34 Iconic learning in networks of logical neurons
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    Chapter 35 Hardware requirements for fast evaluation of functions learned by Adaptive Logic Networks
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    Chapter 36 FPGA as a key component for reconfigurable system
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    Chapter 37 Phylogeny, ontogeny, and epigenesis: Three sources of biological inspiration for softening hardware
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    Chapter 38 Promises and challenges of Evolvable hardware
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    Chapter 39 Designing evolware by cellular programming
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    Chapter 40 Online autonomous evolware
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    Chapter 41 Speeding-up digital ecologies evolution using a hardware emulator: Preliminary results
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    Chapter 42 Challenges of evolvable systems: Analysis and future directions
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    Chapter 43 Functional organisms growing on silicon
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    Chapter 44 Logical universality and self-reproduction in reversible cellular automata
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    Chapter 45 Data compression based on Evolvable hardware
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    Chapter 46 ATM cell scheduling by function level evolvable hardware
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    Chapter 47 An evolutionary robot navigation system using a gate-level evolvable hardware
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    Chapter 48 Genetic evolution of a logic circuit which controls an autonomous mobile robot
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    Chapter 49 Autonomous robot with evolving algorithm based on biological systems
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    Chapter 50 Memory-based neural network and its application to a mobile robot with evolutionary and experience learning
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    Chapter 51 Multiple genetic algorithm processor for hardware optimization
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    Chapter 52 NGEN: A massively parallel reconfigurable computer for biological simulation: Towards a self-organizing computer
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    Chapter 53 Architecture of cell array neuro-processor
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    Chapter 54 Special-purpose brainware architecture for data processing
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    Chapter 55 Evolvable Hardware: An outlook
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    Chapter 56 Reuse, parameterized reuse, and hierarchical reuse of substructures in evolving electrical circuits using genetic programming
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    Chapter 57 Machine learning approach to gate-level Evolvable Hardware
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    Chapter 58 Evolvable systems in hardware design: Taxonomy, survey and applications
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    Chapter 59 From some tasks to biology and then to hardware
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    Chapter 60 Adaptive equalization of digital communication channels using Evolvable Hardware
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    Chapter 61 An evolved circuit, intrinsic in silicon, entwined with physics
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    Chapter 62 Through the labyrinth evolution finds a way: A silicon ridge
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    Chapter 63 Hardware evolution system introducing dominant and recessive heredity
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    Chapter 64 CAM-Brain: A new model for atr's cellular automata based artificial brain project
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    Chapter 65 Evolution of a 60 decibel op amp using genetic programming
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    Chapter 66 Evolution of binary decision diagrams for digital circuit design using genetic programming
Attention for Chapter 38: Promises and challenges of Evolvable hardware
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

wikipedia
2 Wikipedia pages

Readers on

mendeley
49 Mendeley
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Chapter title
Promises and challenges of Evolvable hardware
Chapter number 38
Book title
Evolvable Systems: From Biology to Hardware
Published in
Lecture notes in computer science, June 2005
DOI 10.1007/3-540-63173-9_38
Book ISBNs
978-3-54-063173-6, 978-3-54-069204-1
Authors

Xin Yao, Tetsuya Higuchi, Masaya Iwata, Weixin Liu, Yao, Xin, Higuchi, Tetsuya

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 4%
Spain 1 2%
Italy 1 2%
Germany 1 2%
Unknown 44 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 18 37%
Student > Master 8 16%
Researcher 6 12%
Professor 5 10%
Professor > Associate Professor 5 10%
Other 3 6%
Unknown 4 8%
Readers by discipline Count As %
Engineering 23 47%
Computer Science 19 39%
Social Sciences 2 4%
Agricultural and Biological Sciences 1 2%
Unknown 4 8%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 October 2014.
All research outputs
#7,452,489
of 22,783,848 outputs
Outputs from Lecture notes in computer science
#2,485
of 8,124 outputs
Outputs of similar age
#20,272
of 57,174 outputs
Outputs of similar age from Lecture notes in computer science
#14
of 62 outputs
Altmetric has tracked 22,783,848 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 57,174 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 38th percentile – i.e., 38% of its contemporaries scored the same or lower than it.