每年出版 12 期
ISSN 打印: 1064-2315
ISSN 在线: 2163-9337
Indexed in
Nonstochastic Approach to Determining the Dimension and Parameters of Linear Autoregressive Models by the Input and Output Variables Measurements
摘要
The problem of identifying the dimension and parameters of the autoregressive model of a linear dynamical system with one input and one output by the measured temporal sequences of inputs and outputs is considered. Measuring errors are thought to be bounded. It is shown that the controllability of a dynamical system is a necessary and sufficient condition of determining the dimension and parameters of the system in the absence of errors. In general, the exact solution of the problem can be obtained if the noise reaches its limiting values.
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Gubarev V. F., Salnikov N. N., Melnychuk S. V., Identification of Regularized Models in the Linear Regression Class, Cybernetics and Systems Analysis, 57, 4, 2021. Crossref