Abstract—In this paper, we study the consistency of a frequency-domain, errors-in-variables estimator using data ex-tracted from overlapping subrecords. While the classical approach without overlap needs six consecutive periods, we show in this paper that by using overlapping subrecords, consistent models can be found with only two periods of the steady-state response of a periodic excitation. Moreover, the system identification procedure used for data extracted from independent experiments is shown to be valid for data extracted from overlapping subrecords. This allows the user to considerably reduce the measurement time or the measurement uncertainty without changing the identification procedure. Index Terms—Consistency, efficiency loss, ...
The use of block overlapping and time windowing in the estimation of frequency response functions of...
none2siThis paper deals with the identification of errors-in-variables (EIV) models corrupted by add...
This paper treats identification of continuous-time output error (OE) models based on sampled data. ...
All in-text references underlined in blue are linked to publications on ResearchGate, letting you ac...
The use of periodic excitation signals in identification experiments is advocated. With periodic exc...
Identification of dynamic errors-in-variables systems, where both inputs and outputs are affected by...
Abstract: Using instrumental variable methods to estimate the parameters of dynamic errors-in-variab...
Statistical errors in frequency response estimates depend on the form of the time window used to def...
The usefulness of frequency domain interpretations in linear systems is well known. In this contribu...
In this paper, we study instrumental variable subspace identification of multi-input/multi-output li...
\u97Identication of time-invariant linear dynamic systems is a mature subject. In this contribution ...
none2siThe paper proposes a new frequency domain method for identifying linear dynamic errors-in-var...
Errors-in-variables models are statistical models in which not only dependent but also independent v...
In this paper we develop a novel identification algorithm for Errors-in-Variables systems (represent...
Approaching parameter estimation from the discrete-time domain is the dominating paradigm in system ...
The use of block overlapping and time windowing in the estimation of frequency response functions of...
none2siThis paper deals with the identification of errors-in-variables (EIV) models corrupted by add...
This paper treats identification of continuous-time output error (OE) models based on sampled data. ...
All in-text references underlined in blue are linked to publications on ResearchGate, letting you ac...
The use of periodic excitation signals in identification experiments is advocated. With periodic exc...
Identification of dynamic errors-in-variables systems, where both inputs and outputs are affected by...
Abstract: Using instrumental variable methods to estimate the parameters of dynamic errors-in-variab...
Statistical errors in frequency response estimates depend on the form of the time window used to def...
The usefulness of frequency domain interpretations in linear systems is well known. In this contribu...
In this paper, we study instrumental variable subspace identification of multi-input/multi-output li...
\u97Identication of time-invariant linear dynamic systems is a mature subject. In this contribution ...
none2siThe paper proposes a new frequency domain method for identifying linear dynamic errors-in-var...
Errors-in-variables models are statistical models in which not only dependent but also independent v...
In this paper we develop a novel identification algorithm for Errors-in-Variables systems (represent...
Approaching parameter estimation from the discrete-time domain is the dominating paradigm in system ...
The use of block overlapping and time windowing in the estimation of frequency response functions of...
none2siThis paper deals with the identification of errors-in-variables (EIV) models corrupted by add...
This paper treats identification of continuous-time output error (OE) models based on sampled data. ...