Yuriy S. Shmaliy – författare

Since 1960-1961, when Rudolf E. Kalman has published his seminal work on discrete-time recursive optimal filtering and, together with Richard S. Bucy, on continuous-time optimal filtering of linear nonstationary stochastic processes with white Gaussian noise, recursive filtering and smoothing algorithm have become and still remain a key tool for real-time state estimation. This is despite the fact that Bayesian and convolution-based approaches say that optimal recursions are only available for white Gaussian and colored Gauss-Markov noise. Otherwise, since non-Gaussian noise has high-order statistics, the hypothetical recursive forms seem to be so complex that it is hardly practical to use them instead of batch forms. Therefore, recursive forms are widely used, although this often calls into question their accuracy in harsh environments.When solving state estimation problems for signal processing and control using recursive algorithms, researchers traditionally associate them with Kalman filtering, even when not using all its recursive forms. This is even though some solutions, such as the robust iterative UFIR filter, as well as the transfer function-based H∞ filter, generalized H2 filter, L1 filter, etc., have nothing to do with Kalman filtering. Moreover, data-driven and AI-aided model-based filtering algorithms also lose connection to it. This leads to the idea that instead of thinking of recursive algorithms as Kalman-like, it is worth focusing on the general recursive form and cover all available recursive state estimators under one umbrella, treating Kalman filter is a special case.This book attempts to do this by describing 53 pseudo codes and other forms of optimal, suboptimal, and robust recursive state estimation algorithms.

A unified and systematic theoretical framework for solving problems related to finite impulse response (FIR) estimate Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches is a comprehensive investigation into batch state estimators and recursive forms. The work begins by introducing the reader to the state estimation approach and provides a brief historical overview. Next, the work discusses the specific properties of finite impulse response (FIR) state estimators. Further chapters give the basics of probability and stochastic processes, discuss the available linear and nonlinear state estimators, deal with optimal FIR filtering, and consider a limited memory batch and recursive algorithms. Other topics covered include solving the q-lag FIR smoothing problem, introducing the receding horizon (RH) FIR state estimation approach, and developing the theory of FIR state estimation under disturbances. The book closes by discussing the theory of FIR state estimation for uncertain systems and providing several applications where the FIR state estimators are used effectively. Key concepts covered in the work include: A holistic overview of the state estimation approach, which arose from the need to know the internal state of a real system, given that the input and output are both knownOptimal, optimal unbiased, maximum likelihood, and unbiased and robust finite impulse response (FIR) structuresFIR state estimation approach along with the infinite impulse response (IIR) and Kalman approachesCost functions and the most critical properties of FIR and IIR state estimates Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches was written for professionals in the fields of microwave engineering, system engineering, and robotics who wish to move towards solving finite impulse response (FIR) estimate issues in both theoretical and practical applications. Graduate and senior undergraduate students with coursework dealing with state estimation will also be able to use the book to gain a valuable foundation of knowledge and become more adept in their chosen fields of study.

This book provides readers with modern computational techniques for solving variety of problems from electrical, mechanical, civil and chemical engineering.

This proceedings focus on selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities and associations from around the world to help address the world’s computing, control and industrial engineering.

This book collects selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities, and associations from CCIE 2024, to help address the world’s advanced computing, control technology, information technology, artificial intelligence, machine learning, deep learning, and neural networks. Meanwhile, the topics included in the proceedings have high research value and present current insights, developments, and trends in computing, control, and industrial engineering.

This book collects selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities, and associations from CCIE 2024, to help address the world’s advanced computing, control technology, information technology, artificial intelligence, machine learning, deep learning, and neural networks. Meanwhile, the topics included in the proceedings have high research value and present current insights, developments, and trends in computing, control, and industrial engineering.

This book collects selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities, and associations from CCIE 2024, to help address the world’s advanced computing, control technology, information technology, artificial intelligence, machine learning, deep learning, and neural networks. Meanwhile, the topics included in the proceedings have high research value and present current insights, developments, and trends in computing, control, and industrial engineering.

This book collects selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities, and associations from CCIE 2024, to help address the world’s advanced computing, control technology, information technology, artificial intelligence, machine learning, deep learning, and neural networks. Meanwhile, the topics included in the proceedings have high research value and present current insights, developments, and trends in computing, control, and industrial engineering.

This book collects selected aspects of recent advances and experiences, emerging technology trends that have positively impacted our world from operators, authorities, and associations from CCIE 2022, to help address the world’s advanced computing, control technology, information technology, artificial intelligence, machine learning, deep learning, and neural networks. Meanwhile, the topics included in the proceedings have high research value and present current insights, developments, and trends in computing, control, and industrial engineering.