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System Identification with Quantized Observations

System Identification with Quantized Observations PDF Author: Le Yi Wang
Publisher: Springer Science & Business Media
ISBN: 0817649565
Category : Science
Languages : en
Pages : 317

Book Description
This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed. System Identification with Quantized Observations is an excellent resource for graduate students, systems theorists, control engineers, applied mathematicians, as well as practitioners who use identification algorithms in their work.

System Identification with Quantized Observations

System Identification with Quantized Observations PDF Author: Le Yi Wang
Publisher: Springer Science & Business Media
ISBN: 0817649565
Category : Science
Languages : en
Pages : 317

Book Description
This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed. System Identification with Quantized Observations is an excellent resource for graduate students, systems theorists, control engineers, applied mathematicians, as well as practitioners who use identification algorithms in their work.

System Identification Using Regular and Quantized Observations

System Identification Using Regular and Quantized Observations PDF Author: Qi He
Publisher: Springer Science & Business Media
ISBN: 1461462924
Category : Science
Languages : en
Pages : 100

Book Description
​This brief presents characterizations of identification errors under a probabilistic framework when output sensors are binary, quantized, or regular. By considering both space complexity in terms of signal quantization and time complexity with respect to data window sizes, this study provides a new perspective to understand the fundamental relationship between probabilistic errors and resources, which may represent data sizes in computer usage, computational complexity in algorithms, sample sizes in statistical analysis and channel bandwidths in communications.

System Identification with Quantized Observations

System Identification with Quantized Observations PDF Author:
Publisher:
ISBN:
Category : Quantum theory
Languages : en
Pages : 317

Book Description
This book presents recently developed methodologies that utilize quantized information in system identification and explores their potential in extending control capabilities for systems with limited sensor information or networked systems. The results of these methodologies can be applied to signal processing and control design of communication and computer networks, sensor networks, mobile agents, coordinated data fusion, remote sensing, telemedicine, and other fields in which noise-corrupted quantized data need to be processed. Providing a comprehensive coverage of quantized identification, the book treats linear and nonlinear systems, as well as time-invariant and time-varying systems. The authors examine independent and dependent noises, stochastic- and deterministic-bounded noises, and also noises with unknown distribution functions. The key methodologies combine empirical measures and information-theoretic approaches to derive identification algorithms, provide convergence and convergence speed, establish efficiency of estimation, and explore input design, threshold selection and adaptation, and complexity analysis. System Identification with Quantized Observations is an excellent resource for graduate students, systems theorists, control engineers, applied mathematicians, as well as practitioners who use identification algorithms in their work. Selected material from the book may be used in graduate-level courses on system identification.

System Identification with Quantized Observations

System Identification with Quantized Observations PDF Author: Le Yi Wang
Publisher:
ISBN:
Category : Quantum theory
Languages : en
Pages : 317

Book Description


System Identification Using Regular and Quantized Observations

System Identification Using Regular and Quantized Observations PDF Author: Springer
Publisher:
ISBN: 9781461462934
Category :
Languages : en
Pages : 108

Book Description


Advances in Systems Science

Advances in Systems Science PDF Author: Jerzy Swiątek
Publisher: Springer Science & Business Media
ISBN: 3319018574
Category : Technology & Engineering
Languages : en
Pages : 796

Book Description
The International Conference on Systems Science 2013 (ICSS 2013) was the 18th event of the series of international scientific conferences for researchers and practitioners in the fields of systems science and systems engineering. The conference took place in Wroclaw, Poland during September 10-12, 2013 and was organized by Wroclaw University of Technology and co-organized by: Committee of Automatics and Robotics of Polish Academy of Sciences, Committee of Computer Science of Polish Academy of Sciences and Polish Section of IEEE. The papers included in the proceedings cover the following topics: Control Theory, Databases and Data Mining, Image and Signal Processing, Machine Learning, Modeling and Simulation, Operational Research, Service Science, Time series and System Identification. The accepted and presented papers highlight new trends and challenges in systems science and systems engineering.

Advances in Neural Networks - ISNN 2017

Advances in Neural Networks - ISNN 2017 PDF Author: Fengyu Cong
Publisher: Springer
ISBN: 3319590723
Category : Computers
Languages : en
Pages : 601

Book Description
This book constitutes the refereed proceedings of the 14th International Symposium on Neural Networks, ISNN 2017, held in Sapporo, Hakodate, and Muroran, Hokkaido, Japan, in June 2017. The 135 revised full papers presented in this two-volume set were carefully reviewed and selected from 259 submissions. The papers cover topics like perception, emotion and development, action and motor control, attractor and associative memory, neurodynamics, complex systems, and chaos.

Errors-in-Variables Methods in System Identification

Errors-in-Variables Methods in System Identification PDF Author: Torsten Söderström
Publisher: Springer
ISBN: 3319750011
Category : Technology & Engineering
Languages : en
Pages : 495

Book Description
This book presents an overview of the different errors-in-variables (EIV) methods that can be used for system identification. Readers will explore the properties of an EIV problem. Such problems play an important role when the purpose is the determination of the physical laws that describe the process, rather than the prediction or control of its future behaviour. EIV problems typically occur when the purpose of the modelling is to get physical insight into a process. Identifiability of the model parameters for EIV problems is a non-trivial issue, and sufficient conditions for identifiability are given. The author covers various modelling aspects which, taken together, can find a solution, including the characterization of noise properties, extension to multivariable systems, and continuous-time models. The book finds solutions that are constituted of methods that are compatible with a set of noisy data, which traditional approaches to solutions, such as (total) least squares, do not find. A number of identification methods for the EIV problem are presented. Each method is accompanied with a detailed analysis based on statistical theory, and the relationship between the different methods is explained. A multitude of methods are covered, including: instrumental variables methods; methods based on bias-compensation; covariance matching methods; and prediction error and maximum-likelihood methods. The book shows how many of the methods can be applied in either the time or the frequency domain and provides special methods adapted to the case of periodic excitation. It concludes with a chapter specifically devoted to practical aspects and user perspectives that will facilitate the transfer of the theoretical material to application in real systems. Errors-in-Variables Methods in System Identification gives readers the possibility of recovering true system dynamics from noisy measurements, while solving over-determined systems of equations, making it suitable for statisticians and mathematicians alike. The book also acts as a reference for researchers and computer engineers because of its detailed exploration of EIV problems.

Criteria for System Identification with Quantized Data and the Optimal Quantization Schemes

Criteria for System Identification with Quantized Data and the Optimal Quantization Schemes PDF Author: Koji Tsumura
Publisher:
ISBN:
Category :
Languages : en
Pages : 14

Book Description


Analysis and Design of Networked Control Systems

Analysis and Design of Networked Control Systems PDF Author: Keyou You
Publisher: Springer
ISBN: 1447166159
Category : Technology & Engineering
Languages : en
Pages : 326

Book Description
This monograph focuses on characterizing the stability and performance consequences of inserting limited-capacity communication networks within a control loop. The text shows how integration of the ideas of control and estimation with those of communication and information theory can be used to provide important insights concerning several fundamental problems such as: · minimum data rate for stabilization of linear systems over noisy channels; · minimum network requirement for stabilization of linear systems over fading channels; and · stability of Kalman filtering with intermittent observations. A fundamental link is revealed between the topological entropy of linear dynamical systems and the capacities of communication channels. The design of a logarithmic quantizer for the stabilization of linear systems under various network environments is also extensively discussed and solutions to many problems of Kalman filtering with intermittent observations are demonstrated. Analysis and Design of Networked Control Systems will interest control theorists and engineers working with networked systems and may also be used as a resource for graduate students with backgrounds in applied mathematics, communications or control who are studying such systems.