Kindly note that we have put a lot of effort into researching the best books on Estimation and Identification subject and came out with a recommended list of top 10 best books. The table below contains the Name of these best books, their authors, publishers and an unbiased review of books on "Estimation and Identification" as well as links to the Amazon website to directly purchase these books. As an Amazon Associate, we earn from qualifying purchases, but this does not impact our reviews, comparisons, and listing of these top books; the table serves as a ready reckoner list of these best books.
|1. “System Identification Theory for the User” by L Ljung
Book Review: Appropriate for courses in System Identification. This book is a comprehensive and coherent description of the theory, methodology and practice of System Identification-the science of building mathematical models of dynamic systems by observing input/output data. It puts the user in focus, giving the necessary background to understand theoretical foundation and emphasizing the practical aspects of the options and choices that face the user. The Second Edition has been updated to include material on subspace methods, non-linear black box models-such as neural networks-and methods that use frequency domain data.
|2. “Random Signals Estimation and Identification: Analysis and Applications” by Nirode Mohanty
“Random Signals Estimation and Identification: Analysis and Applications” Book Review: This book presents a comprehensive introduction to random signal analysis, estimation, filtering, and identification by focusing on its computational aspects. Common analytical tools for systems involving random signals are also covered in detail. Essential topics covered in this book include random processes, stationary signals, estimation, spectrum estimation, spectral analysis, filtering, optimization, detection, prediction, and identification. The algorithms presented in this book can also be successfully applied to industrial projects. Exposure to basic probability and linear algebra is assumed. The book is ideal for practicing engineers, scientists, undergraduate and graduate students studying random processes, estimation theory, and system identification.
|3. “Spectrum Estimation and System Identification” by Theodore I Shim S Unnikrishna Pillai Shim Pillai
“Spectrum Estimation and System Identification” Book Review: This book presents a new outlook to spectrum estimation and system identification with the help of positive functions and bounded functions. These powerful concepts have been indispensable in analyzing various signal processing problems, interpolation problems, and the system identification problem from a different perspective. Rational and stable approximation of non-rational transfer functions in the single-channel case and the multichannel case are examined for its applications in distributed system theory, analysis of differential equations with delays, and simulation of systems governed by partial differential equations. This book is suitable for engineers, researchers, and graduate level students.
|4. “State Estimation Techniques: Identification of Parameters of Finite Element Models” by Ahmed Nasrellah Hassan Dr
“State Estimation Techniques: Identification of Parameters of Finite Element Methods” Book Review: This book reviews the development and application of some dynamic state estimation based methods for estimation of parameters of vibrating structures. The text introduces a pseudo-time parameter to investigate strategies for data fusion from multiple tests of different types and quantities of sensor within the framework of Kalman and Particle filtering techniques. A discussion on using finite element models in commercially available softwares to communicate with databases of measurements via particle filtering algorithm developed on MATLAB is also included. The proposed methods are applied to finite element model updating of bridge structures and vehicle structure interaction problems.
|5. “Recursive Identification and Parameter Estimation” by Chen Zhao
“Recursive Identification and Parameter Estimation” Book Review: This book solves system identification and parameter estimation problems arising from diverse areas using a recursive approach. The book starts with an introduction to crucial topics such as probability theory, martingales, martingale difference sequences, Markov chains, mixing processes, and stationary processes. It then addresses the root-seeking problem for functions solved using the classic RM algorithm and SAAWET. Readers can also learn to recursively identify ARMAX systems as well as nonlinear systems. Theoretical analysis and proposed algorithms are provided to help develop modeling and identification skills to successful research and application. The book is designed for students, researchers, and engineers working in systems and control, signal processing, communication, and mathematical statistics.
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