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1. |
Record Nr. |
UNINA9910830778203321 |
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Autore |
Dawson Michael R. W |
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Titolo |
Connectionism [[electronic resource] ] : A Hands-on Approach |
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Pubbl/distr/stampa |
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ISBN |
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1-4051-4387-8 |
1-280-19855-9 |
9786610198559 |
0-470-69407-6 |
1-4051-4389-4 |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (210 p.) |
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Disciplina |
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Soggetti |
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Connectionism |
Social Sciences |
Psychology |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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CONNECTIONISM; Contents; Chapter 1:Hands-On Connectionism; 1.1 Connectionism in Principle and in Practice; 1.2 The Organization of This Book; Chapter 2:The Distributed Associative Memory; 2.1 The Paired Associate Task; 2.2 The Standard Pattern Associator; 2.3 Exploring the Distributed Associative Memory; Chapter 3:The James Program; 3.1 Introduction; 3.2 Installing the Program; 3.3 Teaching a Distributed Memory; 3.4 Testing What the Memory Has Learned; 3.5 Using the Program; Chapter 4:Introducing Hebb Learning; 4.1 Overview of the Exercises; 4.2 Hebb Learning of Basis Vectors |
4.3 Hebb Learning of Orthonormal,Non-Basis VectorsAppendix - Creating mutually orthogonal vectors with Maple; Chapter 5:Limitations of Hebb Learning; 5.1 Introduction; 5.2 The Effect of Repetition; 5.3 The Effect of Correlation; Appendix - Creating the linearly independent set of vectors; Chapter 6:Introducing the Delta Rule; 6.1 Introduction; 6.2 The Delta Rule; 6.3 The Delta Rule and the Effect of Repetition; 6.4 The Delta Rule and the Effect of Correlation; Chapter 7:Distributed Networks and Human Memory; 7.1 Background on the Paired Associate Paradigm |
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7.2 The Effect of Similarity on the Distributed Associative MemoryChapter 8:Limitations of Delta Rule Learning; 8.1 Introduction; 8.2 The Delta Rule and Linear Dependency; Chapter 9:The Perceptron; 9.1 Introduction; 9.2 The Limits of Distributed Associative Memories,and Beyond; 9.3 Properties of the Perceptron; 9.4 What Comes Next; Chapter 10:The Rosenblatt Program; 10.1 Introduction; 10.2 Installing the Program; 10.3 Training a Perceptron; 10.4 Testing What the Memory Has Learned; Chapter 11:Perceptrons and Logic Gates; 11.1 Introduction; 11.2 Boolean Algebra |
11.3 Perceptrons and Two-Valued AlgebraChapter 12:Performing More Logic With Perceptrons; 12.1 Two-Valued Algebra and Pattern Spaces; 12.2 Perceptrons and Linear Separability; Appendix - The DawsonJots Font; Chapter 13:Value Units and Linear Nonseparability; 13.1 Linear Separability and Its Implications; 13.2 Value Units and the Exclusive-Or Relation; 13.3 Value Units and Connectedness; Chapter 14:Network By Problem Type Interactions; 14.1 All Networks Were Not Created Equally; 14.2 Value Units and the Two-Valued Algebra; Chapter 15:Perceptrons and Generalization; 15.1 Background |
15.2 Generalization and Savings for the 9-Majority ProblemChapter 16:Animal Learning Theory and Perceptrons; 16.1 Discrimination Learning; 16.2 Linearly Separable Versions of Patterning; Chapter 17:The Multilayer Perceptron; 17.1 Creating Sequences of Logical Operations; 17.2 Multilayer Perceptrons and the Credit Assignment Problem; 17.3 The Implications of the Generalized Delta Rule; Chapter 18:The Rumelhart Program; 18.1 Introduction; 18.2 Installing the Program; 18.3 Training a Multilayer Perceptron; 18.4 Testing What the Network Has Learned; Chapter 19:Beyond the Perceptron 's Limits |
19.1 Introduction |
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Sommario/riassunto |
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Connectionism is a "hands on" introduction to connectionist modeling through practical exercises in different types of connectionist architectures. explores three different types of connectionist architectures - distributed associative memory, perceptron, and multilayer perceptron provides a brief overview of each architecture, a detailed introduction on how to use a program to explore this network, and a series of practical exercises that are designed to highlight the advantages, and disadvantages, of each accompanied by a website at http://www.bcp.psych.ualbert |
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2. |
Record Nr. |
UNINA9911020337803321 |
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Autore |
Boase-Beier Jean |
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Titolo |
The German Language : A Linguistic Introduction |
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Pubbl/distr/stampa |
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Chichester, : John Wiley & Sons, Ltd., 2007 |
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ISBN |
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9786611310424 |
9781281310422 |
1281310425 |
9780470705681 |
047070568X |
9780470773499 |
0470773499 |
9780470775271 |
0470775270 |
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Descrizione fisica |
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1 online resource (274 p.) |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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German language |
Language / Linguistics |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di contenuto |
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Contents; Preface; Abbreviations; 1 Introduction; 2 Syntax; 3 Morphology; 4 Phonetics; 5 Phonology; 6 Lexis; 7 Stylistics; 8 Historical Background; 9 Contemporary Variation; References; Index; |
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Sommario/riassunto |
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The German Language introduces students of German to a linguistic way of looking at the language. Written from a Chomksyan perspective, this volume covers the basic structural components of the German language: syntax, morphology, phonetics, phonology, and the lexicon.:.; Explores the linguistic structure of German from current theoretical perspectives.; Written from a Chomksyan perspective, this volume covers the basic structural components of the German language: syntax, morphology, phonetics, phonology, and the lexicon.; Serves as a valuable resource for students of German language and lite |
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