Response function estimation from multi-input systems
A novel formalism to estimate the vector linear impulse response functions from the experimental data observed from a multi-input system, allowing for correlation between the inputs, is developed. Time series statistical moments are estimated from the data and are used as the basis of a set of simultaneous equations in the unknown response functions. These simultaneous equations are solved using standard matrix methods for the unknown linear response functions. This approach is an extension to one proposed by \textit{G. E. P. Box} and \textit{G. M. Jenkins} [Time series analysis: Forecasting and control. (1976; Zbl 0363.62069)]\ from the Yule-Walker equations. The ability of the technique to correctly estimate the response functions of a multi-input linear system to a high degree of accuracy is demonstrated, using a numerical example where the properties of the system are known and there is strong correlation between the input data. This novel technique is then used to estimate the response functions of the coupled convective and radiative processes, that act at the internal surface of the ceiling of an experimental building.
vector linear impulse response functions
scientific article; zbMATH DE number 772252