In this paper a novel technique for rotation independent template matching via Quadtree Zernike decomposition is presented. Both the template and the target image are decomposed by using a complex polynomial basis. The template is analyzed in block-based manner by using a quad tree decomposition. This allows the system to better identify the object features. Searching for a complex pattern into...

A simple way to calculate the number of k-matchings, k ~< 5, in hexagonal systems is presented. Some relations between the coefficients of the characteristic polynomial of the adjacency matrix of a hexagonal system and the number of matchings are obtained. (~) 1998 Elsevier Science B.V. All rights reserved

We prove that the minimum value of the least eigenvalue of the signless Laplacian of a connected nonbipartite graph with a prescribed number of vertices is attained solely in the unicyclic graph obtained from a triangle by attaching a path at one of its endvertices. © 2008 Elsevier Inc. All rights reserved. AMS classification: 05C50

Using Lotker’s interlacing theorem on the Laplacian eigenvalues of a graph in [5] and Wang and Belardo’s interlacing theorem on the signless Laplacian eigenvalues of a graph in [6], we in this note obtain spectral conditions for some Hamiltonian properties of graphs. 2010Mathematics Subject Classification : 05C50, 05C45

In this paper we observe that the minimal signless Laplacian spectral radius is obtained uniquely at the kite graph PKn−ω,ω among all connected graphs with n vertices and clique number ω. In addition, we show that the spectral radius μ of PKm,ω (m ≥ 1) satisfies

LetB(n, r) be the set of all bicyclic graphs with n vertices and r cut edges. In this paper we determine the unique graph with maximal adjacency spectral radius or signless Laplacian spectral radius among all graphs in B(n, r).

A linear programming (LP) approach is proposed for the weighted graph matching problem. A linear program is obtained by formulating the graph matching problem in L1 norm and then transforming the resulting quadratic optimization problem to a linear one. The linear program is solved using a Simplex-based algorithm. Then, approximate 0-1 integer solutions are obtained by applying the Hungarian me...

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We introduce a general class of learning algorithms, regret-matching algorithms, and a regret-based framework for analyzing their performance in online decision problems. Our analytic framework is based on a set Φ of transformations over the set of actions. Specifically, we calculate a Φ-regret vector by comparing the average reward obtained by an agent over some finite sequence of rounds to th...