System Identification Using Regular and Quantized Observations
Applications of Large Deviations Principles
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Chapter
Impact of Communication Channels on System Identification
This chapter deals with the identification of systems whose outputs must be quantized, transmitted through a communication channel, and observed afterwards. Communication errors introduce additional uncertaint...
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Chapter
Worst-Case Identification under Binary-Valued Observations
This chapter focuses on the identification of systems where the disturbances are formulated in a deterministic framework as unknown but bounded. Different from the previous chapters, here the identification er...
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Chapter
Empirical-Measure-Based Identification: Binary-Valued Observations
This chapter presents a stochastic framework for systems identification based on empirical measures that are derived from binary-valued observations. This scenario serves as a fundamental building block for su...
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Chapter
Systems with Markovian Parameters
This chapter concerns the identification of systems with time-varying parameters. The parameters are vector-valued and take values in a finite set. As in the previous chapters, only binary-valued observations ...
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Article
Molecular epidemiology of norovirus gastroenteritis in children in Jiangmen, China, 2005–2007
Human noroviruses (NoVs) are an important cause of epidemic acute gastroenteritis. Their role in sporadic cases, however, is less clear. In this study, we performed a two-year surveillance (September 2005 to A...
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Article
Convergence and error bounds of adaptive filtering under model structure and regressor uncertainties
Adaptive filtering algorithms are investigated when system models are subject to model structure errors and regressor signal perturbations. System models for practical applications are often approximations of ...
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Book
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Book
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Chapter
Introduction and Overview
Traditional system identification taking noise measurement into consideration concentrates on convergence in suitable senses (such as in mean square, in distribution, or with probability one) and rates of conv...
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Chapter
Large Deviations: An Introduction
The theory of large deviations characterizes probabilities and moments of certain sequences that are associated with “rare” events. In a typical application, consider the sum of N independent and identically dist...
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Chapter
LDP of System Identification under Mixing Observation Noises
Up to this point, the observation noises are assumed to be uncorrelated. In this chapter, we demonstrate that a much larger class of noise processes can be treated.
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Chapter
Remarks and Conclusion
For clarity, this book assumes that the input is designed to be periodic. Advantages of using full rank and periodic inputs in quantized identification problems have been extensively discussed in [62]. Note th...
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Chapter
System Identification: Formulation
Consider a single-input–single-output (SISO) linear time-invariant (LTI) stable discrete-time system
2.1 $$y(t) =\displaystyle\sum\limi... -
Chapter
Applications to Battery Diagnosis
This chapter uses a battery diagnosis problem to illustrate the use of the LDP in industrial applications. Management of battery systems plays a pivotal role in electric and hybrid vehicles, and in support of ...
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Chapter
Applications to Electric Machines
Electric machines are essential systems in electric vehicles and are widely used in other applications. In particular, permanent magnet direct current (PMDC) motors have been extensively employed in industrial...
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Chapter
Electric Vehicle Battery Technologies
This chapter aims at bridging the gap between chemistry scientists and electrical engineers on electric vehicle (EV) batteries. The power and energy of electric propulsion are first reviewed in Sect. 2.2. Comm...
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Chapter
Weighted and Constrained Consensus Control with Performance Optimization for Robust Distributed UAV Deployments with Dynamic Information Networks
A team of unmanned aerial vehicles (UAVs) in surveillance operations aims to achieve fast deployments, robustness against uncertainties and adversaries, and adaptability when the team expands or reduces. All t...
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Chapter
Applications to Medical Signal Processing
Heart and lung sounds are of essential importance in medical diagnosis of patients with lung or heart diseases. To obtain reliable diagnosis and detection, it is critically important that cardiac and respirato...
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Chapter
LDP of System Identification under Independent and Identically Distributed Observation Noises
We first consider system identification under i.i.d. noise. Extension to correlated noises will be treated in Chapter 5. Beginning with the following assumptions, we should emphasize here that since we conside...
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Article
Asymptotic optimality for consensus-type stochastic approximation algorithms using iterate averaging
This paper introduces a post-iteration averaging algorithm to achieve asymptotic optimality in convergence rates of stochastic approximation algorithms for consensus control with structural constraints. The al...
