Connectionist Models in Cognitive Neuroscience, Dietmar Heinke; Glyn W. Humphreys; Andrew Olson
Автор: Pierce Benjamin A Название: Genetics Essentials. Concepts and Connections. - 3th ed. ISBN: 1464190755 ISBN-13(EAN): 9781464190759 Издательство: Springer Рейтинг: Цена: 9083.00 р. Наличие на складе: Поставка под заказ.
Описание: Derived from Ben Pierce's popular and acclaimed Genetics: A Conceptual Approach, this streamlined text covers basic transmission, molecular, and population genetics.
Описание: Connectionist modelling and neural network applications had become a major sub-field of cognitive science by the mid-1990s. In this ground-breaking book, originally published in 1995, leading connectionists shed light on current approaches to memory and language modelling at the time.
Автор: David Touretzky Название: Connectionist Approaches to Language Learning ISBN: 1461367921 ISBN-13(EAN): 9781461367925 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Marco Catani and Michel Thiebaut de Schotten Название: Atlas of Human Brain Connections ISBN: 0198729375 ISBN-13(EAN): 9780198729372 Издательство: Oxford Academ Рейтинг: Цена: 18216.00 р. Наличие на складе: Поставка под заказ.
Описание: One of the major challenges of modern neuroscience is to define the complex pattern of neural connections that underlie cognition and behaviour. This atlas capitalises on novel diffusion MRI tractography methods to provide a comprehensive overview of connections derived from virtual in vivo tractography dissections of the human brain.
Автор: Houghton George Название: Connectionist Models in Cognitive Psychology ISBN: 0415646901 ISBN-13(EAN): 9780415646901 Издательство: Taylor&Francis Рейтинг: Цена: 7961.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A state-of-the-art review of neural network modelling in core areas of cognitive psychology including: memory and learning, language (written and spoken), cognitive development, cognitive control, attention and action.
Описание: This title presents the most comprehensive existing "case study" of how the effects of damage in connectionist models can replicate the patterns of cognitive impairments that can arise in humans as a result of brain damage.
Описание: Collects together most of the papers presented at the Twelfth Neural Computation and Psychology Workshop (NCPW12) held in 2010 at Birkbeck College (England). This book covers a wide range of research topics in neural computation and psychology, including cognitive development, language processing, higher-level cognition, and more.
Автор: Robert M. French; Jacques P. Sougne Название: Connectionist Models of Learning, Development and Evolution ISBN: 1852333545 ISBN-13(EAN): 9781852333546 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Presents neural network modelling in the areas of evolution, learning, and development. This book, organized in six sections, covers the neural basis of cognition; development and category learning; implicit learning; social cognition; and, semantics. It also covers artificial intelligence, mathematics, psychology, neurobiology, and philosophy.
Автор: David Touretzky Название: Connectionist Approaches to Language Learning ISBN: 0792392167 ISBN-13(EAN): 9780792392163 Издательство: Springer Рейтинг: Цена: 18161.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: arise automatically as a result of the recursive structure of the task and the continuous nature of the SRN's state space. Elman also introduces a new graphical technique for study- ing network behavior based on principal components analysis. He shows that sentences with multiple levels of embedding produce state space trajectories with an intriguing self- similar structure. The development and shape of a recurrent network's state space is the subject of Pollack's paper, the most provocative in this collection. Pollack looks more closely at a connectionist network as a continuous dynamical system. He describes a new type of machine learning phenomenon: induction by phase transition. He then shows that under certain conditions, the state space created by these machines can have a fractal or chaotic structure, with a potentially infinite number of states. This is graphically illustrated using a higher-order recurrent network trained to recognize various regular languages over binary strings. Finally, Pollack suggests that it might be possible to exploit the fractal dynamics of these systems to achieve a generative capacity beyond that of finite-state machines.
Автор: R.H. Phaf Название: Learning in Natural and Connectionist Systems ISBN: 9401043620 ISBN-13(EAN): 9789401043625 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Based on conference proceedings, this book presents revised papers. Also included, and written with the novice reader in mind, is an introductory survey by the volume editors. The volume presents the state of the art in current approaches to NLP.
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