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Book ChapterDOI

Linear System Theory

Roy M. Howard
- pp 229-255
TLDR
Chapter 8 establishes the relationship between the input and output power spectral densities of a linear system and the theory is extended to multiple input-multiple output systems.
Abstract
Chapter 8 establishes the relationship between the input and output power spectral densities of a linear system. Limitations on results are carefully detailed and the case of oscillator noise is considered. The theory is extended to multiple input-multiple output systems.

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Citations
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References
More filters
Book

Feedback Systems: An Introduction for Scientists and Engineers

TL;DR: Feedback Systems develops transfer functions through the exponential response of a system, and is accessible across a range of disciplines that utilize feedback in physical, biological, information, and economic systems.
Journal ArticleDOI

Perspectives and results on the stability and stabilizability of hybrid systems

TL;DR: In this paper, the authors introduce the concept of hybrid systems and some of the challenges associated with the stability of such systems, including the issues of guaranteeing stability of switched stable systems and finding conditions for the existence of switched controllers for stabilizing switched unstable systems.
Book

Predictive Control for Linear and Hybrid Systems

TL;DR: Predictive Control for Linear and Hybrid Systems is an ideal reference for graduate, postgraduate and advanced control practitioners interested in theory and/or implementation aspects of predictive control.
Journal ArticleDOI

Stability Criteria for Switched and Hybrid Systems

TL;DR: This paper considers the stability of switched systems in which there are constraints on the switching rules, through both dwell-time requirements and state-dependent switching laws, and discusses the theory of Lyapunov functions and the existence of converse theorems.
Proceedings Article

Marginalized kernels between labeled graphs

TL;DR: A new kernel function between two labeled graphs that is based on an infinite dimensional feature space, so it is fundamentally different from other string or tree kernels based on dynamic programming and presents promising empirical results in classification of chemical compounds.
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