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Rough-Neural Computing

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Cover of 'Rough-Neural Computing'

Table of Contents

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    Book Overview
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    Chapter 1 Elementary Rough Set Granules: Toward a Rough Set Processor
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    Chapter 2 Rough-Neural Computing: An Introduction
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    Chapter 3 Information Granules and Rough-Neural Computing
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    Chapter 4 A Rough-Neural Computation Model Based on Rough Mereology
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    Chapter 5 Knowledge-Based Networking in Granular Worlds
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    Chapter 6 Adaptive Aspects of Combining Approximation Spaces
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    Chapter 7 Algebras from Rough Sets
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    Chapter 8 Approximation Transducers and Trees: A Technique for Combining Rough and Crisp Knowledge
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    Chapter 9 Using Contextually Closed Queries for Local Closed-World Reasoning in Rough Knowledge Databases
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    Chapter 10 On Model Evaluation, Indexes of Importance, and Interaction Values in Rough Set Analysis
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    Chapter 11 New Fuzzy Rough Sets Based on Certainty Qualification
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    Chapter 12 Toward Rough Datalog: Embedding Rough Sets in Prolog
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    Chapter 13 On Exploring Soft Discretization of Continuous Attributes
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    Chapter 14 Rough-SOM with Fuzzy Discretization
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    Chapter 15 Biomedical Inference: A Semantic Model
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    Chapter 16 Fundamental Mathematical Notions of the Theory of Socially Embedded Games: A Granular Computing Perspective
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    Chapter 17 Fuzzy Games and Equilibria: The Perspective of the General Theory of Games on Nash and Normative Equilibria
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    Chapter 18 Rough Neurons: Petri Net Models and Applications
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    Chapter 19 Information Granulation and Approximation in a Decision-Theoretical Model of Rough Sets
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    Chapter 20 Intelligent Acquisition of Audio Signals, Employing Neural Networks and Rough Set Algorithms
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    Chapter 21 An Approach to Imbalanced Data Sets Based on Changing Rule Strength
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    Chapter 22 Rough-Neural Approach to Testing the Influence of Visual Cues on Surround Sound Perception
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    Chapter 23 Handwritten Digit Recognition Using Adaptive Classifier Construction Techniques
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    Chapter 24 From Rough through Fuzzy to Crisp Concepts: Case Study on Image Color Temperature Description
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    Chapter 25 Information Granulation and Pattern Recognition
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    Chapter 26 Computational Analysis of Acquired Dyslexia of Kanji Characters Based on Conventional and Rough Neural Networks
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    Chapter 27 WaRS: A Method for Signal Classification
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    Chapter 28 A Hybrid Model for Rule Discovery in Data
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Title
Rough-Neural Computing
Published by
Springer Berlin Heidelberg, December 2012
DOI 10.1007/978-3-642-18859-6
ISBNs
978-3-64-262328-8, 978-3-64-218859-6
Editors

Pal, Sankar K., Polkowski, Lech, Skowron, Andrzej

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Mendeley readers

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Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 1 100%
Readers by discipline Count As %
Computer Science 1 100%

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