An auxiliary signal is an input signal that enhances the identifiability of a model based on input-output observations. Assuming that the normal and the failed behaviors of a process can be modeled by two linear uncertain systems, failure detectability can be seen as a multi-model identification problem. In this paper, we extend previous results on auxiliary signal design for multi-model identi...

In this paper, we first examine several criteria for system identification with quantized output data and show that the ordinary parameter estimator for quantization-free case is still reasonable according to those criteria. Then, we give the optimal quantization schemes for minimizing the estimation errors under a constraint on the number of the quantized subsections of the output signals or t...

This work explores a new robust approach for Semantic Parsing of unrestricted texts. Our approach considers Semantic Parsing as a Consistent Labelling Problem (clp), allowing the integration of several knowledge types (syntactic and semantic) obtained from different sources (linguistic and statistic). The current implementation obtains 95% accuracy in model identification and 72% in case-role f...

Writer identification is an important issue in forensic investigations. In this paper, we propose a novel method for identifying a writer by means of features of loops and lead-in strokes of produced letters. Using a k-nearestneighbor classifier, we were able to yield a correct identification performance of 98% on a database of 41 writers. These results are promising and have great potential fo...

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Due to the fact that the error surface of adaptive infinite impulse response (IIR) systems is generally nonlinear and multimodal, the conventional derivative based techniques fail when used in adaptive identification of such systems. In this case, global optimization techniques are required in order to avoid the local minima. Harmony search (HS), a musical inspired metaheuristic, is a recently ...

The nonlinear system becomes an area with numerous investigations over the past decades. The conventional modal analysis could not be  applied on nonlinear continuous system which makes it impossible to construct the reduced order models and obtain system response based on limited number of measurement points. Nonlinear normal modes provide a useful tool for extending modal analysis to nonlinea...

In mobile robotics, it is common to find different control programs designed to achieve a particular robot task. It is often necessary to compare the performance of such controllers. So far this is usually done qualitatively, because of a lack of quantitative behaviour analysis methods. In this paper we present a novel approach to compare robot control codes quantitatively, based on system iden...

Time-delay identification is one of the most important parameters in designing controllers. In the cases where the number of inputs and outputs in a system are more than one, this identification is of great concern. In this paper, a novel autocorrelation-based scheme for the state variable time-delay identification for multi-input multi-output (MIMO) system has been presented. This method is ba...

Many different discrete-time recurrent neural network architectures have been proposed. However, there has been virtually no effort to compare these arch:tectures experimentally. In this paper we review and categorize many of these architectures and compare how they perform on various classes of simple problems including grammatical inference and nonlinear system identification.