Jet engines need to be certified before going into service, i. e., any dangerous vibration has to be detected. Therefore the eigenmodes, displayed as curves in Campbell diagrams, need to be identified first. At the moment this is done manually by engineers. In this paper we introduce a way of automatically detecting eigenmodes in Campbell diagrams by introducing an extension of Hough transform.

Quantile regression techniques have been widely used in empirical economics. In this paper, we consider the estimation of a generalized quantile regression model when data are subject to fixed or random censoring. Through a discretization technique, we transform the censored regression model into a sequence of binary choice models and further propose an integrated smoothed maximum score estimat...

We consider cubic boolean bent functions, each cubic monomial of which contains the same variable. We investigate canonical forms of these functions under affine transformations of variables. In particular, we refine the affine classification of cubic bent functions of 8 variables. 1 Preliminaries Let Vn be an n-dimensional vector space over the field F2, and Fn be the set of all boolean functi...

Abstract: In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship-radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship-radiated noise signa...

Segmentation of medical images is an important component for diagnosis and treatment of diseases using medical imaging technologies. However, automated accurate medical image segmentation is still a challenge due to the difficulties in finding a robust feature descriptor to describe the object boundaries in medical images. In this paper, a new normal vector feature profile (NVFP) is proposed to...

The identification and representation of uncertainty is recognized as an essential component in model applications. One important approach in the identification of uncertainty is sensitivity analysis. Sensitivity analysis evaluates how the variations in the model output can be apportioned to variations in model parameters. One of the most popular sensitivity analysis techniques is Fourier ampli...

We consider the problem of generating hard instances for the Satisfying Assignment Search Problem (in short, SAT). It is not known whether SAT is di cult on average, while it has been believed that the Factorization Problem (in short, FACT) is hard on average. Thus, one can expect to generate hard-on-average instances by using a reduction from FACT to SAT. Although the asymptotically best reduc...

This paper investigates the contribution of features which convey long-term spectro-temporal (ST) information for the purpose of automatic emotional speech classification. The ST representation is obtained by means of a modulation filterbank decomposition of long-term temporal envelopes of the outputs of a gammatone filterbank. The two-dimensional discrete cosine transform is used to reduce the...

The paper introduces a new objective method for speech quality assessment called Fourier-lappedmultilayer perceptron (FLMLP). This method uses an overcomplete transform based on the discrete Fourier transform (DFT) and modulated lapped transform (MLT). This transform generates the DFT and theMLT speech spectral domains fromwhich several relevant perceptual parameters are extracted. The proposed...