Intelligent Estimation : A Soft Computing Paradigm
Jitendra R Raol
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AbeBooks Seller since 14 August 2006
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Add to basketSold by AHA-BUCH GmbH, Einbeck, Germany
AbeBooks Seller since 14 August 2006
Condition: New
Quantity: 2 available
Add to basketNeuware - Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment of a new soft computing framework using AI-based approaches for system identification, parameter estimation, and filtering. This Neuro-Fuzzy-GA-based methodology, succinctly referred to as Intelligent Estimation (IE), integrates these estimation and filtering tasks within a single paradigm.Offering a thorough understanding of soft computing-based estimation concepts and theory, the book discusses a modelling-control-system approach with numerous practical applications in solving mathematical modelling problems for industrial and aerospace engineering systems. It delves into theory, concepts, and various ramifications of neural networks, fuzzy logic, and genetic algorithms for modelling, system identification, filtering, and estimation.This book is intended for upper-level undergraduate and graduate engineering students studying soft computing, intelligent systems, and advanced control systems in industry applications.Instructors will be able to utilize a solutions manual and figure slides for their course.
Seller Inventory # 9781041018230
Intelligent Estimation: A Soft Computing Paradigm presents a unified treatment of a new soft computing framework using AI-based approaches for system identification, parameter estimation, and filtering. This Neuro-Fuzzy-GA-based methodology, succinctly referred to as Intelligent Estimation (IE), integrates these estimation and filtering tasks within a single paradigm.
Offering a thorough understanding of soft computing-based estimation concepts and theory, the book discusses a modelling-control-system approach with numerous practical applications in solving mathematical modelling problems for industrial and aerospace engineering systems. It delves into theory, concepts, and various ramifications of neural networks, fuzzy logic, and genetic algorithms for modelling, system identification, filtering, and estimation.
This book is intended for upper-level undergraduate and graduate engineering students studying soft computing, intelligent systems, and advanced control systems in industry applications.
Instructors will be able to utilize a solutions manual and figure slides for their course.
Jitendra R. Raol received his BE and ME degrees in electrical engineering from M.S. University (MSU) of Baroda, Vadodara, in 1971 and 1973, respectively, and a PhD (in electrical and computer engineering) from McMaster University, Hamilton, Canada, in 1986. He joined the National Aeronautical Laboratory (NAL) in 1975. At CSIR-NAL, he was involved in human pilot modelling in fix- and motion-based research flight simulators. He re-joined NAL in 1986 and retired in July 2007 as Scientist-G (and Head of Flight Mechanics and Control division at CSIR-NAL). He was a fellow of the IEE/IET and a senior member of the IEEE. He is a life-fellow of the Aeronautical Society of India and a life member of the Systems Society of India. Dr. Raol has published nearly 160 research papers and written several books and numerous technical reports. His main research interests include data fusion, system identification, state/parameter estimation, flight mechanics-flight data analysis, H-infinity filtering, nonlinear filtering, artificial neural networks, fuzzy logic systems, genetic algorithms, soft technologies for robotics, and data-systems analytics (DaSyA).
Sara Mohan George holds a BTech in electronics and communication from Mahatma Gandhi University, Kerala, India; MTech and PhD degrees from Visvesvaraya Technological University, Karnataka, India. She is currently an Assistant Professor in Ramaiah Institute of Technology, Bangalore, India. Her research interests include nonlinear filtering, signal processing, and embedded system design. She has published nearly 20 technical papers in various conferences and journals. She is also the co-author of Advances in State and Parameter Estimation: Theory and Practice (CRC Press 2025).
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