Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains
Abstract
Nonlinear System Identification: NARMAX Methods in the Time, Frequency, and Spatio-Temporal Domains describes a comprehensive framework for the identification and analysis of nonlinear dynamic systems in the time, frequency, and spatio-temporal domains. This book is written with an emphasis on making the algorithms accessible so that they can be applied and used in practice. Includes coverage of: The NARMAX (nonlinear autoregressive moving average with exogenous inputs) modelThe orthogonal least squares algorithm that allows models to be built term by
Citation impact
660
total citations
- FWCI
- 25.74
- Percentile
- 100%
- References
- 13
Citations per year
Authors
1Topics & keywords
Topics
Keywords
- Nonlinear system
- Identification (biology)
- Computer science
- Time–frequency analysis
- Physics
- Computer vision
No related works found for this paper.