50 years after the perceptron, 25 years after PDP : neural computation in language sciences / / topic editors: Julien Mayor, Pablo Gomez, Franklin Chang and Gary Lupyan |
Autore | Pablo Gomez |
Pubbl/distr/stampa | Frontiers Media SA, 2014 |
Descrizione fisica | 1 online resource (180 pages) : illustrations; digital, PDF file(s) |
Collana |
Frontiers Research Topics
Frontiers in Psychology |
Soggetto topico |
Perceptrons
Computational linguistics Computational linguistics - Research Language acquisition Cognition |
Soggetto non controllato |
computational linguistics
language acquisition probabilistic cognition Recurrent networks connectionism computational modeling word learning interactive processing Speech Perception language processing |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910131531303321 |
Pablo Gomez
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Frontiers Media SA, 2014 | ||
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Lo trovi qui: Univ. Federico II | ||
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Computational models of cognitive processes : proceedings of the 13th Neural Computation and Psychology Workshop, San Sebastian, Spain, 12-14 July 2012 / / editors, Julien Mayor (University of Geneva, Switzerland), Pablo Gomez (De Paul University, USA) |
Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
Descrizione fisica | 1 online resource (287 p.) |
Disciplina | 612.8/233 |
Altri autori (Persone) |
MayorJulien
GomezPablo (Pablo Alegria) |
Collana | Progress in neural processing |
Soggetto topico |
Neural networks (Neurobiology)
Cognition Neural stimulation |
Soggetto genere / forma | Electronic books. |
ISBN | 981-4458-84-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Preface; Contents; Language; Modelling Language - Vision Interactions in the Hub and Spoke Framework; 1. Introduction; 2. Virtues of the Hub & Spoke Framework; 3. A Hub & Spoke Model of Language Mediated Visual Attention; 3.1. Language Mediated Visual Attention & The Visual World Paradigm; 3.2. Method; 3.2.1. Network; 3.2.2. Artificial Corpus; 3.2.3. Training; 3.2.4. Pre-Test; 3.3. Results; 3.3.1. Simulation of Phonological Effects; 3.3.2. Simulation of Visual Effects; 3.3.3. Simulation of Semantic Effects; 4. Discussion; References
Modelling Letter Perception: The Effect of Supervision and Top-Down Information on Simulated Reaction Times1. Introduction; 2. Method; 2.1. Simulations; 2.2. Neural Network Algorithms; 2.2.1. Restricted Boltzmann Machines; 2.2.2. Training a Deep-Belief Network; 2.2.3. Delta-Rule and Back-Propagation; 2.2.4. Simulating Reaction Times; 2.3. Human Reaction Time Data; 3. Results; 4. Conclusions; References; Encoding Words into a Potts Attractor Network; 1. Introduction; 2. BLISS: The Training Language; 3. Potts Attractor Network: a Simplified Model of the Cortex 4. Implementation of Word Representation in the Potts Network4.1. Semantic Representation; 4.2. Syntactic Representation; 5. Discussion; References; Unexpected Predictability in the Hawaiian Passive; 1. Introduction; 2. Data; 3. Methods; 3.1. Pre-processing; 3.2. The model; 3.3. Error measures; 3.3.1. Mean Squared Error; 3.3.2. Classification Error; 3.4. Baseline estimates; 3.4.1. Random guess: adaptation to the range of target values; 3.4.2. Weighted guess: adaptation to the distribution of target values; 4. Results; 5. Conclusion; Acknowledgements; References Difference Between Spoken and Written Language Based on Zipf 's Law Analysis1. Introduction; 2. Methods; 3. Results; 3.1. Log- log frequency vs. rank plots; 3.2. Five most frequent words in 1-, 2-, and 3-grams; 3.3. Exponent of rank; 4. Discussion; Acknowledgments; References; Reading Aloud is Quicker than Reading Silently: A Study in the Japanese Language Demonstrating the Enhancement of Cognitive Processing by Action; 1. Introduction; 2. Material and Methods; 3. Results; 4. Discussion; References; Development; Testing a Dynamic Neural Field Model of Children's Category Labelling 1. Introduction2. Simulation; 2.1. Dynamic Neural Fields; 2.2. Categorisation by Shared Features; 2.3. Method; 2.3.1. Architecture; 2.3.2. Stimuli; 2.3.3. Design and Procedure; 2.3.4. Results and Discussion; 3. Experiment; 3.1. Method; 3.1.1. Participants; 3.1.2. Stimuli; 3.1.3. Procedure and Design; 3.2. Results and Discussion; 4. General Discussion; References; Theoretical and Computational Limitations in Simulating 3- to4-Month-Old Infants' Categorization Processes; 1. Introduction; 2. Simulation 1. Reproduction of the asymmetric categorization effect; 2.1. Stimuli 2.2. Neural network procedure |
Record Nr. | UNINA-9910453374803321 |
New Jersey : , : World Scientific, , [2014] | ||
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Lo trovi qui: Univ. Federico II | ||
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Computational models of cognitive processes : proceedings of the 13th Neural Computation and Psychology Workshop, San Sebastian, Spain, 12-14 July 2012 / / editors, Julien Mayor, University of Geneva, Switzerland, Pablo Gomez, De Paul University, USA |
Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
Descrizione fisica | 1 online resource (ix, 276 pages) : illustrations (some color) |
Disciplina | 612.8/233 |
Collana | Progress in neural processing |
Soggetto topico |
Neural networks (Neurobiology)
Cognition Neural stimulation |
ISBN | 981-4458-84-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Preface; Contents; Language; Modelling Language - Vision Interactions in the Hub and Spoke Framework; 1. Introduction; 2. Virtues of the Hub & Spoke Framework; 3. A Hub & Spoke Model of Language Mediated Visual Attention; 3.1. Language Mediated Visual Attention & The Visual World Paradigm; 3.2. Method; 3.2.1. Network; 3.2.2. Artificial Corpus; 3.2.3. Training; 3.2.4. Pre-Test; 3.3. Results; 3.3.1. Simulation of Phonological Effects; 3.3.2. Simulation of Visual Effects; 3.3.3. Simulation of Semantic Effects; 4. Discussion; References
Modelling Letter Perception: The Effect of Supervision and Top-Down Information on Simulated Reaction Times1. Introduction; 2. Method; 2.1. Simulations; 2.2. Neural Network Algorithms; 2.2.1. Restricted Boltzmann Machines; 2.2.2. Training a Deep-Belief Network; 2.2.3. Delta-Rule and Back-Propagation; 2.2.4. Simulating Reaction Times; 2.3. Human Reaction Time Data; 3. Results; 4. Conclusions; References; Encoding Words into a Potts Attractor Network; 1. Introduction; 2. BLISS: The Training Language; 3. Potts Attractor Network: a Simplified Model of the Cortex 4. Implementation of Word Representation in the Potts Network4.1. Semantic Representation; 4.2. Syntactic Representation; 5. Discussion; References; Unexpected Predictability in the Hawaiian Passive; 1. Introduction; 2. Data; 3. Methods; 3.1. Pre-processing; 3.2. The model; 3.3. Error measures; 3.3.1. Mean Squared Error; 3.3.2. Classification Error; 3.4. Baseline estimates; 3.4.1. Random guess: adaptation to the range of target values; 3.4.2. Weighted guess: adaptation to the distribution of target values; 4. Results; 5. Conclusion; Acknowledgements; References Difference Between Spoken and Written Language Based on Zipf 's Law Analysis1. Introduction; 2. Methods; 3. Results; 3.1. Log- log frequency vs. rank plots; 3.2. Five most frequent words in 1-, 2-, and 3-grams; 3.3. Exponent of rank; 4. Discussion; Acknowledgments; References; Reading Aloud is Quicker than Reading Silently: A Study in the Japanese Language Demonstrating the Enhancement of Cognitive Processing by Action; 1. Introduction; 2. Material and Methods; 3. Results; 4. Discussion; References; Development; Testing a Dynamic Neural Field Model of Children's Category Labelling 1. Introduction2. Simulation; 2.1. Dynamic Neural Fields; 2.2. Categorisation by Shared Features; 2.3. Method; 2.3.1. Architecture; 2.3.2. Stimuli; 2.3.3. Design and Procedure; 2.3.4. Results and Discussion; 3. Experiment; 3.1. Method; 3.1.1. Participants; 3.1.2. Stimuli; 3.1.3. Procedure and Design; 3.2. Results and Discussion; 4. General Discussion; References; Theoretical and Computational Limitations in Simulating 3- to4-Month-Old Infants' Categorization Processes; 1. Introduction; 2. Simulation 1. Reproduction of the asymmetric categorization effect; 2.1. Stimuli 2.2. Neural network procedure |
Record Nr. | UNINA-9910790976403321 |
New Jersey : , : World Scientific, , [2014] | ||
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Lo trovi qui: Univ. Federico II | ||
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Computational models of cognitive processes : proceedings of the 13th Neural Computation and Psychology Workshop, San Sebastian, Spain, 12-14 July 2012 / / editors, Julien Mayor, University of Geneva, Switzerland, Pablo Gomez, De Paul University, USA |
Pubbl/distr/stampa | New Jersey : , : World Scientific, , [2014] |
Descrizione fisica | 1 online resource (ix, 276 pages) : illustrations (some color) |
Disciplina | 612.8/233 |
Collana | Progress in neural processing |
Soggetto topico |
Neural networks (Neurobiology)
Cognition Neural stimulation |
ISBN | 981-4458-84-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Preface; Contents; Language; Modelling Language - Vision Interactions in the Hub and Spoke Framework; 1. Introduction; 2. Virtues of the Hub & Spoke Framework; 3. A Hub & Spoke Model of Language Mediated Visual Attention; 3.1. Language Mediated Visual Attention & The Visual World Paradigm; 3.2. Method; 3.2.1. Network; 3.2.2. Artificial Corpus; 3.2.3. Training; 3.2.4. Pre-Test; 3.3. Results; 3.3.1. Simulation of Phonological Effects; 3.3.2. Simulation of Visual Effects; 3.3.3. Simulation of Semantic Effects; 4. Discussion; References
Modelling Letter Perception: The Effect of Supervision and Top-Down Information on Simulated Reaction Times1. Introduction; 2. Method; 2.1. Simulations; 2.2. Neural Network Algorithms; 2.2.1. Restricted Boltzmann Machines; 2.2.2. Training a Deep-Belief Network; 2.2.3. Delta-Rule and Back-Propagation; 2.2.4. Simulating Reaction Times; 2.3. Human Reaction Time Data; 3. Results; 4. Conclusions; References; Encoding Words into a Potts Attractor Network; 1. Introduction; 2. BLISS: The Training Language; 3. Potts Attractor Network: a Simplified Model of the Cortex 4. Implementation of Word Representation in the Potts Network4.1. Semantic Representation; 4.2. Syntactic Representation; 5. Discussion; References; Unexpected Predictability in the Hawaiian Passive; 1. Introduction; 2. Data; 3. Methods; 3.1. Pre-processing; 3.2. The model; 3.3. Error measures; 3.3.1. Mean Squared Error; 3.3.2. Classification Error; 3.4. Baseline estimates; 3.4.1. Random guess: adaptation to the range of target values; 3.4.2. Weighted guess: adaptation to the distribution of target values; 4. Results; 5. Conclusion; Acknowledgements; References Difference Between Spoken and Written Language Based on Zipf 's Law Analysis1. Introduction; 2. Methods; 3. Results; 3.1. Log- log frequency vs. rank plots; 3.2. Five most frequent words in 1-, 2-, and 3-grams; 3.3. Exponent of rank; 4. Discussion; Acknowledgments; References; Reading Aloud is Quicker than Reading Silently: A Study in the Japanese Language Demonstrating the Enhancement of Cognitive Processing by Action; 1. Introduction; 2. Material and Methods; 3. Results; 4. Discussion; References; Development; Testing a Dynamic Neural Field Model of Children's Category Labelling 1. Introduction2. Simulation; 2.1. Dynamic Neural Fields; 2.2. Categorisation by Shared Features; 2.3. Method; 2.3.1. Architecture; 2.3.2. Stimuli; 2.3.3. Design and Procedure; 2.3.4. Results and Discussion; 3. Experiment; 3.1. Method; 3.1.1. Participants; 3.1.2. Stimuli; 3.1.3. Procedure and Design; 3.2. Results and Discussion; 4. General Discussion; References; Theoretical and Computational Limitations in Simulating 3- to4-Month-Old Infants' Categorization Processes; 1. Introduction; 2. Simulation 1. Reproduction of the asymmetric categorization effect; 2.1. Stimuli 2.2. Neural network procedure |
Record Nr. | UNINA-9910807277403321 |
New Jersey : , : World Scientific, , [2014] | ||
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Lo trovi qui: Univ. Federico II | ||
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Connectionist models of behaviour and cognition II [[electronic resource] ] : proceedings of the 11th Neural Computation and Psychology Workshop, University of Oxford, UK, 16-18 July 2008 / / editors, Julien Mayor, Nicolas Ruh, Kim Plunk |
Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific, c2009 |
Descrizione fisica | 1 online resource (427 p.) |
Disciplina |
153
612.8/2 |
Altri autori (Persone) |
MayorJulien
RuhNicolas PlunkettKim |
Collana | Progress in neural processing |
Soggetto topico |
Connectionism
Cognition |
Soggetto genere / forma | Electronic books. |
ISBN |
1-282-44156-6
9786612441561 981-283-423-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Preface; CONTENTS; Embedded Cognition; Memory; Categorisation; Temporal Aspects of Cognition; Concepts and High-Level Cognition; Language, Learning and Development; Sensory Processing and Attention; Author Index |
Record Nr. | UNINA-9910457101303321 |
Singapore ; ; Hackensack, NJ, : World Scientific, c2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Connectionist models of behaviour and cognition II [[electronic resource] ] : proceedings of the 11th Neural Computation and Psychology Workshop, University of Oxford, UK, 16-18 July 2008 / / editors, Julien Mayor, Nicolas Ruh, Kim Plunk |
Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific, c2009 |
Descrizione fisica | 1 online resource (427 p.) |
Disciplina |
153
612.8/2 |
Altri autori (Persone) |
MayorJulien
RuhNicolas PlunkettKim |
Collana | Progress in neural processing |
Soggetto topico |
Connectionism
Cognition |
ISBN |
1-282-44156-6
9786612441561 981-283-423-0 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | Preface; CONTENTS; Embedded Cognition; Memory; Categorisation; Temporal Aspects of Cognition; Concepts and High-Level Cognition; Language, Learning and Development; Sensory Processing and Attention; Author Index |
Record Nr. | UNINA-9910780809403321 |
Singapore ; ; Hackensack, NJ, : World Scientific, c2009 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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