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Table of Contents
Prologue; Acknowledgments; Contents; Introduction; 1 Shannonian Versus Semantic Information and Cognition; 1.1 Shannonian Information; 1.2 Semantic Information; 1.3 Applications to Cognition; 1.4 Semantic Information Enters in Disguise; 1.5 Toward Information Adaptation; 2 Information Versus Data; 2.1 General Discussion; 2.1.1 On Knowledge; 2.2 Mathematical Formulation. Some Basic General Concepts; 2.2.1 Information Deflation; 2.2.1.1 Information Inflation; 2.3 Data, Information and Meaning. How Are These Related?; 3 The Empirical Basis of Information Adaptation; 3.1 Introduction
3.2 Deconstruction&hx2013Reconstruction; 3.3 Analysis&hx2013; Synthesis; 3.4 Hybrid Images and the Meaning of the Deconstruction/Analysis Process; 3.4.1 Hybrid Images; 3.4.2 A Model of Hybrid Images; 3.5 Computational Models: Link Between Bottom-Up and Top-Down; 4 A Complexity Theory Approach to Information; 4.1 Complexity Theory; 4.2 Complexity and Information; 4.3 Forms of Communication; 4.3.1 Complexity, Cognition and Information Adaptation; 4.4 A Communication System of a Complex Adaptive Cognitive System; 5 On Synergetic Computers and Other Machines; 5.1 Can Machines Think?
5.2 Trivial Versus Non-Trivial Machines in Relation to Simple Versus Complex Systems5.3 The Synergetic Computer; 5.3.1 Motivation; 5.3.2 Self-organization; 5.3.3 From Pattern Formation to Pattern Recognition; 5.3.4 SIRN
Synergetic Inter-Representation Networks; 6 Pattern Recognition as a Paradigm for Information Adaptation; 6.1 Pattern Recognition; 6.2 Pattern Recognition of Faces as Information Adaptation by Means of Deflation; 6.3 Pattern Recognition of Caricatures as Information Adaptation; 6.4 Pattern Recognition as Information Adaptation by Means of Inflation
7 From General Principles of Information Adaptation to Concrete Specific Models7.1 Introductory Remarks; 7.2 Task: Define Probability of Patterns; 7.3 Information Deflation via Correlation Functions 2026; 7.4 Need for Models: Prototype Patterns; 7.5 Learning; 7.6 Recognition; 7.7 Some More Properties of the SC; 7.8 On Attention Parameters; 7.9 Time Dependent Data Set; 7.10 Machinery; 7.10.1 First Step: Preprocessing; 7.10.2 Second Step: Learning; 7.10.3 Third Step: Recognition; 7.11 The HMAX Model: Outline
Relation to Information Adaptation; 7.11.1 The Invariance Problem
7.11.2 The HMAX Model7.11.3 Information Adaptation; 8 Some Further Applications and Discussions of Information Adaptation; 8.1 A Baby Learning the Concept ``Mother''; 8.2 Information Adaptation to an Approaching Object; 8.3 Adapting the Face of the City to Humans' Information Processing Capabilities; Concluding Notes; References
3.2 Deconstruction&hx2013Reconstruction; 3.3 Analysis&hx2013; Synthesis; 3.4 Hybrid Images and the Meaning of the Deconstruction/Analysis Process; 3.4.1 Hybrid Images; 3.4.2 A Model of Hybrid Images; 3.5 Computational Models: Link Between Bottom-Up and Top-Down; 4 A Complexity Theory Approach to Information; 4.1 Complexity Theory; 4.2 Complexity and Information; 4.3 Forms of Communication; 4.3.1 Complexity, Cognition and Information Adaptation; 4.4 A Communication System of a Complex Adaptive Cognitive System; 5 On Synergetic Computers and Other Machines; 5.1 Can Machines Think?
5.2 Trivial Versus Non-Trivial Machines in Relation to Simple Versus Complex Systems5.3 The Synergetic Computer; 5.3.1 Motivation; 5.3.2 Self-organization; 5.3.3 From Pattern Formation to Pattern Recognition; 5.3.4 SIRN
Synergetic Inter-Representation Networks; 6 Pattern Recognition as a Paradigm for Information Adaptation; 6.1 Pattern Recognition; 6.2 Pattern Recognition of Faces as Information Adaptation by Means of Deflation; 6.3 Pattern Recognition of Caricatures as Information Adaptation; 6.4 Pattern Recognition as Information Adaptation by Means of Inflation
7 From General Principles of Information Adaptation to Concrete Specific Models7.1 Introductory Remarks; 7.2 Task: Define Probability of Patterns; 7.3 Information Deflation via Correlation Functions 2026; 7.4 Need for Models: Prototype Patterns; 7.5 Learning; 7.6 Recognition; 7.7 Some More Properties of the SC; 7.8 On Attention Parameters; 7.9 Time Dependent Data Set; 7.10 Machinery; 7.10.1 First Step: Preprocessing; 7.10.2 Second Step: Learning; 7.10.3 Third Step: Recognition; 7.11 The HMAX Model: Outline
Relation to Information Adaptation; 7.11.1 The Invariance Problem
7.11.2 The HMAX Model7.11.3 Information Adaptation; 8 Some Further Applications and Discussions of Information Adaptation; 8.1 A Baby Learning the Concept ``Mother''; 8.2 Information Adaptation to an Approaching Object; 8.3 Adapting the Face of the City to Humans' Information Processing Capabilities; Concluding Notes; References