Tutorial On Neural Systems Modeling

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Tutorial On Neural Systems Modeling

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Author : Thomas J. Anastasio
language : en
Publisher: Sinauer
Release Date : 2010-03-01

Tutorial On Neural Systems Modeling written by Thomas J. Anastasio and has been published by Sinauer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-01 with Medical categories.

For students of neuroscience and cognitive science who wish to explore the functioning of the brain further, but lack an extensive background in computer programming or maths, this new book makes neural systems modelling truly accessible. Short, simple MATLAB computer programs give readers all the experience necessary to run their own simulations.

Efficient Processing Of Deep Neural Networks

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Author : Vivienne Sze
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2020-06-24

Efficient Processing Of Deep Neural Networks written by Vivienne Sze and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-24 with Computers categories.

This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of the DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as a formalization and organization of key concepts from contemporary works that provides insights that may spark new ideas.

Engineering Applications Of Neural Networks

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Author : Giacomo Boracchi
language : en
Publisher: Springer
Release Date : 2017-07-30

Engineering Applications Of Neural Networks written by Giacomo Boracchi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-30 with Computers categories.

This book constitutes the refereed proceedings of the 18th International Conference on Engineering Applications of Neural Networks, EANN 2017, held in Athens, Greece, in August 2017. The 40 revised full papers and 5 revised short papers presented were carefully reviewed and selected from 83 submissions. The papers cover the topics of deep learning, convolutional neural networks, image processing, pattern recognition, recommendation systems, machine learning, and applications of Artificial Neural Networks (ANN) applications in engineering, 5G telecommunication networks, and audio signal processing. The volume also includes papers presented at the 6th Mining Humanistic Data Workshop (MHDW 2017) and the 2nd Workshop on 5G-Putting Intelligence to the Network Edge (5G-PINE).

Interpretable Machine Learning

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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020

Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

Neural Networks Modeling And Control

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Author : Jorge D. Rios
language : en
Publisher: Academic Press
Release Date : 2020-01-15

Neural Networks Modeling And Control written by Jorge D. Rios and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-01-15 with Science categories.

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. - Provide in-depth analysis of neural control models and methodologies - Presents a comprehensive review of common problems in real-life neural network systems - Includes an analysis of potential applications, prototypes and future trends

Neural Network Methods For Natural Language Processing

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Author : Yoav Goldberg
language : en
Publisher: Springer Nature
Release Date : 2022-06-01

Neural Network Methods For Natural Language Processing written by Yoav Goldberg and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.

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.

Theory Of Neural Information Processing Systems

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Author : A.C.C. Coolen
language : en
Publisher: OUP Oxford
Release Date : 2005-07-21

Theory Of Neural Information Processing Systems written by A.C.C. Coolen and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-07-21 with Neural networks (Computer science) categories.

Theory of Neural Information Processing Systems provides an explicit, coherent, and up-to-date account of the modern theory of neural information processing systems. It has been carefully developed for graduate students from any quantitative discipline, including mathematics, computer science, physics, engineering or biology, and has been thoroughly class-tested by the authors over a period of some 8 years. Exercises are presented throughout the text and notes on historical background and further reading guide the student into the literature. All mathematical details are included and appendices provide further background material, including probability theory, linear algebra and stochastic processes, making this textbook accessible to a wide audience.

Systems Modeling Approaches And Applications

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Author : Alberto Jesus Martin
language : en
Publisher: Frontiers Media SA
Release Date : 2021-01-21

Systems Modeling Approaches And Applications written by Alberto Jesus Martin and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-21 with Science categories.

Biomimetic And Biohybrid Systems

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Author : Tony T. Prescott
language : en
Publisher: Springer
Release Date : 2012-06-22

Biomimetic And Biohybrid Systems written by Tony T. Prescott and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-06-22 with Computers categories.

This book constitutes the proceedings of the First International Conference on Biomimetic and Biohybrid Systems, Living Machines 2012, held in Barcelona, Spain, in July 2012. The 28 full papers and 33 extended abstracts presented in this volume were carefully reviewed and selected for inclusion in this book. The conference addresses themes related to the development of future real-world technologies which will depend strongly on our understanding and harnessing of the principles underlying living systems and the flow of communication signals between living and artificial systems.