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Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling
  • Author : Danilo Comminiello
  • Publsiher : Butterworth-Heinemann
  • Release : 11 June 2018
  • ISBN : 0128129778
  • Pages : 388 pages
  • Rating : 4/5 from 21 ratings
GET THIS BOOKAdaptive Learning Methods for Nonlinear System Modeling

Summary:
Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity introduced by the unknown system. In particular, the methods presented in this book are based on online learning approaches, which process the data example-by-example and allow to model even complex nonlinearities, e.g., showing time-varying and dynamic behaviors. Possible fields of applications of such algorithms includes distributed sensor networks, wireless communications, channel identification, predictive maintenance, wind prediction, network security, vehicular networks, active noise control, information forensics and security, tracking control in mobile robots, power systems, and nonlinear modeling in big data, among many others. This book serves as a crucial resource for researchers, PhD and post-graduate students working in the areas of machine learning, signal processing, adaptive filtering, nonlinear control, system identification, cooperative systems, computational intelligence. This book may be also of interest to the industry market and practitioners working with a wide variety of nonlinear systems. Presents the key trends and future perspectives in the field of nonlinear signal processing and adaptive learning. Introduces novel solutions and improvements over the state-of-the-art methods in the very exciting area of online and adaptive nonlinear identification. Helps readers understand important methods that are effective in nonlinear system modelling, suggesting the right methodology to address particular issues.


Adaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling
  • Author : Danilo Comminiello,Jose C. Principe
  • Publisher : Butterworth-Heinemann
  • Release : 11 June 2018
GET THIS BOOKAdaptive Learning Methods for Nonlinear System Modeling

Adaptive Learning Methods for Nonlinear System Modeling presents some of the recent advances on adaptive algorithms and machine learning methods designed for nonlinear system modeling and identification. Real-life problems always entail a certain degree of nonlinearity, which makes linear models a non-optimal choice. This book mainly focuses on those methodologies for nonlinear modeling that involve any adaptive learning approaches to process data coming from an unknown nonlinear system. By learning from available data, such methods aim at estimating the nonlinearity

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Modelling, Simulation and Applications of Complex Systems

Modelling, Simulation and Applications of Complex Systems
  • Author : Mohd Hafiz Mohd,Md Yushalify Misro,Syakila Ahmad,Doanh Nguyen Ngoc
  • Publisher : Springer Nature
  • Release : 16 May 2022
GET THIS BOOKModelling, Simulation and Applications of Complex Systems

This book discusses the latest progresses and developments on complex systems research and intends to give an exposure to prospective readers about the theoretical and practical aspects of mathematical modelling, numerical simulation and agent-based modelling frameworks. The main purpose of this book is to emphasize a unified approach to complex systems analysis, which goes beyond to examine complicated phenomena of numerous real-life systems; this is done by investigating a huge number of components that interact with each other at different (

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The First Outstanding 50 Years of “Università Politecnica delle Marche”

The First Outstanding 50 Years of “Università Politecnica delle Marche”
  • Author : Sauro Longhi,Andrea Monteriù,Alessandro Freddi,Emanuele Frontoni,Michele Germani,Gian Marco Revel
  • Publisher : Springer Nature
  • Release : 16 December 2019
GET THIS BOOKThe First Outstanding 50 Years of “Università Politecnica delle Marche”

The book describes the significant multidisciplinary research findings at the Università Politecnica delle Marche and the expected future advances. It addresses some of the most dramatic challenges posed by today’s fast-growing, global society and the changes it has caused. It also discusses solutions to improve the wellbeing of human beings. The book covers the main research achievements in the different disciplines of the physical sciences and engineering, as well as several research lines developed at the university’s Faculty

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XIV International Scientific Conference “INTERAGROMASH 2021"

XIV International Scientific Conference “INTERAGROMASH 2021
  • Author : Alexey Beskopylny,Mark Shamtsyan
  • Publisher : Springer Nature
  • Release : 01 December 2021
GET THIS BOOKXIV International Scientific Conference “INTERAGROMASH 2021"

This book contains original and fundamental research papers in the following areas: engineering technologies for precision agriculture, agricultural systems management and digitalization in agriculture, logistics in agriculture, and other topics. Selected materials of the largest regional scientific event—INTERAGROMASH 2021 conference–included in this book present the results of the latest research in the areas of precision agriculture and agricultural machinery industry. The book is aimed for professionals and practitioners, for researchers, scholars, and producers. The materials presented here are used

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Latest Trends in Renewable Energy Technologies

Latest Trends in Renewable Energy Technologies
  • Author : Shelly Vadhera,Bhimrao S. Umre,Akhtar Kalam
  • Publisher : Springer Nature
  • Release : 01 July 2021
GET THIS BOOKLatest Trends in Renewable Energy Technologies

This book presents select proceedings of the National Conference on Renewable Energy and Sustainable Environment (NCRESE 2020) and examines a range of reliable energy-efficient harvesting technologies, their applications and utilization of available alternate energy resources. The topics covered include alternate energy technologies, smart grid topologies and their relevant issues, solar thermal and bio-energy systems, electric vehicles and energy storage systems and its control issues. The book also discusses various properties and performance attributes of advance renewable energy techniques and impact on

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Concept of Adaptive Filtering & Spline Adaptive Filtering Algorithm

Concept of Adaptive Filtering & Spline Adaptive Filtering Algorithm
  • Author : Shivendra Nandan
  • Publisher : The Shivendra Group
  • Release : 16 May 2022
GET THIS BOOKConcept of Adaptive Filtering & Spline Adaptive Filtering Algorithm

A spline adaptive filter (SAF) based nonlinear active noise control (ANC) system is proposed in this paper. The SAF consists of a linear network of adaptive weights in a cascade with an adaptive nonlinear network. The nonlinear network, in turn consists of an adaptive look-up table followed by a spline interpolation network and forms an adaptive activation function. An update rule has been derived for the proposed ANC system, which not only updates the weights of the linear network, but

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Lagrangian and Hamiltonian Methods for Nonlinear Control 2003

Lagrangian and Hamiltonian Methods for Nonlinear Control 2003
  • Author : A Astolfi,Francisco Gordillo,A J Van Der Schaft
  • Publisher : Elsevier
  • Release : 21 October 2003
GET THIS BOOKLagrangian and Hamiltonian Methods for Nonlinear Control 2003

This is the second of a series of IFAC Workshops initiated in 2000. The first one chaired and organized by Profs. N. Leonard and R. Ortega, was held in Princeton in March 2000. This proceedings volume looks at the role-played by Lagrangian and Hamiltonian methods in disciplines such as classical mechanics, quantum mechanics, fluid dynamics, electrodynamics, celestial mechanics and how such methods can be practically applied in the control community. *Presents and illustrates new approaches to nonlinear control that exploit the Lagrangian

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Intelligent Systems

Intelligent Systems
  • Author : Cornelius T. Leondes
  • Publisher : CRC Press
  • Release : 08 October 2018
GET THIS BOOKIntelligent Systems

Intelligent systems, or artificial intelligence technologies, are playing an increasing role in areas ranging from medicine to the major manufacturing industries to financial markets. The consequences of flawed artificial intelligence systems are equally wide ranging and can be seen, for example, in the programmed trading-driven stock market crash of October 19, 1987. Intelligent Systems: Technology and Applications, Six Volume Set connects theory with proven practical applications to provide broad, multidisciplinary coverage in a single resource. In these volumes, international experts present case-study

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Algorithms and Architectures for Real-Time Control 1991

Algorithms and Architectures for Real-Time Control 1991
  • Author : P.J. Fleming,D.I. Jones
  • Publisher : Elsevier
  • Release : 22 July 2014
GET THIS BOOKAlgorithms and Architectures for Real-Time Control 1991

Computer scientists have long appreciated that the relationship between algorithms and architecture is crucial. Broadly speaking the more specialized the architecture is to a particular algorithm then the more efficient will be the computation. The penalty is that the architecture will become useless for computing anything other than that algorithm. This message holds for the algorithms used in real-time automatic control as much as any other field. These Proceedings will provide researchers in this field with a useful up-to-date reference

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State-Space Approaches for Modelling and Control in Financial Engineering

State-Space Approaches for Modelling and Control in Financial Engineering
  • Author : Gerasimos G. Rigatos
  • Publisher : Springer
  • Release : 04 April 2017
GET THIS BOOKState-Space Approaches for Modelling and Control in Financial Engineering

The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black–Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to

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Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications
  • Author : Alma Y. Alanis,Nancy Arana-Daniel,Carlos Lopez-Franco
  • Publisher : Academic Press
  • Release : 07 February 2019
GET THIS BOOKArtificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the

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Process Neural Networks

Process Neural Networks
  • Author : Xingui He,Shaohua Xu
  • Publisher : Springer Science & Business Media
  • Release : 05 July 2010
GET THIS BOOKProcess Neural Networks

For the first time, this book sets forth the concept and model for a process neural network. You’ll discover how a process neural network expands the mapping relationship between the input and output of traditional neural networks and greatly enhances the expression capability of artificial neural networks. Detailed illustrations help you visualize information processing flow and the mapping relationship between inputs and outputs.

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Adaptive Dynamic Programming for Control

Adaptive Dynamic Programming for Control
  • Author : Huaguang Zhang,Derong Liu,Yanhong Luo,Ding Wang
  • Publisher : Springer Science & Business Media
  • Release : 14 December 2012
GET THIS BOOKAdaptive Dynamic Programming for Control

There are many methods of stable controller design for nonlinear systems. In seeking to go beyond the minimum requirement of stability, Adaptive Dynamic Programming in Discrete Time approaches the challenging topic of optimal control for nonlinear systems using the tools of adaptive dynamic programming (ADP). The range of systems treated is extensive; affine, switched, singularly perturbed and time-delay nonlinear systems are discussed as are the uses of neural networks and techniques of value and policy iteration. The text features three

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Self-Learning Optimal Control of Nonlinear Systems

Self-Learning Optimal Control of Nonlinear Systems
  • Author : Qinglai Wei,Ruizhuo Song,Benkai Li,Xiaofeng Lin
  • Publisher : Springer
  • Release : 13 June 2017
GET THIS BOOKSelf-Learning Optimal Control of Nonlinear Systems

This book presents a class of novel, self-learning, optimal control schemes based on adaptive dynamic programming techniques, which quantitatively obtain the optimal control schemes of the systems. It analyzes the properties identified by the programming methods, including the convergence of the iterative value functions and the stability of the system under iterative control laws, helping to guarantee the effectiveness of the methods developed. When the system model is known, self-learning optimal control is designed on the basis of the system

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