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- Nonlinear_system_identification abstract "System identification is a method of identifying or measuring the mathematical model of a system from measurements of the system inputs and outputs. The applications of system identification include any system where the inputs and outputs can be measured and include industrial processes, control systems, economic data, biology and the life sciences, medicine, social systems and many more.A nonlinear system is defined as any system that is not linear, that is any system that does not satisfy the superposition principle. This negative definition tends to obscure the fact that there are very many different types of nonlinear systems. Historically, system identification for nonlinear systems has developed by focusing on specific classes of system and can be broadly categorised into four basic approaches, each defined by a model class, namely (i) Volterra series models, (ii) block structured models, (iii) neural network models, and (iv) NARMAX models.".
- Nonlinear_system_identification wikiPageID "40158142".
- Nonlinear_system_identification wikiPageRevisionID "605258654".
- Nonlinear_system_identification subject Category:Dynamical_systems.
- Nonlinear_system_identification subject Category:Nonlinear_systems.
- Nonlinear_system_identification comment "System identification is a method of identifying or measuring the mathematical model of a system from measurements of the system inputs and outputs.".
- Nonlinear_system_identification label "Nonlinear system identification".
- Nonlinear_system_identification sameAs m.0wy1y8q.
- Nonlinear_system_identification sameAs Q17080460.
- Nonlinear_system_identification sameAs Q17080460.
- Nonlinear_system_identification wasDerivedFrom Nonlinear_system_identification?oldid=605258654.
- Nonlinear_system_identification isPrimaryTopicOf Nonlinear_system_identification.