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Future Directions for Intelligent Systems and Information Sciences

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Cover of 'Future Directions for Intelligent Systems and Information Sciences'

Table of Contents

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    Book Overview
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    Chapter 1 ECOS — Evolving Connectionist Systems — a New/Old Paradigm for On-line Learning and Knowledge Engineering
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    Chapter 2 Artificial Life Technology for Adaptive Information Processing
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    Chapter 3 Evolving ANN Controllers for Smart Mobile Robots
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    Chapter 4 A Simulation Environment for the Manipulation of Naturally Variable Objects
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    Chapter 5 Behavior-Decision Fuzzy Algorithm for Autonomous Mobile Robot
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    Chapter 6 Modelling the Emergence of Speech and Language Through Evolving Connectionist Systems
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    Chapter 7 Discovering the Visual Signature of Painters
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    Chapter 8 Multimodal Interactions with Agents in Virtual Worlds
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    Chapter 9 Virtual BioBots
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    Chapter 10 Future Directions for Neural Networks and Intelligent Systems from the Brain Imaging Research
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    Chapter 11 Quantum Neural Networks
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    Chapter 12 Suprathreshold Stochastic Resonance in a Neuronal Network Model: a Possible Strategy for Sensory Coding
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    Chapter 13 Information Science and Bioinformatics
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    Chapter 14 Neural Network System for Promoter Recognition
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    Chapter 15 Granular Computing : An Introduction
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    Chapter 16 A New Paradigm Shift from Computation on Numbers to Computation on Words on an Example of Linguistic Database Summarization
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    Chapter 17 Hybrid Intelligent Decision Support Systems and Applications for Risk Analysis and Discovery of Evolving Economic Clusters in Europe
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    Chapter 18 Intelligent Resource Management Through the Constrained Resource Planning Model
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    Chapter 19 Evaluative Studies of Fuzzy Knowledge Discovery through NF Systems
Attention for Chapter 11: Quantum Neural Networks
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Chapter title
Quantum Neural Networks
Chapter number 11
Book title
Future Directions for Intelligent Systems and Information Sciences
Published by
Physica, Heidelberg, January 2000
DOI 10.1007/978-3-7908-1856-7_11
Book ISBNs
978-3-79-082470-4, 978-3-79-081856-7
Authors

Alexandr A. Ezhov, Dan Ventura, Ezhov, Alexandr A., Ventura, Dan

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X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 27 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 5 19%
Researcher 4 15%
Student > Ph. D. Student 4 15%
Professor 1 4%
Other 1 4%
Other 2 7%
Unknown 10 37%
Readers by discipline Count As %
Computer Science 8 30%
Physics and Astronomy 6 22%
Engineering 3 11%
Medicine and Dentistry 1 4%
Unknown 9 33%