Massively Parallel, Optical, and Neural Computing in the United States PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Massively Parallel, Optical, and Neural Computing in the United States PDF full book. Access full book title Massively Parallel, Optical, and Neural Computing in the United States by Gilbert Kalb. Download full books in PDF and EPUB format.
Author: Gilbert Kalb
Publisher: IOS Press
ISBN: 9789051990973
Category : Computers
Languages : en
Pages : 220
Get Book Here
Book Description
A survey of products and research projects in the field of highly parallel, optical and neural computers in the USA. It covers operating systems, language projects and market analysis, as well as optical computing devices and optical connections of electronic parts.
Author: Gilbert Kalb
Publisher: IOS Press
ISBN: 9789051990973
Category : Computers
Languages : en
Pages : 220
Get Book Here
Book Description
A survey of products and research projects in the field of highly parallel, optical and neural computers in the USA. It covers operating systems, language projects and market analysis, as well as optical computing devices and optical connections of electronic parts.
Author:
Publisher:
ISBN:
Category : Research
Languages : en
Pages : 1100
Get Book Here
Book Description
Author:
Publisher:
ISBN:
Category : Industries
Languages : en
Pages : 656
Get Book Here
Book Description
Author: Derek Gordon
Publisher: Springer Nature
ISBN: 3030611213
Category : Medical
Languages : en
Pages : 366
Get Book Here
Book Description
Heterogeneity, or mixtures, are ubiquitous in genetics. Even for data as simple as mono-genic diseases, populations are a mixture of affected and unaffected individuals. Still, most statistical genetic association analyses, designed to map genes for diseases and other genetic traits, ignore this phenomenon. In this book, we document methods that incorporate heterogeneity into the design and analysis of genetic and genomic association data. Among the key qualities of our developed statistics is that they include mixture parameters as part of the statistic, a unique component for tests of association. A critical feature of this work is the inclusion of at least one heterogeneity parameter when performing statistical power and sample size calculations for tests of genetic association. We anticipate that this book will be useful to researchers who want to estimate heterogeneity in their data, develop or apply genetic association statistics where heterogeneity exists, and accurately evaluate statistical power and sample size for genetic association through the application of robust experimental design.
Author: L.N. Kanal
Publisher: Elsevier
ISBN: 1483295745
Category : Computers
Languages : en
Pages : 445
Get Book Here
Book Description
Parallel processing for AI problems is of great current interest because of its potential for alleviating the computational demands of AI procedures. The articles in this book consider parallel processing for problems in several areas of artificial intelligence: image processing, knowledge representation in semantic networks, production rules, mechanization of logic, constraint satisfaction, parsing of natural language, data filtering and data mining. The publication is divided into six sections. The first addresses parallel computing for processing and understanding images. The second discusses parallel processing for semantic networks, which are widely used means for representing knowledge - methods which enable efficient and flexible processing of semantic networks are expected to have high utility for building large-scale knowledge-based systems. The third section explores the automatic parallel execution of production systems, which are used extensively in building rule-based expert systems - systems containing large numbers of rules are slow to execute and can significantly benefit from automatic parallel execution. The exploitation of parallelism for the mechanization of logic is dealt with in the fourth section. While sequential control aspects pose problems for the parallelization of production systems, logic has a purely declarative interpretation which does not demand a particular evaluation strategy. In this area, therefore, very large search spaces provide significant potential for parallelism. In particular, this is true for automated theorem proving. The fifth section considers the problem of constraint satisfaction, which is a useful abstraction of a number of important problems in AI and other fields of computer science. It also discusses the technique of consistent labeling as a preprocessing step in the constraint satisfaction problem. Section VI consists of two articles, each on a different, important topic. The first discusses parallel formulation for the Tree Adjoining Grammar (TAG), which is a powerful formalism for describing natural languages. The second examines the suitability of a parallel programming paradigm called Linda, for solving problems in artificial intelligence.Each of the areas discussed in the book holds many open problems, but it is believed that parallel processing will form a key ingredient in achieving at least partial solutions. It is hoped that the contributions, sourced from experts around the world, will inspire readers to take on these challenging areas of inquiry.
Author:
Publisher:
ISBN:
Category : Aeronautics
Languages : en
Pages : 692
Get Book Here
Book Description
Author: Yang Chai
Publisher: Springer Nature
ISBN: 3031115066
Category : Technology & Engineering
Languages : en
Pages : 237
Get Book Here
Book Description
This book provides a detailed introduction to near-sensor and in-sensor computing paradigms, their working mechanisms, development trends and future directions. The authors also provide a comprehensive review of current progress in this area, analyze existing challenges in the field, and offer possible solutions. Readers will benefit from the discussion of computing approaches that intervene in the vicinity of or inside sensory networks to help process data more efficiently, decreasing power consumption and reducing the transfer of redundant data between sensing and processing units. Provides readers with a detailed introduction to the near-sensor and in-sensor computing paradigms; Includes in-depth and comprehensive summaries of the state-of-the-art development in this field; Discusses and compares various neuromorphic sensors and neural networks: Describes integration technology for near-/in-sensor computing; Reveals the relationship between near-/in-sensor computing and other computing paradigms, such as neuromorphic computing, edge computing, intuitive computing, and in-memory computing.
Author: Alexander I. Galushkin
Publisher: Springer Science & Business Media
ISBN: 3540481257
Category : Technology & Engineering
Languages : en
Pages : 396
Get Book Here
Book Description
This book, written by a leader in neural network theory in Russia, uses mathematical methods in combination with complexity theory, nonlinear dynamics and optimization. It details more than 40 years of Soviet and Russian neural network research and presents a systematized methodology of neural networks synthesis. The theory is expansive: covering not just traditional topics such as network architecture but also neural continua in function spaces as well.
Author:
Publisher:
ISBN:
Category : Power resources
Languages : en
Pages : 654
Get Book Here
Book Description
Author: Jorge Fernández-Berni
Publisher: Springer Science & Business Media
ISBN: 1461423929
Category : Technology & Engineering
Languages : en
Pages : 173
Get Book Here
Book Description
This book presents a comprehensive, systematic approach to the development of vision system architectures that employ sensory-processing concurrency and parallel processing to meet the autonomy challenges posed by a variety of safety and surveillance applications. Coverage includes a thorough analysis of resistive diffusion networks embedded within an image sensor array. This analysis supports a systematic approach to the design of spatial image filters and their implementation as vision chips in CMOS technology. The book also addresses system-level considerations pertaining to the embedding of these vision chips into vision-enabled wireless sensor networks. Describes a system-level approach for designing of vision devices and embedding them into vision-enabled, wireless sensor networks; Surveys state-of-the-art, vision-enabled WSN nodes; Includes details of specifications and challenges of vision-enabled WSNs; Explains architectures for low-energy CMOS vision chips with embedded, programmable spatial filtering capabilities; Includes considerations pertaining to the integration of vision chips into off-the-shelf WSN platforms.
