Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence, 1st Edition

  • Yingxu Wang
  • Published By:
  • ISBN-10: 1605669032
  • ISBN-13: 9781605669038
  • DDC: 006.3
  • Grade Level Range: College Freshman - College Senior
  • 375 Pages | eBook
  • Original Copyright 2009 | Published/Released May 2010
  • This publication's content originally published in print form: 2009

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Cognitive informatics is a multidisciplinary field that acts as the bridge between natural science and information science. Specifically, it investigates the potential applications of information processing and natural intelligence to science and engineering disciplines.This collection, entitled "Discoveries and Breakthroughs in Cognitive Informatics and Natural Intelligence", provides emerging research topics in cognitive informatics research with a focus on such topics as reducing cognitive overload, real-time process algebra, and neural networks for iris recognition, emotion recognition in speech, and the classification of musical chords.

Table of Contents

Front Cover.
Title Page.
Copyright Page.
Editorial Advisory Board.
List of Reviewers.
Table of Contents.
Detailed Table of Contents.
1: A Computational Cognitive Model of the Brain.
2: A Cognitive Approach to the Mechanism of Intelligence.
3: Reducing Cognitive Overload by Meta-Learning Assisted Algorithm Selection.
4: Analyzing Learning Methods in a Functional Environment.
5: Humans and Machines: Nature of Learning and Learning of Nature.
6: On Cognitive Properties of Human Factors and Error Models in Engineering and Socialization.
7: User —Centered Interactive Data Mining.
8: On Concept Algebra: A Denotational Mathematical Structure for Knowledge and Software Modeling.
9: On System Algebra: A Denotational Mathematical Structure for Abstract System Modeling.
10: RTPA: A Denotational Mathematics for Manipulating Intelligent and Computational Behaviors.
11: A Denotational Semantics of Real—Time Process Algebra (RTPA).
12: An Operational Semantics of Real-Time Process Algebra (RTPA).
13: Formal Modeling and Specification of Design Patterns Using RTPA.
14: Deductive Semantics of RTPA.
15: On the Big-R Notation for Describing Interative and Recursive Behaviors.
16: Formal RTPA Models for a Set of Meta—Cognitive Processes of the Brain.
17: Unifying Rough Set Analysis and Formal Concept Analysis Based on a Logic Approach to Granular Computing.
18: On Foundations and Applications of the Paradigm of Granular Rough Computing.
19: Robust Independent Component Analysis for Cognitive Informatics.
20: A Relative Fractal Dimension Spectrum for a Perceptual Complexity Measure.
21: 3D Object Classification Based on Volumetric Parts.
22: Modeling Underwater Structures.
23: A Novel Plausible Model for Visual Perception.
24: An Efficient and Automatic Iris Recognition System Using ICM Neural Network.
25: Neural Networks for Language Independent Emotion Recognition in Speech.
26: An Analysis of Internal Representations for Two Artificial Neural Networks that Classify Musical Chords.
27: Foundation and Classification of Nonconventional Neural Units and Paradigm of Nonsynaptic Neural Interaction.
28: Scaling Behavior of Maximal Repeat Distributions in Genomic Sequences: A Randomize Test Follow Up Study.
Compilation of References.
About the Contributors.