similarities of the integral pade approximants ii in this paper we show further similarities of the integral pade approximant the similarity of the integral pade approximant with the functional pade approximant and the improved functional epsilon algorithms is demonstrated the purpose of demonstrating the similarity between the integral pade approximant and the functional pade approximant is to verify our conjecture which is the integral pade approximant and the hybrid functional pade approximant produce identical rational functions finally we demonstrate the improvement of the classical functional epsilon algorithms which also has a relationship with the integral pade approximant

detecting singular patterns in 2d vector fields using weighted laurent polynomial in this paper we propose a method for detecting patterns of interest in vector fields our method detects patterns in a scale and rotation invariant manner it works by approximating the vector field data locally using a laurent polynomial weighted by radial basis functions the proposed representation is able to model both analytic and non analytic flow fields invariance to scale and rotation is achieved by combining the linearity properties of the model coefficients and a scale space parameter of the radial basis functions promising detection results are obtained on a variety of fluid flow sequences

on the convergence of rows of vector pade approximants we state and prove a de montessus like theorem for vector valued meromorphic functions using vector pade approximants which are defined in the context of clifford algebras the proof is based on that used by saff for the scalar case the theorem may be regarded as an answer to a general problem posed by graves morris and saff

local well posedness for the maxwell schrodinger equation time local well posedness for the maxwell schrodinger equation in the coulomb gauge is studied in sobolev spaces by the contraction mapping principle the lorentz gauge and the temporal gauge cases are also treated by the gauge transform

convex graph invariant relaxations for graph edit distance the edit distance between two graphs is a widely used measure of similarity that evaluates the smallest number of vertex and edge deletions insertions required to transform one graph to another it is np hard to compute in general and a large number of heuristics have been proposed for approximating this quantity with few exceptions these methods generally provide upper bounds on the edit distance between two graphs in this paper we propose a new family of computationally tractable convex relaxations for obtaining lower bounds on graph edit distance these relaxations can be tailored to the structural properties of the particular graphs via convex graph invariants specific examples that we highlight in this paper include constraints on the graph spectrum as well as tractable approximations of the stability number and the maximum cut values of graphs we prove under suitable conditions that our relaxations are tight i e exactly compute the graph edit distance when one of the graphs consists of few eigenvalues we also validate the utility of our framework on synthetic problems as well as real applications involving molecular structure comparison problems in chemistry

definition and extraction of stable points from fingerprint images this paper introduces a new idea to define and extract singular points sps including cores and deltas from fingerprint images by a zone could be in theorem that describes harmonic relationships of a sp and its neighbors according to the theorem we can view sps as stable points attractors and rejectors by their rotations estimate core s direction and restore sp offset the proposed method is validated in the following two hierarchical aspects one is to test the reliability and accuracy of coarse sp detection by means of two indices ri and ac and the other is the accuracy of core s location and the stability of core s direction in terms of improved fingercode matching experiments on partial fvc2004 data sets show that it works well and outperforms three other methods

on a representation of vector continued fractions abstract vector pade approximants to power series with vector coefficients may be calculated using the three term recurrence relations of vector continued fractions if formulated in the framework of clifford algebras we show that the numerator and denominator polynomials of these fractions take particularly simple forms which require just a few degrees of freedom in their representation the new description also allows the calculation of hybrid approximants

extrapolation methods for vector sequences this is an expository paper that describes and compares five methods for extrapolating to the limit or anti limit of a vector sequence without explicit knowledge of the sequence generator the methods are the minimal polynomial extrapolation mpe studied by cabay and jackson mesina and skelboe the reduced rank extrapolation rre of eddy which we show to be equivalent to mesina s version of mpe the vector and scalar versions of the epsilon algorithm vea sea introduced by wynn and extended by brezinski and gekeler and the topological epsilon algorithm tea of brezinski we cover the derivation and error analysis of iterated versions of the algorithms as applied to both linear and nonlinear problems and we show why these versions tend to converge quadratically we also present samples from extensive numerical testing that has led us to the following conclusions a tea in spite of its role as a theoretical link between the polynomial type and the epsilon type methods has no practical appl

global models for the orientation field of fingerprints an approach based on quadratic differentials quadratic differentials naturally define analytic orientation fields on planar surfaces we propose to model orientation fields of fingerprints by specifying quadratic differentials models for all fingerprint classes such as arches loops and whorls are laid out these models are parametrised by few geometrically interpretable parameters which are invariant under euclidean motions we demonstrate their ability in adapting to given observed orientation fields and we compare them to existing models using the fingerprint images of the nist special database 4 we also illustrate that these model allow for extrapolation into unobserved regions this goes beyond the scope of earlier models for the orientation field as those are restricted to the observed planar fingerprint region within the framework of quadratic differentials we are able to verify analytically penrose s formula for the singularities on a palm l s penrose dermatoglyphics scientific american vol 221 no 6 pp 73 84 1969 potential applications of these models are the use of their parameters as indices of large fingerprint databases as well as the definition of intrinsic coordinates for single fingerprint images

an extension of a row convergence theorem for vector pade approximants abstract a row convergence theorem of de montessus type is established for vector pade approximants to a vector valued meromorphic function f while in a previous paper the authors established such a theorem for the case when f has simple poles the essential feature of the present paper is to treat the situation when f has multiple poles

fingerprint pattern classification abstract this paper presents a new method for fingerprint classification in this method fingerprint images are divided into 32 32 subregions to obtain direction pattern next the relaxation smoothing process with singularity detection and convergency checking is performed starting from the singular regions found feature parameters of the fingerprint are obtained by extracting major flow line traces the result of the experiments shows that this approach is capable of classifying fingerprint patterns into more than ten categories

row convergence theorems for generalised inverse vector valued pade approximants abstract the approximants mentioned in the title are related to vector valued continued fractions and the vector algorithm devised by wynn in 1963 here we establish a unitary invariance property of these approximants and describe how the classical 1 dimensional pade approximants can be obtained as a special case the main results of the paper consist of de montessus de ballore type convergence theorems for row sequences having fixed denominator degree of vector valued approximants to meromorphic vector functions

iterative residual based vector methods to accelerate fixed point iterations fixed point iterations are still the most common approach to dealing with a variety of numerical problems such as coupled problems multi physics domain decomposition or nonlinear problems electronic structure heat transfer nonlinear mechanics methods to accelerate fixed point iteration convergence or more generally sequence convergence have been extensively studied since the 1960 s for scalar sequences the most popular and efficient acceleration method remains the 2 of aitken various vector acceleration algorithms are available in the literature which often aim at being multi dimensional generalizations of the 2 method in this paper we propose and analyse a generic residual based formulation for accelerating vector sequences the question of the dynamic use of this residual based transformation during the fixed point iterations for obtaining a new accelerated fixed point method is then raised we show that two main classes of such iterative algorithms can be derived and that this approach is generic in that various existing acceleration algorithms for vector sequences are thereby recovered in order to illustrate the interest of such algorithms we apply them in the field of nonlinear mechanics on a simplified point wise solver used to perform mechanical behaviour unit testings the proposed test cases clearly demonstrate that accelerated fixed point iterations based on the elastic operator quasi newton method are very useful when the mechanical behaviour does not provide the so called consistent tangent operator moreover such accelerated algorithms also prove to be competitive with respect to the standard newton raphson algorithm when available

generalized strichartz inequalities for the wave equation strichartz inequalities for the wave equation u f are estimates of the solution u of the cauchy problem for that equation in the form of space time integral norms in terms of similar norms of the inhomogeneity f and of suitable norms of the initial data

symmetric phase only matched filtering of fourier mellin transforms for image registration and recognition presents a new method to match a 2d image to a translated rotated and scaled reference image the approach consists of two steps the calculation of a fourier mellin invariant fmi descriptor for each image to be matched and the matching of the fmi descriptors the fmi descriptor is translation invariant and represents rotation and scaling as translations in parameter space the matching of the fmi descriptors is achieved using symmetric phase only matched filtering spomf the performance of the fmi spomf algorithm is the same or similar to that of phase only matched filtering when dealing with image translations the significant advantage of the new technique is its capability to match rotated and scaled images accurately and efficiently the innovation is the application of spomf to the fmi descriptors which guarantees high discriminating power and excellent robustness in the presence of noise this paper describes the principle of the new method and its discrete implementation for either image detection problems or image registration problems practical results are presented for various applications in medical imaging remote sensing fingerprint recognition and multiobject identification

enhanced gradient based algorithm for the estimation of fingerprint orientation fields an accurate estimation of fingerprint orientation fields is an essential step in the overall fingerprint recognition process conventional gradient based approaches are popular but very sensitive to noise in this paper we propose a novel implementation to improve the performance of gradient based methods the enhanced algorithm chooses the best orientation estimate from four overlapping neighborhoods of every image block where the voting scheme is based on the reliability measures we test our algorithm on real fingerprint images the experiment results suggest that our enhanced algorithm achieves visibly better noise resistance with modest computation time in comparison with other gradient based methods

singular point detection by shape analysis of directional fields in fingerprints this paper presents a new fingerprint singular point detection method that is type distinguishable and applicable to various fingerprint images regardless of their resolutions the proposed method detects singular points by analyzing the shapes of the local directional fields of a fingerprint image using the predefined rules all types of singular points upper core lower core and delta points can be extracted accurately and delineated in terms of the type of singular points in case of arch type fingerprints there exists no singular point but reference points for arch type fingerprints are required to be detected for registration therefore we propose a new reference point detection method for arch type fingerprints as well the result of the experiments on the two public databases fvc2000 2a fvc2002 2a with different resolutions demonstrates that the proposed method has high accuracy in locating each types of singular points and detecting the reference points of arch type fingerprints without regard to their image resolutions

the bloch wave operator generalizations and applications part i the time independent case this is part 1 of a two part review on wave operator theory and methods the basic theory of the time independent wave operator is presented in terms of partitioned matrix theory for the benefit of general readers with a discussion of the links between the matrix and projection operator approaches the matrix approach is shown to lead to simple derivations of the wave operators and effective hamiltonians of lowdin bloch des cloizeaux and kato as well as to some associated variational forms the principal approach used throughout stresses the solution of the nonlinear equation for the reduced wave operator leading to the construction of the effective hamiltonians of bloch and of des cloizeaux several mathematical techniques which are useful in implementing this approach are explained some of them being relatively little known in the area of wave operator calculations the theoretical discussion is accompanied by several specimen numerical calculations which apply the described techniques to a selection of test matrices taken from the previous literature on wave operator methods the main emphasis throughout is on the use of numerical methods which use iterative or perturbation algorithms with simple pade approximant methods being found sufficient to deal with most of the cases of divergence which are encountered the use of damping factors and relaxation parameters is found to be effective in stabilizing calculations which use the energy dependent effective hamiltonian of lowdin in general the computations suggest that the numerical applications of the nonlinear equation for the reduced wave operator are best carried out with the equation split into a pair of equations in which the bloch effective hamiltonian appears as a separate entity the presentation of the theoretical and computational details throughout is accompanied by references to and discussion of many works which have used wave operator methods in physics chemistry and engineering some of the techniques described in this part 1 will be further extended and applied in part 2 of the review which deals with the changes which are required to extend wave operator theory to the case of a time dependent hamiltonian such as that which describes the interaction of a laser pulse with an atom or molecule

global existence and asymptotic behavior of solutions for the maxwell schrodinger equations in three space dimensions in this paper we study the global existence and asymptotic behavior of solutions for the maxwell schrodinger equations under the coulomb gauge condition in three space dimensions with the final states given att this leads to the construction of the modified wave operator for certain scattered data it is also shown that for the initial data in the range of the modified wave operator the initial value problem of the maxwell schrodinger equations has the global solutions in time

smoothing effects for schrodinger equations with electro magnetic potentials and applications to the maxwell schrodinger equations abstract we consider schrodinger equations in r 1 2 with electro magnetic potentials the potentials belong to h 1 and typically they are time independent or determined as solutions to inhomogeneous wave equations we prove kato type smoothing estimates for solutions we also apply this result to the maxwell schrodinger equations in the lorentz gauge and prove unique solvability of this system in the energy space

endpoint strichartz estimates we prove an abstract strichartz estimate which implies previously unknown endpoint strichartz estimates for the wave equation in dimension n 4 and the schrodinger equation in dimension n 3 three other applications are discussed local existence for a nonlinear wave equation and strichartz type estimates for more general dispersive equations and for the kinetic transport equation

introduction to the determinantal formulae for the levin type algorithms abstract there are two aims of this paper firstly we shall introduce the determinantal formulae for the new levin type algorithms and secondly we shall demonstrate the similarities between the new levin type algorithms and the well established methods namely the aitken 2 algorithm the brezinski theta algorithm and the lubkin transformation actually there are two groups of similarities first of the group demonstrates the similarity between the super enhanced levin algorithm the super modified levin algorithm the brezinski theta algorithm and the lubkin transformation the second group of similarity is between the modified levin algorithm the original levin transformation and the aitken 2 algorithm

extrapolation methods for vector sequences an analogue of aitken s 2 method suitable for vector sequences is proposed aspects of the numerical performance of the vector algorithm based on using the moore penrose inverse are investigated the fact that the denominator polynomial associated with a vector pade approximant is the square of its equivalent in the scalar case is shown to be a source of approximation error in cases where the convergence of the vector sequence is dominated by real eigenvalues a hybrid form of the vector pade approximant having a denominator polynomial of minimal degree is proposed and its effectiveness is demonstrated on several standard examples

markov random field models for directional field and singularity extraction in fingerprint images a bayesian formulation is proposed for reliable and robust extraction of the directional field in fingerprint images using a class of spatially smooth priors the spatial smoothness allows for robust directional field estimation in the presence of moderate noise levels parametric template models are suggested as candidate singularity models for singularity detection the parametric models enable joint extraction of the directional field and the singularities in fingerprint impressions by dynamic updating of feature information this allows for the detection of singularities that may have previously been missed as well as better aligning the directional field around detected singularities a criteria is presented for selecting an optimal block size to reduce the number of spurious singularity detections the best rates of spurious detection and missed singularities given by the algorithm are 4 9 and 7 1 respectively based on the nist 4 database

pixel level singular point detection from multi scale gaussian filtered orientation field singular point as a global feature plays an important role in fingerprint recognition inconsistent detection of singular points apparently gives an affect to fingerprint alignment classification and verification accuracy this paper proposes a novel approach to pixel level singular point detection from the orientation field obtained by multi scale gaussian filters initially a robust pixel level orientation field is estimated by a multi scale averaging framework then candidate singular points in pixel level are extracted from the complex angular gradient plane derived directly from the pixel level orientation field the candidate singular points are finally validated via a cascade framework comprised of nested poincare indices and local feature based classification experimental results over the fvc 2000 db2 confirm that the proposed method achieves robust and accurate orientation field estimation and consistent pixel level singular point detection the experimental results exhibit a low computational cost with better performance thus the proposed method can be employed in real time fingerprint recognition

walking to singular points of fingerprints singular point is an essential global feature in fingerprint images existing methods for singular points detection generally visit each pixel or each small image block to determine the singular point that is to say existing methods require scanning the image to compute a quantity at each pixel or block and hence they are inevitably time consuming we propose a fast algorithm for detecting singular points by walking directly to them instead of scanning the image walking directional fields wdfs are established from the orientation field then following the walking directions on wdfs we can rapidly walk to the singular points the walking algorithm is extremely fast and easily implemented with acceptable accuracy further more its accuracy can also be improved by combining with state of the art methods we can rapidly walk to a candidate singular point then refine its location using existing more accurate method in the local area experimental results on datasets of spd2010 and fvc validate the high efficiency and satisfactory accuracy of the proposed algorithm highlightswe propose a novel fast method for singular point detection we can walk directly to singular points without scanning fingerprint images simplicity of the idea makes the algorithm easy to be implemented our algorithm can be combined with state of the art method to improve performance

on space time means and everywhere defined scattering operators for nonlinear klein gordon equations on demontre l existence d operateurs de diffusion definis partout pour certaines equations de klein gordon non lineaires

computerized flow field analysis oriented texture fields an approach to the solution of signal to symbol transformation in the domain of flow fields such as oriented texture fields and velocity vector fields is discussed the authors use the geometric theory of differential equations to derive a symbol set based on the visual appearance of phase portraits which are a geometric representation of the solution curves of a system of differential equations they also provide the computational framework to start with a given flow field and derive its symbolic representation specifically they segment the given texture derive its symbolic representation and perform a quantitative reconstruction of the salient features of the original texture based on the symbolic descriptors results of applying this technique to several real texture images are presented this technique is useful in describing complex flow visualization pictures defects in lumber processing defects in semiconductor wafer inspection and optical flow fields

introduction to the improved functional epsilon algorithm this paper introduces the improved functional epsilon algorithm we have defined this new method in principle of the modified aitken 2 algorithm moreover we have found that the improved functional epsilon algorithm has remarkable precision of the approximation of the exact solution and there exists a relationship with the integral pade approximant the use of the improved functional epsilon algorithm for accelerating the convergence of sequence of functions is demonstrated the relationship of the improved functional epsilon algorithm with the integral pade approximant is also demonstrated moreover we illustrate the similarity between the integral pade approximant and the modified aitken 2 algorithm thus we have shown that the integral pade approximant is a natural generalisation of modified aitken 2 algorithm

systematic methods for the computation of the directional fields and singular points of fingerprints the first subject of the paper is the estimation of a high resolution directional field of fingerprints traditional methods are discussed and a method based on principal component analysis is proposed the method not only computes the direction in any pixel location but its coherence as well it is proven that this method provides exactly the same results as the averaged square gradient method that is known from literature undoubtedly the existence of a completely different equivalent solution increases the insight into the problem s nature the second subject of the paper is singular point detection a very efficient algorithm is proposed that extracts singular points from the high resolution directional field the algorithm is based on the poincare index and provides a consistent binary decision that is not based on postprocessing steps like applying a threshold on a continuous resemblance measure for singular points furthermore a method is presented to estimate the orientation of the extracted singular points the accuracy of the methods is illustrated by experiments on a live scanned fingerprint database

vector rational interpolation algorithms of burlisch stoer neville form we present algorithms of the bulirsch stoer neville form for calculating the value of the vector rational interpolant the derivation parallels that of the bulirsch stoer algorithm for the usual scalar rational interpolation algorithm of stoer and bulirsch using the clifford algebra foundations for vector rational interpolants of roberts

fingerprint ridge distance computation methodologies abstract the average ridge distance of fingerprint images is used in many problems and applications it is used in fingerprint filter design or in identification and classification procedures this paper addresses the problem of local average ridge distance computation this computation is based on a two step procedure first the average distance is defined in each significant portion of the image and then this information is propagated onto the remaining regions to complete the computation two methods are considered in the first step geometric and spectral in the geometric approach the central points of ridges are estimated on a regular grid and straight lines passing through these points and parallel to the ridge directions are used the second method is based on the computation of harmonic coefficients leading to effective estimates of the average ridge period in order to complete the average distance map a diffusion equation is used so that maps with minimum variations are favored finally some experimental results on nist sdb4 are reported

well posedness for the nonlinear klein gordon schrodinger equations with heterointeractions in this paper we study the well posedness of solution to a certain system of nonlinear klein gordon schrodinger equations in three space dimensions basing on the strichartz estimates we obtain the global existence uniqueness of the solutions and continuous dependence with respect to initial data in the sobolev spaces of low regularities by setting appropriate contraction and taking difference estimates

regular articlegeneralized strichartz inequalities for the wave equation we make a synthetic exposition of the generalized strichartz inequalities for the wave equation obtained in 6 together with the limiting cases recently obtained in 13 with as simple proofs as possible the proofs combine stationary phase estimates dyadic decompositions the hardy littlewood inequality or the holder inequality in time and abstract duality and interpolation arguments

a nonlinear orientation model for global description of fingerprints a nonlinear orientation model for the representation of the orientation matrix of a fingerprint image is presented a general procedure to obtain the set of parameters describing this model is shown particularly a piecewise linear orientation function is analysed the model compared with a previous zero pole model shows substantial decrease in the orientation error the application of this model for efficient identity verification based on the ridge orientation is explored

singular points detection based on zero pole model in fingerprint images an algorithm is proposed which combines zero pole model and hough transform ht to detect singular points orientation of singular points is defined on the basis of the zero pole model which can further explain the practicability of zero pole model contrary to orientation field generation detection of singular points is simplified to determine the parameters of the zero pole model ht uses rather global information of fingerprint images to detect singular points this makes our algorithm more robust to noise than methods that only use local information as the zero pole model may have a little warp from actual fingerprint orientation field poincare index is used to make position adjustment in neighborhood of the detected candidate singular points experimental results show that our algorithm performs well and fast enough for real time application in database nist 4

hybrid vector transformations we present in this paper hybrid and semi hybrid vector extrapolation methods for a vector sequence transformation we will define the generalized residual which allows us to introduce a new hybrid vector transformation when solving linear systems this new transformation reduces to the hybrid procedure defined by brezinski and redivo zaglia 1994 which is a generalization of the smoothing technique in the second part of this paper we define a new composite transformation called semi hybrid when applied to linearly generated sequences we will show that the residual polynomial of the semi hybrid transformation is the product of two residual polynomials

fingerprint identification using graph matching abstract a new algorithm for automated fingerprint encoding and matching is presented the algorithm is intended to be insensitive to imperfections introduced during fingerprint registration such as noise distortion and displacement a fingerprint is represented in the form of a graph whose nodes correspond to ridges in the print edges of the graph connect nodes that represent neighboring or intersecting ridges hence the graph structure captures the topological relationships within the fingerprint the algorithm has been implemented and tested using a library of real life fingerprint images

kato type estimates for nls equation in a scalar field and unique solvability of nkgs system in energy space abstract we consider schrodinger equation in r 2 1 with nonlinear scalar potential the potentials are time independent or determined as solutions to inhomogeneous wave equations by constructing a modified propagator we derive kato type smoothing estimates for the nonlinear schrodinger nls equation with the help of these results we prove the unique solvability of the nonlinear klein gordon schrodinger nkgs system for all time in the energy space

long range scattering for the maxwell schrodinger system in the lorenz gauge without any restriction on the size of data abstract this paper concerns the scattering theory for the maxwell schrodinger ms system in the lorenz gauge or more precisely the existence of the modified wave operators for this system in r 3 1 space time we construct solutions to the ms system which behave as free maxwell and schrodinger waves with prescribed asymptotic states when t without any restriction on the size thereof since this system belongs to the borderline between the short range case and the long range case we need modification of phase for the schrodinger function

solution of integral equations using generalised inverse function valued pade approximants i abstract neumann series solutions for the linear integral equation x 1 1 0 1 x y y d y converge for small values of we use generalised inverse function valued pade approximants to accelerate the convergence of the neumann series and to estimate the singular value of these estimates are found to compare very favourably with those from the fredholm determinant method and the pade approximant method

fingerprint reference point detection for image retrieval based on symmetry and variation reference point plays an important role in fingerprint identification systems the reference point is widely used for the fingerprint retrieval in large scale databases this paper proposes a novel algorithm for detecting a convex core point as a unique reference point consistently and accurately for all types of fingerprints in order to detect robust core point candidates a modified complex filter called semi radial symmetry filter is proposed to detect correctly rotational symmetries of core points moreover a vertical orientation variation feature called voriv feature is proposed to remove spurious core points and concave core points therefore the proposed technique computes the variation and symmetry combined energy vscome then the reference point is located by searching the global vscome maximum the experimental results on the public database fvc2004 db1 set a show that the proposed technique exhibits a very high robustness and gets the best performance in comparing with other approaches in literature

vector valued rational interpolants i it is shown explicitly that the samelson inverse may be used to define vector valued thiele type rational interpolants and the equivalence with claessens algorithm is established for the special case of vector valued pade approximants the general form of mccleod s theorem follows as a corollary

fingerprint matching using an orientation based minutia descriptor we introduce a novel fingerprint representation scheme that relies on describing the orientation field of the fingerprint pattern with respect to each minutia detail this representation allows the derivation of a similarity function between minutiae that is used to identify corresponding features and evaluate the resemblance between two fingerprint impressions a fingerprint matching algorithm based on the proposed representation is developed and tested with a series of experiments conducted on two public domain collections of fingerprint images the results reveal that our method can achieve good performance on these data collections and that it outperforms other alternative approaches implemented for comparison

on convex relaxation of graph isomorphism graphs are a ubiquitous mathematical abstraction used in numerous problems in science and engineering of particular importance is the need to find the best structure preserving matching of graphs since graph matching gm is a computationally intractable problem numerous heuristics exist to approximate its solution an important class of gm heuristics is relaxation techniques based on replacing the original problem by a continuous convex program conditions for applicability or inapplicability of such convex relaxations are poorly understood in this study we propose easy to check spectral properties to characterize a wide family of graphs for which we prove equivalence of convex relaxation to the exact gm

the cauchy problem for the coupled maxwell schrodinger equations the cauchy problem for the coupled maxwell schrodinger equations in rd in the lorentz gauge is considered the viscosity method is used to establish local existence in one and two space dimensions global solutions are obtained

global existence and uniqueness of solutions to the maxwell schrodinger equations the time local and global well posedness for the maxwell schrodinger equations is considered in sobolev spaces in three spatial dimensions the strichartz estimates of koch and tzvetkov type are used for obtaining the solutions in the sobolev spaces of low regularities one of the main results is that the solutions exist time globally for large data

energy convergence for singular limits of zakharov type systems we prove existence and uniqueness of solutions to the klein gordon zakharov system in the energy space h1 l2 on some time interval which is uniform with respect to two large parameters c and these two parameters correspond to the plasma frequency and the sound speed in the simultaneous high frequency and subsonic limit we recover the nonlinear schrodinger system at the limit we are also able to say more when we take the limits separately

fingerprint classification using fast fourier transform and nonlinear discriminant analysis in this paper we present a new approach for fingerprint classification based on discrete fourier transform dft and nonlinear discriminant analysis utilizing the dft and directional filters a reliable and efficient directional image is constructed from each fingerprint image and then nonlinear discriminant analysis is applied to the constructed directional images reducing the dimension dramatically and extracting the discriminant features the proposed method explores the capability of dft and directional filtering in dealing with low quality images and the effectiveness of nonlinear feature extraction method in fingerprint classification experimental results demonstrates competitive performance compared with other published results

existence of solutions for schrodinger evolution equations we study the existence uniqueness and regularity of the solution of the initial value problem for the time dependent schrodinger equationi u t 1 2 u v t x u u 0 u0 we provide sufficient conditions onv t x such that the equation generates a unique unitary propagatoru t s and such thatu t s u0ec1 l2 c0 h2 n foru0eh2 n the conditions are general enough to accommodate moving singularities of type x 2 n 4 or x n 2 n 3

a randomized approach with geometric constraints to fingerprint verification abstract in this paper a fuzzy bipartite weighted graph model is proposed to solve fingerprint verification problem a fingerprint image is preprocessed first to form clusters of feature points which are called feature point clusters twenty four attributes are extracted for each feature point cluster the attributes are characterized by fuzzy values attributes of an input image to be verified are considered as the set of left nodes in a fuzzy bipartite weighted graph and the attributes of claimed template fingerprint image are considered as the set of right nodes in the graph the fingerprint verification problem is thus converted into a fuzzy bipartite weighted graph matching problem a matching algorithm is proposed for the fuzzy bipartite weighted graph model to find an optimal matching with a goodness score experimental results reveal the feasibility of the proposed approach in fingerprint verification

geometric framework for fingerprint image classification given a digitized fingerprint image we would like to classify it into one of several types already established in the literature in this paper we consider five types for classification double loop whorl left loop right loop and arch we illustrate the use of a geometric framework for a systematic top down classification of the foregoing types from the double loop type down to the arch type in the order given above the framework employs both a geometric grouping and a global geometric shape analysis of fingerprint ridges to accomplish the required task these processes are based on the framework s underlying b spline representation and interpretation of the ridges

a fast projected fixed point algorithm for large graph matching we propose a fast algorithm for approximate matching of large graphs previous graph matching algorithms suffer from high computational complexity and therefore do not have good scalability by using a new doubly stochastic projection for matching two weighted graphs of n nodes our algorithm has time complexity only o n 3 per iteration and space complexity o n 2 we proved that our algorithm converges at a super logarithmic rate experiments on large synthetic and real graphs over 1000 nodes were conducted to evaluate the performance of various algorithms results show that due to its fast convergence our algorithm is more than an order of magnitude faster than the previous state of the art algorithms while maintaining comparable accuracy in large graph matching highlightslow time complexity o n3 iteration for two graphs of n nodes super logarithm convergence guarantee large graph matching experiments