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Balanced truncation for model reduction of biological oscillators. [PDF]
Biol Cybern, 2021 AbstractModel reduction is a central problem in mathematical biology. Reduced order models enable modeling of a biological system at different levels of complexity and the quantitative analysis of its properties, like sensitivity to parameter variations and resilience to exogenous perturbations.
Padoan A, Forni F, Sepulchre R.
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Efficient numerical algorithms for balanced stochastic truncation [PDF]
, 2001 We propose an efficient numerical algorithm for relative error model reduction based on balanced stochastic truncation. The method uses full-rank factors of the Gramians to be balanced versus each other and exploits the fact that for large-scale systems ...
Peter Benner +2 more
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Time-limited Balanced Truncation for Data Assimilation Problems [PDF]
Journal of Scientific Computing, 2022 AbstractBalanced truncation is a well-established model order reduction method which has been applied to a variety of problems. Recently, a connection between linear Gaussian Bayesian inference problems and the system-theoretic concept of balanced truncation has been drawn (Qian et al in Sci Comput 91:29, 2022).
Josie König, Melina A. Freitag
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Empirical balanced truncation of nonlinear systems [PDF]
Journal of Nonlinear Science, 2006 Novel constructions of empirical controllability and observability gramians for nonlinear systems for subsequent use in a balanced truncation style of model reduction are proposed.
Condon, Marissa, Ivanov, Rossen I.
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Balanced Truncation of Networked Linear Passive Systems [PDF]
Automatica, 2019 This paper studies model order reduction of multi-agent systems consisting of identical linear passive subsystems, where the interconnection topology is characterized by an undirected weighted graph.
Besselink, Bart +2 more
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Model Compression Method for S4 With Diagonal State Space Layers Using Balanced Truncation [PDF]
IEEE AccessTo implement deep learning models on edge devices, model compression methods have been widely recognized as useful. However, it remains unclear which model compression methods are effective for Structured State Space Sequence (S4) models incorporating ...
Haruka Ezoe, Kazuhiro Sato
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Frequency interval balanced truncation of discrete-time bilinear systems
Cogent Engineering, 2016 This paper presents the development of a new model reduction method for discrete-time bilinear systems based on the balanced truncation framework. In many model reduction applications, it is advantageous to analyze the characteristics of the system with ...
Ahmad Jazlan +3 more
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Balanced truncation for linear switched systems [PDF]
Nonlinear Analysis: Hybrid Systems, 2013 In this paper, we present a theoretical analysis of the model reduction algorithm for linear switched systems. This algorithm is a reminiscence of the balanced truncation method for linear parameter varying systems. Specifically in this paper, we provide
Boyd +21 more
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Mixed Riccati–Lyapunov Balanced Truncation for Order Reduction of Electrical Circuit Systems [PDF]
EnergiesThis paper proposes a novel algorithm, termed Mixed Riccati–Lyapunov Balanced Truncation (MRLBT), tailored for order reduction of Linear Time-Invariant Continuous-Time Descriptor Systems (LTI-CTD), commonly encountered in electrical and electronic ...
Huy-Du Dao +4 more
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A Balanced Truncation Primer [PDF]
, 2001 Balanced truncation, a technique from robust control theory, is a systematic method for producing simple approximate models of complex linear systems. This technique may have significant applications in physics, particularly in the study of large classical and quantum systems.
Benjamin Rahn
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