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Recurrent Neural Networks for Prediction, Danilo P. Mandic, Jonathon A. Chambers


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Автор: Danilo P. Mandic, Jonathon A. Chambers
Название:  Recurrent Neural Networks for Prediction
ISBN: 9780471495178
Издательство: Wiley
Классификация:


ISBN-10: 0471495174
Обложка/Формат: Hardcover
Страницы: 308
Вес: 0.73 кг.
Дата издания: 06.08.2001
Серия: Adaptive and cognitive dynamic systems: signal processing, learning, communications and control
Язык: English
Размер: 24.82 x 15.39 x 2.21 cm
Читательская аудитория: Postgraduate, research & scholarly
Подзаголовок: Learning algorithms, architectures and stability
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: Neural networks consist of interconnected groups of neurons which function as processing units and aim to reconstruct the operation of the human brain.


Neural Networks for Pattern Recognition

Автор: Bishop, Christopher M.
Название: Neural Networks for Pattern Recognition
ISBN: 0198538642 ISBN-13(EAN): 9780198538646
Издательство: Oxford Academ
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Цена: 13939.00 р.
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Описание: This book is the first to provide a comprehensive account of neural networks from a statistical perspective. Its emphasis is on pattern recognition, which currently represents the area of greatest applicability for neural networks. By focusing on pattern recognition, the book provides a much more extensive treatment of many topics than is available in earlier books.

Artificial Neural Networks for Engineering Applications

Автор: Alanis, Alma
Название: Artificial Neural Networks for Engineering Applications
ISBN: 0128182474 ISBN-13(EAN): 9780128182475
Издательство: Elsevier Science
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Цена: 17180.00 р.
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Описание: Hoe bestuur je een wendbare organisatie, of beter, hoe bestuur je een organisatie naar een blijvende wendbare organisatie?¢ Ben jij lid van het Managementteam (MT) of lid van de directie die de noodzaak tot verandering in besturing ziet, die de urgentie voelt om daar iets aan te doen en gehoor hiervoor wil vinden bij de collega leden van het MT of directie? ¢ Ben jij een coach in een organisatie die beweging richting een wendbare organisatie vooral bottom up ziet groeien, een beweging waar je de top down beweging aan toe wil voegen?. In deze pocketguide vind je een praktische methode hoe dit aan te pakken. Besturen in een steeds sneller veranderende wereld. Met de waan van de dag die vaak veel aandacht vraagt en die je kan afleiden van de te behalen resultaten. De auteurs gaan in op het operationaliseren van de strategische organisatiedoelen en daarmee het besturen van de gehele organisatie. De stellingname van dit boek is: maak scherp wat dit kwartaal bereikt moet worden om de strategische doelen te bereiken. Stuur kort cyclisch om te kunnen reageren op veranderende klantwensen of gewijzigde wet- en regelgeving. Werk samen als managementteam of directie richting dje strategische doelen en voorkom dat iedereen in de organisatie vooral een eigen doel nastreeft. Breng meer focus in de operationalisering van de strategie, minder met "brandjes" bezig zijn en meer met het voorkomen ervan. Krijg snel helder wat je medewerkers belemmert in hun werk. Lukt het om de belemmeringen in jouw organisatie snel op te lossen? De kern van deze pocketguide betreft het FOCUS- bord. Deze manier van visual management is een krachtig middel in de besturing. De toepassing ervan zorgt voor samenwerking tussen alle lagen in de organisatie, kort cyclisch sturen en focus op het behalen van de strategische doelen.

Neural Network Methods in Natural Language Processing

Автор: Goldberg Yoav
Название: Neural Network Methods in Natural Language Processing
ISBN: 1627052984 ISBN-13(EAN): 9781627052986
Издательство: Mare Nostrum (Eurospan)
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Цена: 11504.00 р.
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Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.

Supervised Sequence Labelling with Recurrent Neural Networks

Автор: Alex Graves
Название: Supervised Sequence Labelling with Recurrent Neural Networks
ISBN: 3642432182 ISBN-13(EAN): 9783642432187
Издательство: Springer
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Цена: 15672.00 р.
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Описание: This book offers a complete framework for classifying and transcribing sequential data with recurrent neural networks. It uses state-of-the-art results in speech and handwriting recognition to show the framework in action.

Theory, Concepts and Methods of Recurrent Neural Networks and Soft Computing

Автор: Rogerson Jeremy
Название: Theory, Concepts and Methods of Recurrent Neural Networks and Soft Computing
ISBN: 1632404931 ISBN-13(EAN): 9781632404930
Издательство: Неизвестно
Цена: 26659.00 р.
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Learning with Recurrent Neural Networks

Автор: Barbara Hammer
Название: Learning with Recurrent Neural Networks
ISBN: 185233343X ISBN-13(EAN): 9781852333430
Издательство: Springer
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Цена: 15672.00 р.
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Описание: Folding networks, a generalization of recurrent neural networks to tree structured inputs, are investigated as a mechanism to learn regularities on classical symbolic data. Also, the architecture, the training mechanism, and several applications in different areas are explained in this work.

Recurrent Neural Networks for Short-Term Load Forecasting

Автор: Filippo Maria Bianchi; Enrico Maiorino; Michael C.
Название: Recurrent Neural Networks for Short-Term Load Forecasting
ISBN: 3319703374 ISBN-13(EAN): 9783319703374
Издательство: Springer
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Цена: 7685.00 р.
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Описание: The key component in forecasting demand and consumption of resources in a supply network is an accurate prediction of real-valued time series.

AI Techniques for Reliability Prediction for Electronic Components

Автор: Cherry Bhargava
Название: AI Techniques for Reliability Prediction for Electronic Components
ISBN: 1799814645 ISBN-13(EAN): 9781799814641
Издательство: Mare Nostrum (Eurospan)
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Цена: 30215.00 р.
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Описание: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry.

AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.

AI Techniques for Reliability Prediction for Electronic Components

Автор: Cherry Bhargava
Название: AI Techniques for Reliability Prediction for Electronic Components
ISBN: 1799814653 ISBN-13(EAN): 9781799814658
Издательство: Mare Nostrum (Eurospan)
Цена: 24948.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: In the industry of manufacturing and design, one major constraint has been enhancing operating performance using less time. As technology continues to advance, manufacturers are looking for better methods in predicting the condition and residual lifetime of electronic devices in order to save repair costs and their reputation. Intelligent systems are a solution for predicting the reliability of these components; however, there is a lack of research on the advancements of this smart technology within the manufacturing industry. AI Techniques for Reliability Prediction for Electronic Components provides emerging research exploring the theoretical and practical aspects of prediction methods using artificial intelligence and machine learning in the manufacturing field. Featuring coverage on a broad range of topics such as data collection, fault tolerance, and health prognostics, this book is ideally designed for reliability engineers, electronic engineers, researchers, scientists, students, and faculty members seeking current research on the advancement of reliability analysis using AI.

Toward Deep Neural Networks

Автор: Zhang
Название: Toward Deep Neural Networks
ISBN: 1138387037 ISBN-13(EAN): 9781138387034
Издательство: Taylor&Francis
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Цена: 19140.00 р.
Наличие на складе: Поставка под заказ.

Описание: This book introduces deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors` 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet.

Neural Networks Modeling And Control

Автор: Rios, Jorge D.
Название: Neural Networks Modeling And Control
ISBN: 0128170786 ISBN-13(EAN): 9780128170786
Издательство: Elsevier Science
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Цена: 19875.00 р.
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Описание:

Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control.

As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends.

Artificial Neural Networks in Medicine and Biology

Автор: H. Malmgren; M. Borga; L. Niklasson
Название: Artificial Neural Networks in Medicine and Biology
ISBN: 1852332891 ISBN-13(EAN): 9781852332891
Издательство: Springer
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Цена: 23058.00 р.
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Описание: This volume comprises a selection of papers focusing specifically on the topics of ANNs in medicine and biology. It covers three main areas: the medical applications of ANNs, such as in diagnosis and outcome prediction, medical image analysis, and medical signal processing.


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