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The paper discusses applicability of CARMA, CARIMA and Box-Jenkins models for identification of systems of different structure. Especially, the difficulties encountered by unstable plant modes are considered. It is shown that the behaviour of identification algorithms may depend on location of the noise in the real system. Therefore it may be advisable to use different models for identification purposes...
A polynomial time algorithm for converting time domain input-output data into worst case frequency domain set membership information with arbitrary precision is presented. Experimental data is assumed to be noise corrupted time domain input-output measurements for a single-input single-output linear shift invariant discrete time system. This method uses prior knowledge of bounds on both the output...
This paper presents a robust scheme for the indirect type of model reference adaptive control (MRAC) system, in the presence of unmodelled dynamics and measurement noise. This scheme is characterized by the use of adaptive law with dead zone and integral type of fixed compensator. Stability of the MRAC system is analyzed by employing the concept of L2δ norm and the Bellman-Gronwall lemma, based on...
This paper proposes Variable Step-Size Least Mean Modulus Algorithm (VSS-LMMA) for robust filtering in impulsive noise environments. The VSS-LMMA for use in adaptive filters in digital QAM systems is basically the LMMA combined with a new simple variable step-size control algorithm to improve the convergence speed of the LMMA while preserving its robustness against additive impulsive observation noise...
Voiced sounds are the result of a periodic excitation of the vocal tract due to the vocal folds vibration. They are characterised by the fundamental frequency of the phonation, named pitch, which is the rate of vibration of the folds. In pathologic voices, pitch variations are indicative of the patient status, hence robust pitch estimation methods are required in order to track such variations and...
In this paper, we propose an adaptive scheme to design directional second order derivatives orthogonally and tangentially to the local edge. The principle lies on the definition of two adaptive filter masks which estimate the two derivatives along the normal (n) and tangential (t) directions. Both filter masks are controlled by an adaptive mask whose coefficients are tuned in accordance with the local...
The least-squares and the subspace methods are well known approaches for blind channel identification/equalization. When the order of the channel is known, the algorithms are able to identify the channel, under the so-called length and zero conditions. Furthermore, in the noiseless case, the channel can be perfectly equalized. Less is known about the performance of these algorithms in the cases in...
In this paper, we present several new robust isolated word speech recognition systems which employ FMQ/MQ as the spectral labelling process, followed by a Hidden Markov Model (HMM), or a HMM and Neural Network (HMM/MLP) classification technique. The ISWR systems provide selective input data to a neural network in response to speech signal to acoustic noise ratios to improve speech recognition system...
The performances of adaptive array algorithms are known to degrade in scenarios with moving interfering sources. Recently, several robust approaches have been proposed to overcome this problem. Below, we compare conventional and robust algorithms using shallow sea sonar data with moving co-channel interference originated from shipping noise. This data set was recorded by a towed horizontal Uniform...
Differentiation of a signal is required in many applications in the field of signal processing. Linear differentiators fail to give good results for signals corrupted by both Gaussian and impulsive type of noise. For such cases nonlinear methods can be used in order to obtain better results. In this paper we propose a method, which we call randomized regression differentiator, based on random sampling...
This papers deals with supervised texture classification. The extracted features are the image second and third order moments. The number of possible moment lags for 2-D signals increases rapidly with the order of the moment even for small lag neighbourhoods. The paper focuses on the selection of moment lags that optimise classification performance. Lag selection also serves another purpose: it waives...
This work deals with the problem of linear polyphase blind equalization (BE), i. e. we are interested in equalizing the output of a single-input-multiple-output (SIMO) channel, without observing its input. A recent result by Liu and Dong [1] showed that if the sub-channel polynomials are co-prime, the equalizer output whiteness suffices for the equalization of a white input. Based on this observation,...
A novel approach to estimation of the Interaural Time Difference (ITD) from the measured Head Related Impulse Responses (HRIR) is proposed in the paper. An innovative application of the cross-correlation function that is estimated for impulse responses corresponding to adjacent sound arrival directions makes the presented method robust and immune to inherent noise components occuring in the measured...
The problem of estimating the state of discrete-time linear systems when uncertainties affect the system matrices is addressed. A quadratic cost function is considered, involving a finite number of recent measurements and a prediction vector. This leads to state the estimation problem in the form of a regularized least-squares one with uncertain data. The optimal solution (involving on-line scalar...
It is shown how noisy closed-loop frequency response measurements may be used to obtain pointwise in frequency bounds on the possible difference between an unknown closed-loop system and a nominal model of the closed-loop. To this end, the ν-gap metric framework for robustness analysis plays a central role.
The problem of model-based fault detection in the presence of both parametric uncertainty and noise is addressed in this paper. Intervals are used to represent the uncertainty in the system parameters and interval extensions of parity equations are used as adaptive threshold selectors. A proper combination in time of different (interval) parity equations, together with a robust indicator, is used...
This paper presents a methodology for enhancing the robustness of a GPC controlled system by convex optimisation of the Youla parameter. This methodology requires, as a first step, the design of an initial GPC controller; this controller is then robustified considering frequency and temporal constraints. By means of the Youla parametrisation, frequency and temporal constraints are formulated within...
This paper presents two new methods for robust parameter estimation of mixtures in the context of MR data segmentation. The head is constituted of different types of tissue that can be modeled by a finite mixture of multivariate Gaussian distributions. Our goal is to estimate accurately the statistics of desired tissues in presence of other ones of lesser interest. These latter can be considered as...
This contribution deals with the role and the performance of echocompensation and noise suppression, when used in combination with speech recognition systems. For two applications of interest (speech control in car or via telephone) there are quite significant differences to classical echocompensation and noise suppression for telephone conferences. It will be pointed out, how the systems are structured,...
Motion estimation is a very important topic in computer vision and image sequence compression. However, most commonly used motion estimation algorithms do not take into consideration any motion invariances that a certain local motion might possess. In this paper, a technique for estimating the invariant motion parameters of non-translational motion fields is proposed, which leads to more efficient...
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