We have derived computationally simple and intuitive expressions for score tests of neglected serial correlation in unobserved component univariate models using frequency domain methods.
We derive computationally simple and intuitive score tests of neglected serial correlation in unobserved component univariate models using frequency domain techniques.
More recently, in a companion paper (Fiorentini and Sentana 2013) we have derived tests for neglected serial correlation in the latent variables of dynamic factor models using frequency domain techniques.
The reverberation is absorbed by using frequency-domain processing.
Both DBN model using time-domain signals and FFT-DBN model using frequency distribution of the signals are investigated, and the comparison results are provided and discussed.
They use frequency-domain filtering technique to remove sensor noise.
Linear black box models are identified using frequency domain identification techniques, while robust linear control design techniques (H∞ and μ-synthesis) account for the model uncertainties introduced by the linear model approximation of the nonlinear dynamics.
This paper presents a charge control strategy using frequency domain models and room air temperature set-point profile as input.
The models used in the design work have been obtained using frequency domain tests conducted on the physical plants.
Soil moisture was recorded using frequency domain reflectometry sensors.
