Thinking Machines

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks. This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning. Presents a clear understanding of various available machine learning hardware accelerator solutions that can be applied to selected machine learning algorithms Offers key insights into the development of hardware, from algorithms, software, logic circuits, to hardware accelerators Introduces the baseline characteristics of deep neural network models that should be treated by hardware as well Presents readers with a thorough review of past research and products, explaining how to design through ASIC and FPGA approaches for target machine learning models Surveys current trends and models in neuromorphic computing and neural network hardware architectures Outlines the strategy for advanced hardware development through the example of deep learning accelerators

Produk Detail:

  • Author : Shigeyuki Takano
  • Publisher : Academic Press
  • Pages : 322 pages
  • ISBN : 0128182806
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKThinking Machines

Thinking Machines

Thinking Machines
  • Author : Shigeyuki Takano
  • Publisher : Academic Press
  • Release : 27 March 2021
GET THIS BOOKThinking Machines

Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design

Efficient Processing of Deep Neural Networks

Efficient Processing of Deep Neural Networks
  • Author : Vivienne Sze,Yu-Hsin Chen,Tien-Ju Yang,Joel S. Emer
  • Publisher : Morgan & Claypool Publishers
  • Release : 24 June 2020
GET THIS BOOKEfficient Processing of Deep Neural Networks

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 key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy

Brainmakers: How Scientists Moving Beyond Computers Create Rival to Humn Brain

Brainmakers: How Scientists Moving Beyond Computers Create Rival to Humn Brain
  • Author : David H. Freedman
  • Publisher : Simon and Schuster
  • Release : 15 June 2010
GET THIS BOOKBrainmakers: How Scientists Moving Beyond Computers Create Rival to Humn Brain

A fascinating tour behind the scenes at laboratories around the world as top researchers race to create revolutionary "thinking machines" that may one day lead to a new form of intelligence. Join David Freedman as he takes you on a fascinating tour behind the scenes at laboratories around the world as top researchers race to create revolutionary "thinking machines" that may one day lead to a new form of intelligence. The subject of fantasy and skepticism for centuries—from William

The Promise of Neural Networks

The Promise of Neural Networks
  • Author : J.G. Taylor
  • Publisher : Springer Science & Business Media
  • Release : 06 December 2012
GET THIS BOOKThe Promise of Neural Networks

This book is the product of a 15-month intensive investigation of the European artificial network scene, together with a view of the broader framework of the subject in a world context. It could not have been completed in such a remarkably short time, and so effectively, without the dedicated efforts of Louise Turner, the DEANNA secretary, and Geoff Chappell, the DEANNA researcher, at the Centre for Neural Networks, King's College, London. I would like to take this opportunity to thank

Learning and Categorization in Modular Neural Networks

Learning and Categorization in Modular Neural Networks
  • Author : Jacob M.J. Murre
  • Publisher : Psychology Press
  • Release : 25 February 2014
GET THIS BOOKLearning and Categorization in Modular Neural Networks

This book introduces a new neural network model called CALM, for categorization and learning in neural networks. The author demonstrates how this model can learn the word superiority effect for letter recognition, and discusses a series of studies that simulate experiments in implicit and explicit memory, involving normal and amnesic patients. Pathological, but psychologically accurate, behavior is produced by "lesioning" the arousal system of these models. A concise introduction to genetic algorithms, a new computing method based on the biological

Handbook of Neural Computation

Handbook of Neural Computation
  • Author : Emile Fiesler,Russell Beale
  • Publisher : CRC Press
  • Release : 15 January 2020
GET THIS BOOKHandbook of Neural Computation

The Handbook of Neural Computation is a practical, hands-on guide to the design and implementation of neural networks used by scientists and engineers to tackle difficult and/or time-consuming problems. The handbook bridges an information pathway between scientists and engineers in different disciplines who apply neural networks to similar probl

Neural Networks for Perception

Neural Networks for Perception
  • Author : Harry Wechsler
  • Publisher : Academic Press
  • Release : 10 May 2014
GET THIS BOOKNeural Networks for Perception

Neural Networks for Perception, Volume 1: Human and Machine Perception focuses on models for understanding human perception in terms of distributed computation and examples of PDP models for machine perception. This book addresses both theoretical and practical issues related to the feasibility of both explaining human perception and implementing machine perception in terms of neural network models. The book is organized into two parts. The first part focuses on human perception. Topics on network model of object recognition in human vision,

The Hidden Pattern

The Hidden Pattern
  • Author : Ben Goertzel
  • Publisher : Universal-Publishers
  • Release : 18 October 2021
GET THIS BOOKThe Hidden Pattern

The Hidden Pattern presents a novel philosophy of mind, intended to form a coherent conceptual framework within which it is possible to understand the diverse aspects of mind and intelligence in a unified way. The central concept of the philosophy presented is the concept of "pattern": minds and the world they live in and co-create are viewed as patterned systems of patterns, evolving over time, and various aspects of subjective experience and individual and social intelligence are analyzed in detail

Deep Learning with PyTorch

Deep Learning with PyTorch
  • Author : Luca Pietro Giovanni Antiga,Eli Stevens,Thomas Viehmann
  • Publisher : Simon and Schuster
  • Release : 01 July 2020
GET THIS BOOKDeep Learning with PyTorch

“We finally have the definitive treatise on PyTorch! It covers the basics and abstractions in great detail. I hope this book becomes your extended reference document.” —Soumith Chintala, co-creator of PyTorch Key Features Written by PyTorch’s creator and key contributors Develop deep learning models in a familiar Pythonic way Use PyTorch to build an image classifier for cancer detection Diagnose problems with your neural network and improve training with data augmentation Purchase of the print book includes a free

Human and Machine Vision

Human and Machine Vision
  • Author : Virginio Cantoni
  • Publisher : Springer Science & Business Media
  • Release : 29 June 2013
GET THIS BOOKHuman and Machine Vision

The following are the proceedings of the Third International Workshop on Perception held in Pavia, Italy, on September 27-30, 1993, under the auspices of four institutions: the Group of Cybernetic and Biophysics (GNCB)s of the National Research Council (CNR), the Italian Association for Artificial Intelligence (AI * IA), the Italian Association of Psychology (AlP), and the Italian Chapter of the International Association for Pattern Recognition (IAPR). The theme of this third workshop was: "Human and Machine Vision: Analogies and Divergencies." A

From Animals to Animats 2

From Animals to Animats 2
  • Author : Jean-Arcady Meyer,H. L. Roitblat,Stewart W. Wilson,Stewart W Wilson
  • Publisher : MIT Press
  • Release : 18 October 1993
GET THIS BOOKFrom Animals to Animats 2

More than sixty contributions in From Animals to Animats 2 byresearchers in ethology, ecology, cybernetics, artificial intelligence, robotics, and related fieldsinvestigate behaviors and the underlying mechanisms that allow animals and, potentially, robots toadapt and survive in uncertain environments. Jean-Arcady Meyer is Director of Research, CNRS, Paris.Herbert L. Roitblat is Professor of Psychology at the University of Hawaii at Manoa. Stewart W.Wilson is a scientist at The Rowland Institute for Science, Cambridge,Massachusetts. Topics covered: The Animat Approach to Adaptive