Learning In The Absence Of Training Data

Download Learning In The Absence Of Training Data full books in PDF, epub, and Kindle. Read online Learning In The Absence Of Training Data ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Learning in the Absence of Training Data

Author : Dalia Chakrabarty
Publisher : Springer Nature
ISBN 13 : 303131011X
Total Pages : 241 pages
Book Rating : 4.0/5 (313 download)

DOWNLOAD NOW!

Book Synopsis Learning in the Absence of Training Data by : Dalia Chakrabarty

Download or read book Learning in the Absence of Training Data written by Dalia Chakrabarty and published by Springer Nature. This book was released on 2023-07-13 with total page 241 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the concept of “bespoke learning”, a new mechanistic approach that makes it possible to generate values of an output variable at each designated value of an associated input variable. Here the output variable generally provides information about the system’s behaviour/structure, and the aim is to learn the input-output relationship, even though little to no information on the output is available, as in multiple real-world problems. Once the output values have been bespoke-learnt, the originally-absent training set of input-output pairs becomes available, so that (supervised) learning of the sought inter-variable relation is then possible. Three ways of undertaking such bespoke learning are offered: by tapping into system dynamics in generic dynamical systems, to learn the function that causes the system’s evolution; by comparing realisations of a random graph variable, given multivariate time series datasets of disparate temporal coverage; and by designing maximally information-availing likelihoods in static systems. These methodologies are applied to four different real-world problems: forecasting daily COVID-19 infection numbers; learning the gravitational mass density in a real galaxy; learning a sub-surface material density function; and predicting the risk of onset of a disease following bone marrow transplants. Primarily aimed at graduate and postgraduate students studying a field which includes facets of statistical learning, the book will also benefit experts working in a wide range of applications. The prerequisites are undergraduate level probability and stochastic processes, and preliminary ideas on Bayesian statistics.

Bayesian Statistics and New Generations

Author : Raffaele Argiento
Publisher : Springer Nature
ISBN 13 : 3030306119
Total Pages : 184 pages
Book Rating : 4.0/5 (33 download)

DOWNLOAD NOW!

Book Synopsis Bayesian Statistics and New Generations by : Raffaele Argiento

Download or read book Bayesian Statistics and New Generations written by Raffaele Argiento and published by Springer Nature. This book was released on 2019-11-21 with total page 184 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of peer-reviewed contributions to the fourth Bayesian Young Statisticians Meeting, BAYSM 2018, held at the University of Warwick on 2-3 July 2018. The meeting provided a valuable opportunity for young researchers, MSc students, PhD students, and postdocs interested in Bayesian statistics to connect with the broader Bayesian community. The proceedings offer cutting-edge papers on a wide range of topics in Bayesian statistics, identify important challenges and investigate promising methodological approaches, while also assessing current methods and stimulating applications. The book is intended for a broad audience of statisticians, and demonstrates how theoretical, methodological, and computational aspects are often combined in the Bayesian framework to successfully tackle complex problems.

BASICS OF MACHINE LEARNING, DEEP LEARNING AND NATURAL LANGUAGE PROCESSING

Author : Dr.R.GNANAJEYARAMAN
Publisher : SK Research Group of Companies
ISBN 13 : 8119980751
Total Pages : 217 pages
Book Rating : 4.1/5 (199 download)

DOWNLOAD NOW!

Book Synopsis BASICS OF MACHINE LEARNING, DEEP LEARNING AND NATURAL LANGUAGE PROCESSING by : Dr.R.GNANAJEYARAMAN

Download or read book BASICS OF MACHINE LEARNING, DEEP LEARNING AND NATURAL LANGUAGE PROCESSING written by Dr.R.GNANAJEYARAMAN and published by SK Research Group of Companies. This book was released on 2024-02-07 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dr.R.GNANAJEYARAMAN, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.U.ARUL, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.M.RAMA MOORTHY, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India. Dr.CARMEL MARY BELINDA.M.J, Professor, Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, Chennai, Tamil Nadu, India.

Machine Learning

Author : T V Geetha
Publisher : CRC Press
ISBN 13 : 1000867161
Total Pages : 478 pages
Book Rating : 4.0/5 (8 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning by : T V Geetha

Download or read book Machine Learning written by T V Geetha and published by CRC Press. This book was released on 2023-05-17 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning: Concepts, Techniques and Applications starts at basic conceptual level of explaining machine learning and goes on to explain the basis of machine learning algorithms. The mathematical foundations required are outlined along with their associations to machine learning. The book then goes on to describe important machine learning algorithms along with appropriate use cases. This approach enables the readers to explore the applicability of each algorithm by understanding the differences between them. A comprehensive account of various aspects of ethical machine learning has been discussed. An outline of deep learning models is also included. The use cases, self-assessments, exercises, activities, numerical problems, and projects associated with each chapter aims to concretize the understanding. Features Concepts of Machine learning from basics to algorithms to implementation Comparison of Different Machine Learning Algorithms – When to use them & Why – for Application developers and Researchers Machine Learning from an Application Perspective – General & Machine learning for Healthcare, Education, Business, Engineering Applications Ethics of machine learning including Bias, Fairness, Trust, Responsibility Basics of Deep learning, important deep learning models and applications Plenty of objective questions, Use Cases, Activity and Project based Learning Exercises The book aims to make the thinking of applications and problems in terms of machine learning possible for graduate students, researchers and professionals so that they can formulate the problems, prepare data, decide features, select appropriate machine learning algorithms and do appropriate performance evaluation.

Technical Advancements of Machine Learning in Healthcare

Author : Hrudaya Kumar Tripathy
Publisher : Springer Nature
ISBN 13 : 9813346981
Total Pages : 393 pages
Book Rating : 4.8/5 (133 download)

DOWNLOAD NOW!

Book Synopsis Technical Advancements of Machine Learning in Healthcare by : Hrudaya Kumar Tripathy

Download or read book Technical Advancements of Machine Learning in Healthcare written by Hrudaya Kumar Tripathy and published by Springer Nature. This book was released on 2021-02-27 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on various advanced technologies which integrate with machine learning to assist one of the most leading industries, healthcare. It presents recent research works based on machine learning approaches supported by medical and information communication technologies with the use of data and image analysis. The book presents insight about techniques which broadly deals in delivery of quality, accurate and affordable healthcare solutions by predictive, proactive and preventative methods. The book also explores the possible use of machine learning in enterprises, such as enhanced medical imaging/diagnostics, understanding medical data, drug discovery and development, robotic surgery and automation, radiation treatments, creating electronic smart records and outbreak prediction.

Advances in Machine Learning and Computational Intelligence

Author : Srikanta Patnaik
Publisher : Springer Nature
ISBN 13 : 9811552436
Total Pages : 853 pages
Book Rating : 4.8/5 (115 download)

DOWNLOAD NOW!

Book Synopsis Advances in Machine Learning and Computational Intelligence by : Srikanta Patnaik

Download or read book Advances in Machine Learning and Computational Intelligence written by Srikanta Patnaik and published by Springer Nature. This book was released on 2020-07-25 with total page 853 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected high-quality papers presented at the International Conference on Machine Learning and Computational Intelligence (ICMLCI-2019), jointly organized by Kunming University of Science and Technology and the Interscience Research Network, Bhubaneswar, India, from April 6 to 7, 2019. Addressing virtually all aspects of intelligent systems, soft computing and machine learning, the topics covered include: prediction; data mining; information retrieval; game playing; robotics; learning methods; pattern visualization; automated knowledge acquisition; fuzzy, stochastic and probabilistic computing; neural computing; big data; social networks and applications of soft computing in various areas.

Geophysical Applications of Artificial Neural Networks and Fuzzy Logic

Author : W. Sandham
Publisher : Springer Science & Business Media
ISBN 13 : 9401702713
Total Pages : 336 pages
Book Rating : 4.4/5 (17 download)

DOWNLOAD NOW!

Book Synopsis Geophysical Applications of Artificial Neural Networks and Fuzzy Logic by : W. Sandham

Download or read book Geophysical Applications of Artificial Neural Networks and Fuzzy Logic written by W. Sandham and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past fifteen years has witnessed an explosive growth in the fundamental research and applications of artificial neural networks (ANNs) and fuzzy logic (FL). The main impetus behind this growth has been the ability of such methods to offer solutions not amenable to conventional techniques, particularly in application domains involving pattern recognition, prediction and control. Although the origins of ANNs and FL may be traced back to the 1940s and 1960s, respectively, the most rapid progress has only been achieved in the last fifteen years. This has been due to significant theoretical advances in our understanding of ANNs and FL, complemented by major technological developments in high-speed computing. In geophysics, ANNs and FL have enjoyed significant success and are now employed routinely in the following areas (amongst others): 1. Exploration Seismology. (a) Seismic data processing (trace editing; first break picking; deconvolution and multiple suppression; wavelet estimation; velocity analysis; noise identification/reduction; statics analysis; dataset matching/prediction, attenuation), (b) AVO analysis, (c) Chimneys, (d) Compression I dimensionality reduction, (e) Shear-wave analysis, (f) Interpretation (event tracking; lithology prediction and well-log analysis; prospect appraisal; hydrocarbon prediction; inversion; reservoir characterisation; quality assessment; tomography). 2. Earthquake Seismology and Subterranean Nuclear Explosions. 3. Mineral Exploration. 4. Electromagnetic I Potential Field Exploration. (a) Electromagnetic methods, (b) Potential field methods, (c) Ground penetrating radar, (d) Remote sensing, (e) inversion.

Applications of artificial intelligence, machine learning, and deep learning in plant breeding

Author : Maliheh Eftekhari
Publisher : Frontiers Media SA
ISBN 13 : 2832549713
Total Pages : 246 pages
Book Rating : 4.8/5 (325 download)

DOWNLOAD NOW!

Book Synopsis Applications of artificial intelligence, machine learning, and deep learning in plant breeding by : Maliheh Eftekhari

Download or read book Applications of artificial intelligence, machine learning, and deep learning in plant breeding written by Maliheh Eftekhari and published by Frontiers Media SA. This book was released on 2024-05-29 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence (AI) is an extensive concept that can be interpreted as a concentration on designing computer programs to train machines to accomplish functions like or better than hu-mans. An important subset of AI is Machine Learning (ML), in which a computer is provided with the capacity to learn its own patterns instead of the patterns and restrictions set by a human programmer, thus improving from experience. Deep Learning (DL), as a class of ML techniques, employs multilayered neural networks. The application of AI to plant science research is new and has grown significantly in recent years due to developments in calculation power, proficien-cies of hardware, and software progress. AI algorithms try to provide classifications and predic-tions. As applied to plant breeding, particularly omics data, ML as a given AI algorithm tries to translate omics data, which are intricate and include nonlinear interactions, into precise plant breeding. The applications of AI are extending rapidly and enhancing intensely in sophistication owing to the capability of rapid processing of huge and heterogeneous data. The conversion of AI techniques into accurate plant breeding is of great importance and will play a key role in the new era of plant breeding techniques in the coming years, particularly multi-omics data analysis. Advancements in plant breeding mainly depend upon developing statistical methods that harness the complicated data provided by analytical technologies identifying and quantifying genes, transcripts, proteins, metabolites, etc. The systems biology approach used in plant breeding, which integrates genomics, transcriptomics, proteomics, metabolomics, and other omics data, provides a massive amount of information. It is essential to perform accurate statistical analyses and AI methods such as ML and DL as well as optimization techniques to not only achieve an understanding of networks regulation and plant cell functions but develop high-precision models to predict the reaction of new Genetically Modified (GM) plants in special conditions. The constructed models will be of great economic importance, significantly reducing the time, labor, and instrument costs when finding optimized conditions for the bio-exploitation of plants. This Research Topic covers a wide range of studies on artificial intelligence-assisted plant breeding techniques, which contribute to plant biology and plant omics research. The relevant sub-topics include, but are not restricted to, the following: • AI-assisted plant breeding using omics and multi-omics approaches • Applying AI techniques along with multi-omics to recognize novel biomarkers associated with plant biological activities • Constructing up-to-date ML modeling and analyzing methods for dealing with omics data related to different plant growth processes • AI-assisted omics techniques in the plant defense process • Combining AI-assisted omics and multi-omics techniques using plant system biology approaches • Combining bioinformatics tools with AI approaches to analyze plant omics data • Designing cutting-edge workflow and developing innovative AI biology methods for omics data analysis

Explanation-Based Neural Network Learning

Author : Sebastian Thrun
Publisher : Springer Science & Business Media
ISBN 13 : 1461313813
Total Pages : 274 pages
Book Rating : 4.4/5 (613 download)

DOWNLOAD NOW!

Book Synopsis Explanation-Based Neural Network Learning by : Sebastian Thrun

Download or read book Explanation-Based Neural Network Learning written by Sebastian Thrun and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. `The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm.' From the Foreword by Tom M. Mitchell.

Managing Airline Networks

Author : Markus Franke
Publisher : Routledge
ISBN 13 : 1000336123
Total Pages : 178 pages
Book Rating : 4.0/5 (3 download)

DOWNLOAD NOW!

Book Synopsis Managing Airline Networks by : Markus Franke

Download or read book Managing Airline Networks written by Markus Franke and published by Routledge. This book was released on 2020-12-29 with total page 178 pages. Available in PDF, EPUB and Kindle. Book excerpt: Managing Airline Networks: Design, Integration and Innovative Technologies is a fully comprehensive description of state-of-the-art network management practices at airlines. Designed as a compendium on current practices and future trends in the field, the book offers an instructive guide through the complex world of non-linear production systems. Written by a renowned consultant and aviation expert, the book discusses the impact of network management on airline resource planning and performance, and examines the interplay between network management and adjacent functions. The book includes a practical case study and is enriched with academic perspectives. Discussing upcoming trends in the sector, the book provides an outlook on advanced technologies that may play a role in next-generation network management. Features include: a description of basic network types, performance indicators for profitable networks, efficient processes and success factors for network management, and common optimisation models and tools; descriptive overviews, supported by practical examples, and leading to a deep-dive case study; a section on trends in network management, outlining new demand forecasting models, ‘big data’ applications, machine learning and AI use cases, and alternative optimisation models for airlines. Managing Airline Networks: Design, Integration and Innovative Technologies is designed as a comprehensive compendium and is essential reading for both aviation practitioners and students of airline management.

Grid Modernization ─ Future Energy Network Infrastructure

Author : Mohammadreza Daneshvar
Publisher : Springer Nature
ISBN 13 : 303064099X
Total Pages : 293 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

Book Synopsis Grid Modernization ─ Future Energy Network Infrastructure by : Mohammadreza Daneshvar

Download or read book Grid Modernization ─ Future Energy Network Infrastructure written by Mohammadreza Daneshvar and published by Springer Nature. This book was released on 2021-03-08 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents theoretical, technical, and practical information on the modernization of future energy networks. All the basic requirements covering concepts, modeling, optimizing, and analyzing of future energy grids with various energy carriers such as electricity, gas, heat, and water, as well as their markets and contracts, are explained in detail. The main focus of the book is on modernizing both the energy consumers and the energy producers and analyzing various aspects of grid modernization such as reliability, resiliency, stability, and security. Coverage includes advanced communication protocols and solution methods for the Internet of Energy (IoE) infrastructure and energy trading in future energy grids with high/full share of renewable energy resources (RERs) within the transactive energy (TE) paradigm. Probabilistic modeling and optimizing of modern grids will be evaluated using realistic case studies considering the economic aspects of multi-carrier energy markets. This book will be welcomed as an important resource by researchers and postgraduate students studying energy systems, as well as practicing engineers working on modernizing energy grids and the design, planning, scheduling, and operation of smart power systems. Proposes practical solutions for solving the challenges of modern multi-carrier energy grids; Examines various types of energy storage systems and distributed energy resources (DERs) with an emphasis on renewable energy resources (RERs); Provides comprehensive mathematical models for optimizing of future modern multi-carrier energy grids.

Information Processing in Medical Imaging

Author : Sebastien Ourselin
Publisher : Springer
ISBN 13 : 3319199927
Total Pages : 811 pages
Book Rating : 4.3/5 (191 download)

DOWNLOAD NOW!

Book Synopsis Information Processing in Medical Imaging by : Sebastien Ourselin

Download or read book Information Processing in Medical Imaging written by Sebastien Ourselin and published by Springer. This book was released on 2015-06-22 with total page 811 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, held at the Sabhal Mor Ostaig College on the Isle of Skye, Scotland, UK, in June/July 2015. The 22 full papers and 41 poster papers presented in this volume were carefully reviewed and selected from 195 submissions. They were organized in topical sections named: probabilistic graphical models; MRI reconstruction; clustering; statistical methods; longitudinal analysis; microstructure imaging; shape analysis; multi-atlas fusion; fast image registration; deformation models; and the poster session.

Intelligent Techniques for Predictive Data Analytics

Author : Neha Singh
Publisher : John Wiley & Sons
ISBN 13 : 1394227973
Total Pages : 276 pages
Book Rating : 4.3/5 (942 download)

DOWNLOAD NOW!

Book Synopsis Intelligent Techniques for Predictive Data Analytics by : Neha Singh

Download or read book Intelligent Techniques for Predictive Data Analytics written by Neha Singh and published by John Wiley & Sons. This book was released on 2024-06-21 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Comprehensive resource covering tools and techniques used for predictive analytics with practical applications across various industries Intelligent Techniques for Predictive Data Analytics provides an in-depth introduction of the tools and techniques used for predictive analytics, covering applications in cyber security, network security, data mining, and machine learning across various industries. Each chapter offers a brief introduction on the subject to make the text accessible regardless of background knowledge. Readers will gain a clear understanding of how to use data processing, classification, and analysis to support strategic decisions, such as optimizing marketing strategies and customer relationship management and recommendation systems, improving general business operations, and predicting occurrence of chronic diseases for better patient management. Traditional data analytics uses dashboards to illustrate trends and outliers, but with large data sets, this process is labor-intensive and time-consuming. This book provides everything readers need to save time by performing deep, efficient analysis without human bias and time constraints. A section on current challenges in the field is also included. Intelligent Techniques for Predictive Data Analytics covers sample topics such as: Models to choose from in predictive modeling, including classification, clustering, forecast, outlier, and time series models Price forecasting, quality optimization, and insect and disease plant and monitoring in agriculture Fraud detection and prevention, credit scoring, financial planning, and customer analytics Big data in smart grids, smart grid analytics, and predictive smart grid quality monitoring, maintenance, and load forecasting Management of uncertainty in predictive data analytics and probable future developments in the field Intelligent Techniques for Predictive Data Analytics is an essential resource on the subject for professionals and researchers working in data science or data management seeking to understand the different models of predictive analytics, along with graduate students studying data science courses and professionals and academics new to the field.

Rhetorical Machines

Author : John Jones
Publisher : University Alabama Press
ISBN 13 : 0817359540
Total Pages : 294 pages
Book Rating : 4.8/5 (173 download)

DOWNLOAD NOW!

Book Synopsis Rhetorical Machines by : John Jones

Download or read book Rhetorical Machines written by John Jones and published by University Alabama Press. This book was released on 2019-07-02 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: A landmark volume that explores the interconnected nature of technologies and rhetorical practice Rhetorical Machines addresses new approaches to studying computational processes within the growing field of digital rhetoric. While computational code is often seen as value-neutral and mechanical, this volume explores the underlying, and often unexamined, modes of persuasion this code engages. In so doing, it argues that computation is in fact rife with the values of those who create it and thus has powerful ethical and moral implications. From Socrates’s critique of writing in Plato’s Phaedrus to emerging new media and internet culture, the scholars assembled here provide insight into how computation and rhetoric work together to produce social and cultural effects. This multidisciplinary volume features contributions from scholar-practitioners across the fields of rhetoric, computer science, and writing studies. It is divided into four main sections: “Emergent Machines” examines how technologies and algorithms are framed and entangled in rhetorical processes, “Operational Codes” explores how computational processes are used to achieve rhetorical ends, “Ethical Decisions and Moral Protocols” considers the ethical implications involved in designing software and that software’s impact on computational culture, and the final section includes two scholars’ responses to the preceding chapters. Three of the sections are prefaced by brief conversations with chatbots (autonomous computational agents) addressing some of the primary questions raised in each section. At the heart of these essays is a call for emerging and established scholars in a vast array of fields to reach interdisciplinary understandings of human-machine interactions. This innovative work will be valuable to scholars and students in a variety of disciplines, including but not limited to rhetoric, computer science, writing studies, and the digital humanities.

Computational Intelligence in Archaeology

Author : Barcelo, Juan A.
Publisher : IGI Global
ISBN 13 : 1599044919
Total Pages : 436 pages
Book Rating : 4.5/5 (99 download)

DOWNLOAD NOW!

Book Synopsis Computational Intelligence in Archaeology by : Barcelo, Juan A.

Download or read book Computational Intelligence in Archaeology written by Barcelo, Juan A. and published by IGI Global. This book was released on 2008-07-31 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides analytical theories offered by innovative artificial intelligence computing methods in the archaeological domain.

Advanced Computing Technologies and Applications

Author : Hari Vasudevan
Publisher : Springer Nature
ISBN 13 : 9811532427
Total Pages : 686 pages
Book Rating : 4.8/5 (115 download)

DOWNLOAD NOW!

Book Synopsis Advanced Computing Technologies and Applications by : Hari Vasudevan

Download or read book Advanced Computing Technologies and Applications written by Hari Vasudevan and published by Springer Nature. This book was released on 2020-05-06 with total page 686 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book features selected papers presented at the 2nd International Conference on Advanced Computing Technologies and Applications, held at SVKM’s Dwarkadas J. Sanghvi College of Engineering, Mumbai, India, from 28 to 29 February 2020. Covering recent advances in next-generation computing, the book focuses on recent developments in intelligent computing, such as linguistic computing, statistical computing, data computing and ambient applications.

Emerging Memory and Computing Devices in the Era of Intelligent Machines

Author : Pedram Khalili Amiri
Publisher : MDPI
ISBN 13 : 3039285025
Total Pages : 276 pages
Book Rating : 4.0/5 (392 download)

DOWNLOAD NOW!

Book Synopsis Emerging Memory and Computing Devices in the Era of Intelligent Machines by : Pedram Khalili Amiri

Download or read book Emerging Memory and Computing Devices in the Era of Intelligent Machines written by Pedram Khalili Amiri and published by MDPI. This book was released on 2020-04-16 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computing systems are undergoing a transformation from logic-centric towards memory-centric architectures, where overall performance and energy efficiency at the system level are determined by the density, performance, functionality and efficiency of the memory, rather than the logic sub-system. This is driven by the requirements of data-intensive applications in artificial intelligence, autonomous systems, and edge computing. We are at an exciting time in the semiconductor industry where several innovative device and technology concepts are being developed to respond to these demands, and capture shares of the fast growing market for AI-related hardware. This special issue is devoted to highlighting, discussing and presenting the latest advancements in this area, drawing on the best work on emerging memory devices including magnetic, resistive, phase change, and other types of memory. The special issue is interested in work that presents concepts, ideas, and recent progress ranging from materials, to memory devices, physics of switching mechanisms, circuits, and system applications, as well as progress in modeling and design tools. Contributions that bridge across several of these layers are especially encouraged.