Powerful tools lead to new principles and algorithms for various linear and nonlinear system identification techniques Careful mathematics provide a rigorous basis for cross-fertilization between system identification and machine learning Develops system identification principles in both deterministic and stochastic (Bayesian) settings This book is open access, which means that you have free and unlimited access.
Regularized System Identification
Gianluigi Pillonetto;Alessandro Chiuso;
2022
Abstract
Powerful tools lead to new principles and algorithms for various linear and nonlinear system identification techniques Careful mathematics provide a rigorous basis for cross-fertilization between system identification and machine learning Develops system identification principles in both deterministic and stochastic (Bayesian) settings This book is open access, which means that you have free and unlimited access.
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