For New condition books in our store; You will be the first user. You will be the first to open the book cover. For Used condition books in our store; It shows signs of wear from consistent use, but it remains in good condition and works perfectly. There are no problems in page content and in the paper. There are no problems except minor faults. All pages and cover are intact , but may have aesthetic issues such as price clipping, nicks, scratches, and scuffs. Pages may include some notes and highlighting. For all our books; Cargo will be delivered in the required time. 100% Satisfaction is Guaranteed!

Advances in Distributed Sensor Integration: Application and Theory (Prentice Hall Series on Environmental and Intelligent Manufacturing systems)

Computers & Technology

Iyengar, S. S.

Prasad, L.

Min, H.

Networking & Cloud Computing

PRENTICE/HALL

Understand multi-sensor fusion--the most sophisticated way to deliver accurate real-world data to computer systems. Applications include aviation, medicine, military, manufacturing, and transportation. The Sensor Fusion Toolkit on disk contains C programs discussed in the book and supports each section.

Multi-Sensor Fusion: Fundamentals and Applications With Software

Brooks, R.R.

Versatile solutions to routing network flows in unpredictable circumstances, presenting both mathematical tools and applications.
Our increasingly integrated world relies on networks both physical and virtual to transfer goods and information. The Internet is a network of networks that connects people around the world in a real-time manner, but it can be disrupted by massive data flows, diverse traffic patterns, inadequate infrastructure, and even natural disasters and political conflict. Similar challenges exist for transportation and energy distribution networks. There is an urgent need for intelligent and adaptable routing of network flows, and a rich literature has evolved that treats “oblivious network design.” This book offers novel computational schemes for efficiently solving routing problems in unpredictable circumstances and proposes some real world applications for them. The versatile routing schemes mathematically guarantee long-term efficiency and are most appropriate for networks with non-deterministic (or oblivious) current and past states. 
After an introduction to network design and the importance of routing problems, the book presents mathematical tools needed to construct versatile routing schemes, emphasizing the role of linked hierarchical data structures, both top-down and bottom-up. It then describes two important applications of versatile routing schemes: a secure model for congestion-free content-centric networks (which will play a key role in the future of the Internet) and a novel approach for the distribution of green power resources on a smart electricity grid.

Oblivious Network Routing: Algorithms and Applications

Boroojeni, Kianoosh G.

Mit Pr

Parallel algorithms Made Easy The complexity of today's applications coupled with the widespread use of parallel computing has made the design and analysis of parallel algorithms topics of growing interest. This volume fills a need in the field for an introductory treatment of parallel algorithms-appropriate even at the undergraduate level, where no other textbooks on the subject exist. It features a systematic approach to the latest design techniques, providing analysis and implementation details for each parallel algorithm described in the book. Introduction to Parallel Algorithms covers foundations of parallel computing; parallel algorithms for trees and graphs; parallel algorithms for sorting, searching, and merging; and numerical algorithms. This remarkable book: * Presents basic concepts in clear and simple terms * Incorporates numerous examples to enhance students' understanding * Shows how to develop parallel algorithms for all classical problems in computer science, mathematics, and engineering * Employs extensive illustrations of new design techniques * Discusses parallel algorithms in the context of PRAM model * Includes end-of-chapter exercises and detailed references on parallel computing. This book enables universities to offer parallel algorithm courses at the senior undergraduate level in computer science and engineering. It is also an invaluable text/reference for graduate students, scientists, and engineers in computer science, mathematics, and engineering.

Introduction to Parallel Algorithms

Xavier, C.

Games & Strategy Guides

Wiley-Interscience

This is the only book to cover infrastructure aspects of sensor networks in a comprehensive fashion. The only other books on sensor networks do not cover this topic or do so only superficially as part of a less-focussed multi-authored treatment.

Scalable Infrastructure for Distributed Sensor Networks

Computer Science

Springer

This is the only book to cover infrastructure aspects of sensor networks in a comprehensive fashion. The only other books on sensor networks do not cover this topic or do so only superficially as part of a less-focussed multi-authored treatment.

Mathematical Theories of Machine Learning - Theory and Applications

This book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle points in non-convex optimization problems. In the second part, the authors propose algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries. In the last part, the authors introduce an novel VAR model with Elastic-Net regularization and its equivalent Bayesian model allowing for both a stable sparsity and a group selection.

Business & Money

Shi, Bin

Industries

Review\n“The book discusses mathematical theories of machine learning. … The book is very technically written and it is addressed to professionals in the field.” (Smaranda Belciug, zbMATH 1422.68003, 2019)\nThis book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle points in non-convex optimization problems. In the second part, the authors propose algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries. In the last part, the authors introduce an novel VAR model with Elastic-Net regularization and its equivalent Bayesian model allowing for both a stable sparsity and a group selection.\nFrom the Back Cover\nThis book studies mathematical theories of machine learning. The first part of the book explores the optimality and adaptivity of choosing step sizes of gradient descent for escaping strict saddle points in non-convex optimization problems. In the second part, the authors propose algorithms to find local minima in nonconvex optimization and to obtain global minima in some degree from the Newton Second Law without friction. In the third part, the authors study the problem of subspace clustering with noisy and missing data, which is a problem well-motivated by practical applications data subject to stochastic Gaussian noise and/or incomplete data with uniformly missing entries. In the last part, the authors introduce an novel VAR model with Elastic-Net regularization and its equivalent Bayesian model allowing for both a stable sparsity and a group selection. 
Provides a thorough look into the variety of mathematical theories of machine learning Presented in four parts, allowing for readers to easily navigate the complex theories Includes extensive empirical studies on both the synthetic and real application time series data

This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems.&nbsp;

Deep Learning Networks: Design, Development and Deployment

Madni, Azad M.

Singaram, Jayakumar

This book provides a thorough treatment of privacy and security issues for researchers in the fields of smart grids, engineering, and computer science. It presents comprehensive insight to understanding the big picture of privacy and security challenges in both physical and information aspects of smart grids. The authors utilize an advanced interdisciplinary approach to address the existing security and privacy issues and propose legitimate countermeasures for each of them in the standpoint of both computing and electrical engineering. The proposed methods are theoretically proofed by mathematical tools and illustrated by real-world examples.

Smart Grids: Security and Privacy Issues

Amini, M. Hadi

See the best price to sell, buy, or rent books by Iyengar, S. S.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Books by Iyengar, S. S.

See the best price to sell, buy, or rent books by Iyengar, S. S.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

Advances in Distributed Sensor Integration: Application and Theory (Prentice Hall Series on Environmental and Intelligent Manufacturing systems)

Multi-Sensor Fusion: Fundamentals and Applications With Software

Oblivious Network Routing: Algorithms and Applications

Introduction to Parallel Algorithms

Scalable Infrastructure for Distributed Sensor Networks

Scalable Infrastructure for Distributed Sensor Networks

Mathematical Theories of Machine Learning - Theory and Applications

Mathematical Theories of Machine Learning - Theory and Applications

Deep Learning Networks: Design, Development and Deployment

Smart Grids: Security and Privacy Issues