Neural Based Orthogonal Data Fitting
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Neural Based Orthogonal Data Fitting
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Author : Giansalvo Cirrincione
language : en
Publisher: John Wiley & Sons
Release Date : 2011-04-06
Neural Based Orthogonal Data Fitting written by Giansalvo Cirrincione and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-04-06 with Mathematics categories.
The presentation of a novel theory in orthogonal regression The literature about neural-based algorithms is often dedicated to principal component analysis (PCA) and considers minor component analysis (MCA) a mere consequence. Breaking the mold, Neural-Based Orthogonal Data Fitting is the first book to start with the MCA problem and arrive at important conclusions about the PCA problem. The book proposes several neural networks, all endowed with a complete theory that not only explains their behavior, but also compares them with the existing neural and traditional algorithms. EXIN neurons, which are of the authors' invention, are introduced, explained, and analyzed. Further, it studies the algorithms as a differential geometry problem, a dynamic problem, a stochastic problem, and a numerical problem. It demonstrates the novel aspects of its main theory, including its applications in computer vision and linear system identification. The book shows both the derivation of the TLS EXIN from the MCA EXIN and the original derivation, as well as: Shows TLS problems and gives a sketch of their history and applications Presents MCA EXIN and compares it with the other existing approaches Introduces the TLS EXIN neuron and the SCG and BFGS acceleration techniques and compares them with TLS GAO Outlines the GeTLS EXIN theory for generalizing and unifying the regression problems Establishes the GeMCA theory, starting with the identification of GeTLS EXIN as a generalization eigenvalue problem In dealing with mathematical and numerical aspects of EXIN neurons, the book is mainly theoretical. All the algorithms, however, have been used in analyzing real-time problems and show accurate solutions. Neural-Based Orthogonal Data Fitting is useful for statisticians, applied mathematics experts, and engineers.
Efficient Online Learning Algorithms For Total Least Square Problems
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Author : Xiangyu Kong
language : en
Publisher: Springer Nature
Release Date : 2024-07-17
Efficient Online Learning Algorithms For Total Least Square Problems written by Xiangyu Kong and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-17 with Mathematics categories.
This book reports the developments of the Total Least Square (TLS) algorithms for parameter estimation and adaptive filtering. Specifically, it introduces the authors’ latest achievements in the past 20 years, including the recursive TLS algorithms, the approximate inverse power iteration TLS algorithm, the neural based MCA algorithm, the neural based SVD algorithm, the neural based TLS algorithm, the TLS algorithms under non-Gaussian noises, performance analysis methods of TLS algorithms, etc. In order to faster the understanding and mastering of the new methods provided in this book for readers, before presenting each new method in each chapter, a specialized section is provided to review the closely related several basis models. Throughout the book, large of procedure of new methods are provided, and all new algorithms or methods proposed by us are tested and verified by numerical simulations or actual engineering applications. Readers will find illustrative demonstration examples on a range of industrial processes to study. Readers will find out the present deficiency and recent developments of the TLS parameter estimation fields, and learn from the the authors’ latest achievements or new methods around the practical industrial needs. In my opinion, this book can be assimilated by advanced undergraduates and graduate students, as well as statisticians, because of the new tools in data analysis, applied mathematics experts, because of the novel theories and techniques that we propose, engineers, above all for the applications in control, system identification, computer vision, and signal processing.
Fundamentals Of Cognitive Radio
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Author : Peyman Setoodeh
language : en
Publisher: John Wiley & Sons
Release Date : 2017-07-06
Fundamentals Of Cognitive Radio written by Peyman Setoodeh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-07-06 with Technology & Engineering categories.
A comprehensive treatment of cognitive radio networks and the specialized techniques used to improve wireless communications The human brain, as exemplified by cognitive radar, cognitive radio, and cognitive computing, inspires the field of Cognitive Dynamic Systems. In particular, cognitive radio is growing at an exponential rate. Fundamentals of Cognitive Radio details different aspects of the human brain and provides examples of how it can be mimicked by cognitive dynamic systems. The text offers a communication-theoretic background, including information on resource allocation in wireless networks and the concept of robustness. The authors provide a thorough mathematical background with data on game theory, variational inequalities, and projected dynamic systems. They then delve more deeply into resource allocation in cognitive radio networks. The text investigates the dynamics of cognitive radio networks from the perspectives of information theory, optimization, and control theory. It also provides a vision for the new world of wireless communications by integration of cellular and cognitive radio networks. This groundbreaking book: Shows how wireless communication systems increasingly use cognition to enhance their networks Explores how cognitive radio networks can be viewed as spectrum supply chain networks Derives analytic models for two complementary regimes for spectrum sharing (open-access and market-driven) to study both equilibrium and disequilibrium behaviors of networks Studies cognitive heterogeneous networks with emphasis on economic provisioning for resource sharing Introduces a framework that addresses the issue of spectrum sharing across licensed and unlicensed bands aimed for Pareto optimality Written for students of cognition, communication engineers, telecommunications professionals, and others, Fundamentals of Cognitive Radio offers a new generation of ideas and provides a fresh way of thinking about cognitive techniques in order to improve radio networks.
Bayesian Signal Processing
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Author : James V. Candy
language : en
Publisher: John Wiley & Sons
Release Date : 2016-06-20
Bayesian Signal Processing written by James V. Candy and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-20 with Technology & Engineering categories.
Presents the Bayesian approach to statistical signal processing for a variety of useful model sets This book aims to give readers a unified Bayesian treatment starting from the basics (Baye’s rule) to the more advanced (Monte Carlo sampling), evolving to the next-generation model-based techniques (sequential Monte Carlo sampling). This next edition incorporates a new chapter on “Sequential Bayesian Detection,” a new section on “Ensemble Kalman Filters” as well as an expansion of Case Studies that detail Bayesian solutions for a variety of applications. These studies illustrate Bayesian approaches to real-world problems incorporating detailed particle filter designs, adaptive particle filters and sequential Bayesian detectors. In addition to these major developments a variety of sections are expanded to “fill-in-the gaps” of the first edition. Here metrics for particle filter (PF) designs with emphasis on classical “sanity testing” lead to ensemble techniques as a basic requirement for performance analysis. The expansion of information theory metrics and their application to PF designs is fully developed and applied. These expansions of the book have been updated to provide a more cohesive discussion of Bayesian processing with examples and applications enabling the comprehension of alternative approaches to solving estimation/detection problems. The second edition of Bayesian Signal Processing features: “Classical” Kalman filtering for linear, linearized, and nonlinear systems; “modern” unscented and ensemble Kalman filters: and the “next-generation” Bayesian particle filters Sequential Bayesian detection techniques incorporating model-based schemes for a variety of real-world problems Practical Bayesian processor designs including comprehensive methods of performance analysis ranging from simple sanity testing and ensemble techniques to sophisticated information metrics New case studies on adaptive particle filtering and sequential Bayesian detection are covered detailing more Bayesian approaches to applied problem solving MATLAB® notes at the end of each chapter help readers solve complex problems using readily available software commands and point out other software packages available Problem sets included to test readers’ knowledge and help them put their new skills into practice Bayesian Signal Processing, Second Edition is written for all students, scientists, and engineers who investigate and apply signal processing to their everyday problems.
Proceedings Of The 4th International Conference Engineering Innovations And Sustainable Development
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Author : Valentina Mantulenko
language : en
Publisher: Springer Nature
Release Date : 2025-07-10
Proceedings Of The 4th International Conference Engineering Innovations And Sustainable Development written by Valentina Mantulenko and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-10 with Business & Economics categories.
This book presents the contributions from the 4th International Conference Engineering Innovations and Sustainable Development, held in Samara, Russia, on February 27, 2025. By presenting international research on various sustainability issues, it includes topics such as current trends in industrial and agricultural development, innovations in the construction and transport sectors, problems concerning the financing of innovative activities and governmental support for innovations, and engineering competences and skills in the era of new technologies. It also covers the economic, environmental, and informational aspects of sustainable development in the context of innovations. Finally, the book addresses theoretical and practical aspects by studying the phenomenon of sustainability and engineering development in terms of comparing international experiences. It provides significant value for scientists, teachers, and students of higher educational institutions, and specialists, who are researching sustainable development issues in the era of engineering innovations.
Power Converters And Ac Electrical Drives With Linear Neural Networks
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Author : Maurizio Cirrincione
language : en
Publisher: CRC Press
Release Date : 2017-12-19
Power Converters And Ac Electrical Drives With Linear Neural Networks written by Maurizio Cirrincione and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-19 with Technology & Engineering categories.
The first book of its kind, Power Converters and AC Electrical Drives with Linear Neural Networks systematically explores the application of neural networks in the field of power electronics, with particular emphasis on the sensorless control of AC drives. It presents the classical theory based on space-vectors in identification, discusses control of electrical drives and power converters, and examines improvements that can be attained when using linear neural networks. The book integrates power electronics and electrical drives with artificial neural networks (ANN). Organized into four parts, it first deals with voltage source inverters and their control. It then covers AC electrical drive control, focusing on induction and permanent magnet synchronous motor drives. The third part examines theoretical aspects of linear neural networks, particularly the neural EXIN family. The fourth part highlights original applications in electrical drives and power quality, ranging from neural-based parameter estimation and sensorless control to distributed generation systems from renewable sources and active power filters. Simulation and experimental results are provided to validate the theories. Written by experts in the field, this state-of-the-art book requires basic knowledge of electrical machines and power electronics, as well as some familiarity with control systems, signal processing, linear algebra, and numerical analysis. Offering multiple paths through the material, the text is suitable for undergraduate and postgraduate students, theoreticians, practicing engineers, and researchers involved in applications of ANNs.
Robust And Regularized Algorithms For Vehicle Tractive Force Prediction And Mass Estimation
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Author : Rhode, Stephan
language : en
Publisher: KIT Scientific Publishing
Release Date : 2018-10-01
Robust And Regularized Algorithms For Vehicle Tractive Force Prediction And Mass Estimation written by Rhode, Stephan and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-01 with Mass categories.
This work provides novel robust and regularized algorithms for parameter estimation with applications in vehicle tractive force prediction and mass estimation. Given a large record of real world data from test runs on public roads, recursive algorithms adjusted the unknown vehicle parameters under a broad variation of statistical assumptions for two linear gray-box models.
Data Variant Kernel Analysis
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Author : Yuichi Motai
language : en
Publisher: John Wiley & Sons
Release Date : 2015-04-27
Data Variant Kernel Analysis written by Yuichi Motai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-27 with Computers categories.
Describes and discusses the variants of kernel analysis methods for data types that have been intensely studied in recent years This book covers kernel analysis topics ranging from the fundamental theory of kernel functions to its applications. The book surveys the current status, popular trends, and developments in kernel analysis studies. The author discusses multiple kernel learning algorithms and how to choose the appropriate kernels during the learning phase. Data-Variant Kernel Analysis is a new pattern analysis framework for different types of data configurations. The chapters include data formations of offline, distributed, online, cloud, and longitudinal data, used for kernel analysis to classify and predict future state. Data-Variant Kernel Analysis: Surveys the kernel analysis in the traditionally developed machine learning techniques, such as Neural Networks (NN), Support Vector Machines (SVM), and Principal Component Analysis (PCA) Develops group kernel analysis with the distributed databases to compare speed and memory usages Explores the possibility of real-time processes by synthesizing offline and online databases Applies the assembled databases to compare cloud computing environments Examines the prediction of longitudinal data with time-sequential configurations Data-Variant Kernel Analysis is a detailed reference for graduate students as well as electrical and computer engineers interested in pattern analysis and its application in colon cancer detection.
Non Bf Slag Based Green Cementitious Materials
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Author : Lijie Guo
language : en
Publisher: Frontiers Media SA
Release Date : 2022-08-12
Non Bf Slag Based Green Cementitious Materials written by Lijie Guo 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 2022-08-12 with Technology & Engineering categories.
Machine Learning
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Author : Abdelhamid Mellouk
language : en
Publisher: BoD – Books on Demand
Release Date : 2009-01-01
Machine Learning written by Abdelhamid Mellouk and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-01-01 with Computers categories.
Machine Learning can be defined in various ways related to a scientific domain concerned with the design and development of theoretical and implementation tools that allow building systems with some Human Like intelligent behavior. Machine learning addresses more specifically the ability to improve automatically through experience.