Сибирский федеральный университет

Тип публикации: доклад, тезисы доклада, статья из сборника материалов конференций

Конференция: II International Scientific Conference "Advanced Technologies in Aerospace, Mechanical and Automation Engineering"; Krasnoyarsk; Krasnoyarsk

Год издания: 2020

Идентификатор DOI: 10.1088/1757-899X/734/1/012143

Аннотация: Dynamical models are of fundamental importance in many problems such as simulation, optimization and prediction. In identification problem of dynamical systems an input vector is typically considered as delayed vector of previous outputs. Embedding lag and embedding dimension should be chosen correctly. Identification of nonlinear systems is generally performed using kernel-based methods since they do not require any additional information about system structure. A common question in identification of dynamical system is sensitivity of kernel-based models to selected embedding lag and embedding dimension. The paper presents simulations of the kernel least mean squares algorithm on one-step prediction problem for various values of embedding lag and embedding dimension. It is shown that optimal embedding lag and embedding dimension is dependent on model parameters, while usage of optimal model parameters decreases the value of optimal embedding dimension.

Журнал: IOP Conference Series: Materials Science and Engineering

Выпуск журнала: 734

Номера страниц: 12143

Издатель: Institute of Physics and IOP Publishing Limited

• Antropov N.R. (Reshetnev Siberian State University of Science and Technology)
• Agafonov E.D. (Reshetnev Siberian State University of Science and Technology)

• Ядро РИНЦ (eLIBRARY.RU)