A partially ordered (generalized) pattern (POP) is a generalized pattern some of whose letters are incomparable, an extension of generalized permutation patterns introduced by Babson and Steingŕımsson. POPs were introduced in the symmetric group by Kitaev [19, 21], and studied in the set of k-ary words by Kitaev and Mansour [22]. Moreover, Kitaev et al. [23] introduced segmented POPs in composi...

In this short communication we describe some experiments in which methods of statistical pattern recognition are applied for musical style recognition and disputed musical authorship attribution. Values of a set of 20 features (also called ‘‘style markers’’) are measured in the scores of a set of compositions, mainly describing the different sonorities in the compositions. For a first study ove...

A partially ordered (generalized) pattern (POP) is a generalized pattern some of whose letters are incomparable, an extension of generalized permutation patterns introduced by Babson and Steingŕımsson. POPs were introduced in the symmetric group by Kitaev [19, 21], and studied in the set of k-ary words by Kitaev and Mansour [22]. Moreover, Kitaev et al. [23] introduced segmented POPs in composi...

In this paper, a fast and accurate algorithm is proposed to recognize open and closed eye states. In the proposed algorithm, first a hierarchical preprocessing stage is used to detect eye areas. This stage employs Haar features to detect face area, color, and intensity mappings to extract eye candidate areas, and some simple geometrical relations for a final decision of the eye regions. In the ...

We study the effects of adding a local perturbation in a pattern forming system, taking as an example the Ginzburg-Landau equation with a small localized inhomogeneity in two dimensions. Measuring the response through the linearization at a periodic pattern, one finds an unbounded linear operator that is not Fredholm due to continuous spectrum in typical translation invariant or weighted spaces...

Abstract: Previous analyses of pattern search algorithms for unconstrained and linearly constrained minimization have focused on proving convergence of a subsequence of iterates to a limit point satisfying either directional or first-order necessary conditions for optimality, depending on the smoothness of the objective function in a neighborhood of the limit point. Even though pattern search m...