The aim of this paper is to identify the nominal model and associated uncertainty bound of a lightly damped flexible beam in order to be utilized in robust controller design methods. Our approach is based on Set Membership theory where the system’s uncertainties assumed to be unknown but bounded (UBB). Both parametric and non-parametric uncertainties have been accounted in the robust identifica...

Identification based PID tuning is studied. The proposed approach consists of the identification of linear or nonlinear process model and model based control design. The identification test can be performed in both open loop and closed-loop. The so-called ASYM method is used to solve the identification problem. The method identifies a low order process model with a quantification of model error...

Along with investigating similarity metrics between audio material, the topic of robust matching of pairs of audio content has gained wide interest recently. In particular, if this matching process is carried out using a compact representation of the audio content ("audio fingerprint"), it is possible to identify unknown audio material by means of matching it to a database with the fingerprints...

In this paper, estimation and identification theories will be examined with the goal of determining some new methods of adding robustness. The focus will be upon uncertain estimation problems, namely ones in which the uncertainty multiplies the quantities to be estimated. Mathematically the problem can be stated as, for system matrices and data matrices that lie in the sets (A + δA) and (b + δb...

This paper investigates the problem of speaker identification in noisy conditions, assuming that there is no prior knowledge about the noise. To confine the effect of the noise on recognition, we use a multi-stream approach to characterize the speech signal, assuming that while all of the feature streams may be affected by the noise, there may be some streams that are less severely affected and...

The paper describes a rule-based system for tagging clause boundaries, implemented for annotating the Estonian Reference Corpus of the University of Tartu, a collection of written texts containing ca 245 million running words and available for querying via Keeleveeb language portal. The system needs information about parts of speech and grammatical categories coded in the word-forms, i.e. it ta...

Mobile augmented reality applications have received considerable interest in recent years, as camera equipped mobile phones become ubiquitous. We have developed a “Point and Find” application on a cell phone, where a user can point his cell phone at a building on the Stanford campus, and get relevant information of the building on his phone. The problem of recognizing buildings under different ...

Current state-of-the-art speaker identification (SID) systems perform exceptionally well under clean conditions, but their performance deteriorates when noise and channel degradations are introduced. Literature has mostly focused on robust modeling techniques to combat degradations due to background noise and/or channel effects, and have demonstrated significant improvement in SID performance i...

This paper addresses robust deconvolution filtering when the system and noise dynamics are obtained by parametric system identification. Consistent with standard identificationmethods, the uncertainty in the estimated parameters is represented by an ellipsoidal uncertainty region. Three problems are considered: (1) computation of the worst case H2 performance of a given deconvolution filter in ...

Identification of low-quality scanned documents is not trivial in real-world settings. Existing research mainly focusing on similarity-based approaches rely on perfect string data from a document. Also, studies using image processing techniques for document identification rely on clean data and large differences among templates. Both these approaches fail to maintain accuracy in the context of ...