The Illusion of Reality was conceived during my tenure as director of the newly established Division of Information Science and Technology at the National Science Foundation in 1979-1981 as a partial response to the need for a textbook for students, both in and out of government, that would pro vide a comprehensive view of information science as a fundamental constitu ent of other more established disciplines with a unity and coherence distinct from computer science, cognitive science, and library science although it is related to all of them. Driven by the advances of information technology,…mehr
The Illusion of Reality was conceived during my tenure as director of the newly established Division of Information Science and Technology at the National Science Foundation in 1979-1981 as a partial response to the need for a textbook for students, both in and out of government, that would pro vide a comprehensive view of information science as a fundamental constitu ent of other more established disciplines with a unity and coherence distinct from computer science, cognitive science, and library science although it is related to all of them. Driven by the advances of information technology, the perception of information science has progressed rapidly: today it seems well understood that information processing biological organisms and informa tion processing electronic machines have something basic in common that may subsume the theory of computation, as well as fundamental parts of physics. This book is primarily intended as a text for an advanced undergraduate or a graduate introduction to information science. The multidisciplinary nature of the subject has naturally led to the inclusion of a considerable amount of background material in various fields. The reader is likely to fmd the treat ment relatively oversimplified in fields with which he is familiar and, perhaps, somewhat heavier sailing in less familiar waters. The theme of common principles among seemingly unrelated applications provides the connective tissue for the diverse topics covered in the text and, I hope, justifies the variable level of presentation. Some of the material appears here for the first time.
1 Introduction Purpose of This Book and History of the Subject.- 1.1 The Subject Matter of Information Science.- 1.2 History of Information Science.- 1.3 Information and Thermodynamics.- 1.4 Early Development of Sensory Physiology and Psychophysics.- 1.5 Selective Omission of Information.- 1.6 The Quantum Mechanical Theory of Measurement.- 1.7 Early Development of Electrical Communication Engineering and Its Formalization as Information Theory.- 1.8 The Development of Computers.- 1.9 The Information Processing Viewpoint in Psychology.- 1.10 Some Principles of Information Science.- 2 Mathematics of Information Measurement.- 2.1 Purpose of This Chapter.- 2.2 The Information Content of a Measurement.- 2.3 Formal Derivation of the Information Content of a Measurement.- 2.4 Application of the Information in a Measurement to Psychophysics.- 2.5 The Probability Interpretation of the Information Measure.- 2.6 The Uncertainty Principle for Measurement.- 2.7 Conservation of Information.- 2.8 Information Content of a Calculation.- 2.9 Generalization of the Notion of an Information Measure.- 2.10 Excursus on the Theory of Groups and Their Invariants.- CHAPTER3 Physical Measurements and Information.- 3.1 Purpose of This Chapter.- 3.2 The Uncertainty Principle of Heisenberg.- 3.3 Theory of Measurement and the Conservation of Information.- 3.4 Entropy and Information.- 3.5 Information, Energy, and Computation.- 3.6 The Physics of Information Processing.- 3.7 What Is Life?.- 3.8 The Theory of Measurement and Information.- 3.9 Time's Arrow.- 3.10 Information Gain and Special Relativity.- 4 Principles of information-Processing Systems arid Signal Detection.- 4.1 Purpose of This Chapter.- 4.2 Hierarchical Organization of Information-Processing Systems.- 4.3 Extremal Systems and the Cost of Information.- 4.4 Signals, Modulation, and Fourier Analysis.- 4.5 Shannon's Sampling Theorem and the Uncertainty Relation.- 5 Biological Signal Detection and Information Processing.- 5.1 Purpose of This Chapter.- 5.2 Interconvertibility of Information Representations.- 5.3 Human Vision.- 5.4 Continuity of the Visual Manifold.- 5.5 Stabilized Vision.- 5.6 Information Content of Contours.- 5.7 Subjective Contours.- 5.8 Models of Human Color Perception.- 5.9 The Gaze as a Flying-Spot Scanner.- 5.10 Biological Echolocation Systems.- 5.11 A Catalog of Visual Illusions.- 5.12 Hierarchical Sampling Systems and the Duality between Noise and Aliasing.- 6 Pattern Structure and Learning.- 6.1 Purpose of This Chapter.- 6.2 Texture and Textons.- 6.3 Edge Detection, Uncertainty, and Hierarchy.- 6.4 Pattern Structure and Learning.- Biographical Sketches.- References.
1 Introduction Purpose of This Book and History of the Subject.- 1.1 The Subject Matter of Information Science.- 1.2 History of Information Science.- 1.3 Information and Thermodynamics.- 1.4 Early Development of Sensory Physiology and Psychophysics.- 1.5 Selective Omission of Information.- 1.6 The Quantum Mechanical Theory of Measurement.- 1.7 Early Development of Electrical Communication Engineering and Its Formalization as Information Theory.- 1.8 The Development of Computers.- 1.9 The Information Processing Viewpoint in Psychology.- 1.10 Some Principles of Information Science.- 2 Mathematics of Information Measurement.- 2.1 Purpose of This Chapter.- 2.2 The Information Content of a Measurement.- 2.3 Formal Derivation of the Information Content of a Measurement.- 2.4 Application of the Information in a Measurement to Psychophysics.- 2.5 The Probability Interpretation of the Information Measure.- 2.6 The Uncertainty Principle for Measurement.- 2.7 Conservation of Information.- 2.8 Information Content of a Calculation.- 2.9 Generalization of the Notion of an Information Measure.- 2.10 Excursus on the Theory of Groups and Their Invariants.- CHAPTER3 Physical Measurements and Information.- 3.1 Purpose of This Chapter.- 3.2 The Uncertainty Principle of Heisenberg.- 3.3 Theory of Measurement and the Conservation of Information.- 3.4 Entropy and Information.- 3.5 Information, Energy, and Computation.- 3.6 The Physics of Information Processing.- 3.7 What Is Life?.- 3.8 The Theory of Measurement and Information.- 3.9 Time's Arrow.- 3.10 Information Gain and Special Relativity.- 4 Principles of information-Processing Systems arid Signal Detection.- 4.1 Purpose of This Chapter.- 4.2 Hierarchical Organization of Information-Processing Systems.- 4.3 Extremal Systems and the Cost of Information.- 4.4 Signals, Modulation, and Fourier Analysis.- 4.5 Shannon's Sampling Theorem and the Uncertainty Relation.- 5 Biological Signal Detection and Information Processing.- 5.1 Purpose of This Chapter.- 5.2 Interconvertibility of Information Representations.- 5.3 Human Vision.- 5.4 Continuity of the Visual Manifold.- 5.5 Stabilized Vision.- 5.6 Information Content of Contours.- 5.7 Subjective Contours.- 5.8 Models of Human Color Perception.- 5.9 The Gaze as a Flying-Spot Scanner.- 5.10 Biological Echolocation Systems.- 5.11 A Catalog of Visual Illusions.- 5.12 Hierarchical Sampling Systems and the Duality between Noise and Aliasing.- 6 Pattern Structure and Learning.- 6.1 Purpose of This Chapter.- 6.2 Texture and Textons.- 6.3 Edge Detection, Uncertainty, and Hierarchy.- 6.4 Pattern Structure and Learning.- Biographical Sketches.- References.
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