the image foresting transform theory algorithms and applications the image foresting transform ift is a graph based approach to the design of image processing operators based on connectivity it naturally leads to correct and efficient implementations and to a better understanding of how different operators relate to each other we give here a precise definition of the ift and a procedure to compute it a generalization of dijkstra s algorithm with a proof of correctness we also discuss implementation issues and illustrate the use of the ift in a few applications

blind identification of mimo fir systems driven by quasistationary sources using second order statistics a frequency domain approach this paper discusses a frequency domain method for blind identification of multiple input multiple output mimo convolutive channels driven by white quasistationary sources the sources can assume arbitrary probability distributions and in some cases they can even be all gaussian distributed we also show that under slightly more restrictive assumptions the algorithm can be applied to the case when the sources are colored nonstationary signals we demonstrate that by using the second order statistics of the channel outputs under mild conditions on the nonstationarity of sources and under the condition that channel is column wise coprime the impulse response of the mimo channel can be identified up to an inherent scaling and permutation ambiguity we prove that by using the new algorithm under the stated assumptions a uniform permutation across all frequency bins is guaranteed and the inherent frequency dependent scaling ambiguities can be resolved hence no post processing is required as is the case with previous frequency domain algorithms we further present an efficient two step frequency domain algorithm for identifying the channel numerical simulations are presented to demonstrate the performance of the new algorithm

an exact finite rotation shell theory its mixed variational formulation and its finite element implementation a non linear shell theory including transverse shear strains with exact description of the kinematical fields is developed the strain measures are derived via the polar decomposition theorem allowing for an explicit use of a three parametric rotation tensor thus in plane rotations also called drilling degrees of freedom are included in a natural way various alternatives of the theory are derived for a special version of the theory with altogether six kinematical fields different mixed variational principles are given a hybrid finite element formulation which does not exhibit locking phenomena is developed numerical examples of shell deformation at finite rotations with excellent element performance are presented comparison with results reported in the literature demonstrates the features of the theory as well as the proposed finite element formulation

meshless implementation of the geometrically exact kirchhoff love shell theory summary in the present paper a meshless generalized multiple fixed least squares implementation of the geometrically exact kirchhoff love shell theory is described the material time derivative of the deformation gradient and the first piola kirchhoff stress tensor are considered as basic conjugate quantities to evaluate the internal power the shell s initial geometry is reproduced exactly by the predefined mapping from a reference plane configuration as a constitutive model a neo hookean material whose functional is altered in compliance with the plane stress condition is chosen the augmented weak form suitable for both interpolative and non interpolative approximations thanks to the imposition of the essential boundary conditions through lagrange multipliers is consistently linearized and the resultant bilinear form proved to be symmetric the appearance of the corner reactions related to the jumps of the pseudo torsion boundary moment requires the inclusion of additional pointwise displacement constraints at the essential boundary corners the importance of these quantities is demonstrated in the numerical tests revealing its positive influence on the displacements and particularly their derivatives up to 3rd order in both linear and nonlinear problems the possibility of incorporation of drilling boundary moment for nonlinear problems was successfully assessed copyright 2014 john wiley sons ltd

a 4 node finite shell element for the implementation of general hyperelastic 3d elasticity at finite strains abstract in this paper a finite shell element for large deformations is presented based on extensible director kinematics the essential feature is an interface to arbitrary three dimensional material laws the non linear lagrangian formulation is based on the three field variational principle parametrized with the displacement vector enhanced green lagrangian strain tensor and second piola kirchhoff stress tensor the developed quadrilateral shell element is characterized by a course mesh accuracy and distortion insensitivity compared with bilinear displacement approaches furthermore plane stress response is approximately recovered in the asymptotic case of vanishing thickness a number of example problems investigating large deformation as well as finite strain applications are presented compressible and incompressible hyperelastic materials of the st venant kirchhoff neo hookean and mooney rivlin type are particularly used

a linear time algorithm for computing exact euclidean distance transforms of binary images in arbitrary dimensions a sequential algorithm is presented for computing the exact euclidean distance transform dt of a k dimensional binary image in time linear in the total number of voxels n the algorithm which is based on dimensionality reduction and partial voronoi diagram construction can be used for computing the dt for a wide class of distance functions including the l sub p and chamfer metrics at each dimension level the dt is computed by constructing the intersection of the voronoi diagram whose sites are the feature voxels with each row of the image this construction is performed efficiently by using the dt in the next lower dimension the correctness and linear time complexity are demonstrated analytically and verified experimentally the algorithm may be of practical value since it is relatively simple and easy to implement and it is relatively fast not only does it run in o n time but the time constant is small a simple modification of the algorithm computes the weighted euclidean dt which is useful for images with anisotropic voxel dimensions a parallel version of the algorithm runs in o n p time with p processors

efficient euclidean distance transform algorithm of binary images in arbitrary dimensions in this paper we propose an efficient algorithm i e pbedt for short to compute the exact euclidean distance transform edt of a binary image in arbitrary dimensions the pbedt is based on independent scan and implemented in a recursive way i e the edt of a d dimensional image is able to be computed from the edts of its d 1 dimensional sub images in each recursion all of the rows in the current dimensional direction are processed one by one the points in the current processing row and their closest feature points in d 1 dimensional sub images can be shown in a euclidean plane by using the geometric properties of the perpendicular bisector the closest feature points of d 1 dimensional sub images are easily verified so as to lead to the edt of a d dimensional image after eliminating the invalid points the time complexity of the pbedt algorithm is linear in the amount of both image points and dimensions with a small coefficient compared with the state of the art edt algorithms the pbedt algorithm is much faster and more stable in most cases

blind equalization of digital communication channels using high order moments the authors describe algorithms for blind equalization of digital communication channels of the quadrature amplitude modulation qam type these algorithms are based on the fourth order statistical moments of the received data sequence the first of the two is a linear least squares type algorithm the second algorithm is of the nonlinear least squares type the algorithms use the fourth order statistical moments of the symbol sequence to explicitly estimate the channel impulse response the estimated impulse response is used in turn to construct a linear mean square error equalizer the performance of this equalizer is not optimal in any sense but it is adequate for channels with mild intersymbol interference or when the number of data points available for estimating the channel response is very large

fast maximum likelihood for blind identification of multiple fir channels this paper develops a fast maximum likelihood method for estimating the impulse responses of multiple fir channels driven by an arbitrary unknown input the resulting method consists of two iterative steps where each step minimizes a quadratic function the two step maximum likelihood tsml method is shown to be high snr efficient i e attaining the cramer rao lower bound crb at high snr the tsml method exploits a novel orthogonal complement matrix of the generalized sylvester matrix simulations show that the tsml method significantly outperforms the cross relation cr method and the subspace ss method and attains the crb over a wide range of snr this paper also studies a fisher information fi matrix to reveal the identifiability of the m channel system a strong connection between the fi based identifiability and the cr based identifiability is established

blind identification of fir systems driven by markov like input signals we propose a new algorithm for the blind identification and equalization of finite impulse response fir systems using the second order statistics of the received signal the new algorithm is set in the same context as the algorithms of tong et al 1994 and moulines et al 1995 however unlike those earlier approaches it is designed to allow correlated input signals specifically the algorithm accommodates finite memory sources and sources whose autocorrelation function decays exponentially numerical simulations compare the equalization performance of the new algorithm to those of tong and moulines it is shown that our algorithm yields consistently lower bit error rates at a wide variety of signal to noise ratios and at various equalizer lengths moreover the algorithm maintains this advantage even if it has no a priori information of source correlation or if source symbols are uncorrelated

a list processing approach to compute voronoi diagrams and the euclidean distance transform we propose an efficient voronoi transform algorithm for constructing voronoi diagrams using segment lists of rows a significant feature of the algorithm is that it takes segments rather than pixels as the basic units to represent and propagate the nearest neighbor information the segment lists are dynamically updated as they are scanned a distance map can then be easily computed from the segment list representation of the voronoi diagram experimental results have demonstrated its high efficiency extension of the algorithm to higher dimensions is also discussed

the cosserat surface as a shell model theory and finite element formulation abstract relying on the concept of a cosserat continuum the reduction of the three dimensional equations of a shell body to two dimensions is carried out in a direct manner by considering the cosserat continuum to be a two dimensional surface by that a non linear shell theory including transverse shear strains with exact description of the kinematical fields is derived the strain measures are taken to be the first and the second cosserat deformation tensors allowing for an explicit use of a three parametric rotation tensor thus inplane rotations also called drilling degrees of freedom are included in a natural way the structure of the configuration space is discussed and two possible definitions of it are given equipped once with a killing metric and once with an euclidean one a partially mixed variational principle is proposed on the base of which an efficient hybrid finite element formulation which does not exhibit locking phenomena is developed various numerical examples of shell deformations at finite rotations with excellent element performance are presented

a unified finite strain theory for membranes and ropes abstract the finite strain theory is reformulated in the frame of the tangential differential calculus tdc resulting in a unification in a threefold sense firstly ropes membranes and three dimensional continua are treated with one set of governing equations secondly the reformulated boundary value problem applies to parametrized and implicit geometries therefore the formulation is more general than classical ones as it does not rely on parametrizations implying curvilinear coordinate systems and the concept of co and contravariant base vectors this leads to the third unification tdc based models are applicable to two fundamentally different numerical approaches on the one hand one may use the classical surface fem where the geometry is discretized by curved one dimensional elements for ropes and two dimensional surface elements for membranes on the other hand it also applies to recent trace fem approaches where the geometry is immersed in a higher dimensional background mesh then the shape functions of the background mesh are evaluated on the trace of the immersed geometry and used for the approximation as such the trace fem is a fictitious domain method for partial differential equations on manifolds the numerical results show that the proposed finite strain theory yields higher order convergence rates independent of the numerical methodology the dimension of the manifold and the geometric representation type

genuinely resultant shell finite elements accounting for geometric and material non linearity the underlying theory is statically and geometrically exact and it naturally includes small strain and finite strain problems of thin as well as thick shells this paper examines the development of computational procedures employing the newton kantorovich linearization process and the galerkin type discretization method the treatment of finite rotations through an arbitrary parametrization of the rotation group the interpolation procedure of so 3 valued functions underlying the construction of finite element basis

distances defined by neighborhood sequences abstract this paper investigates general properties of distance functions defined over digitized space we assume that a distance between two points is defined as the length of a shortest path connecting them in the underlying graph which is defined by a given neighborhood sequence many typical distance functions can be described in this form but there are cases in which given neighborhood sequence do not define distance functions we first derive a necessary and sufficient condition for a neighborhood sequence to define a distance function we then discuss another important problem of estimating how tight such distances can approximate the euclid distance from the view point of relative error and absolute error

blind and semi blind fir multichannel estimation global identifiability conditions two channel estimation methods are often opposed training sequence methods that use the information induced by known symbols and blind methods that use the information contained in the received signal and possibly hypotheses on the input symbol statistics but without integrating the information from known symbols if present semi blind methods combine both training sequence and blind information and are more powerful than the two methods separately we investigate the identifiability conditions for blind and semi blind finite impulse response fir multichannel estimation in terms of channel characteristics received data length and input symbol excitation modes as well as number of known symbols for semi blind estimation two models corresponding to two different cases of a priori knowledge on the input symbols are studied the deterministic model in which the unknown symbols are considered as unknown deterministic quantities and the gaussian model in which they are considered as gaussian random variables this last model includes the methods using the second order statistics of the received data semi blind methods appear superior to blind and training sequence methods and allow the estimation of any channel with only few known symbols furthermore the gaussian model appears more robust than the deterministic one as it leads to less demanding identifiability conditions

on unique localization of multiple sources by passive sensor arrays necessary and sufficient conditions are derived for the unique localization of narrowband sources having the same known center frequency by passive sensor arrays the conditions specify the maximum number of sources that can be uniquely localized by a general array that satisfies some mild geometric constraints the conditions are expressed in terms of the number of sensors and the rank of the correlation matrix of the sources two different conditions are presented the first guarantees uniqueness for every batch of sampled data the second which is weaker guarantees uniqueness for almost every batch of sampled data with the exception of a set of batches of measure zero it is shown that a condition that is slightly weaker than the second one is also necessary

morphological iterative closest point algorithm this work presents a method for the registration of three dimensional 3 d shapes the method is based on the iterative closest point icp algorithm and improves it through the use of a 3 d volume containing the shapes to be registered the voronoi diagram of the model shape points is first constructed in the volume then this is used for the calculation of the closest point operator this way a dramatic decrease of the computational cost is achieved

digital distance functions on three dimensional grids in this paper we examine five different three dimensional grids suited for image processing digital distance functions are defined on the cubic face centered cubic body centered cubic honeycomb and diamond grids we give the parameters that minimize an error function that favors distance functions with low rotational dependency we also give an algorithm for computing the distance transform the tool by which these distance functions can be applied in image processing applications

strict identifiability of multiple fir channels driven by an unknown arbitrary sequence the problem of blind identification of multiple finite impulse response fir channels driven by a common input arises in a wide range of applications it has received increasing attention in the signal processing community a system of multiple fir channels driven by an unknown input is said to be strictly identifiable if in the absence of noise the given channel outputs can only be realized by a unique up to a constant system impulse response and a unique input sequence we show necessary and sufficient conditions for strict identifiability and establish a connection among strict identifiability a cross relation based cr based identifiability and a fisher information based fi based identifiability

thin shells with finite rotations formulated in biot stresses theory and finite element formulation a bending theory for thin shells undergoing finite rotations is presented and its associated finite element model is described the kinematic assumption is based on a shear elastic reissner mindlin theory the starting point for the derivation of the strain measures are the resultant equilibrium equations and the associated principle of virtual work within this formulation the polar decomposition of the shell material deformation gradient leads to symmetric strain measures the associated work conjugate stress resultants and stress couples are integrals of the biot stress tensor this tensor is invariant with respect to rigid body motions and therefore appropriate for the formulation of constitutive equations finite rotations are introduced via eulerian angles the finite element discretization of arbitrary shells is based on the isoparametric concept formulated with respect to a plane reference configuration the numerical model is applied to different non linear plate and shell problems and compared with existing formulations due to a consistent linearization the step size of a load increment is only limited by the local convergence behaviour of newton s method

identification of 2 d noncausal gauss markov random fields parameter identification of multidimensional noncausal markov random fields is an important paradigm in multidimensional signal processing and modeling and the solutions to this problem are employed in many areas of image processing an original procedure for estimating the model parameters of discrete index 2 d noncausal gauss markov random fields gmrfs from noisy observations is proposed valid for both finite and infinite lattices and for any kind of boundary conditions starting from a suitable local representation of the gmrf and taking into account the symmetry property of so called field potentials a linear equation set relating the model parameters to the 2 d autocorrelation function known or estimated of the observed field is derived its solution gives the parameter estimates of the gmrf together with the estimate of the possibly unknown variance of the observation noise

the stability of nonlinear least squares problems and the cramer rao bound a number of problems of interest in signal processing can be reduced to nonlinear parameter estimation problems the traditional approach to studying the stability of these estimation problems is to demonstrate finiteness of the cramer rao bound crb for a given noise distribution we review an alternate deterministic notion of stability for the associated nonlinear least squares nls problem from the realm of nonlinear programming i e that the global minimizer of the least squares problem exists and varies smoothly with the noise furthermore we show that under mild conditions identifiability of the parameters along with a finite crb for the case of gaussian noise is equivalent to the deterministic stability of the nls problem finally we demonstrate the application of our result which is general to the problems of multichannel blind deconvolution and sinusoid retrieval to generate new stability results for these problems with little additional effort

estimating shortest paths and minimal distances on digitized three dimensional surfaces abstract the estimation of minimal distances and shortest paths between points on a continuous three dimensional 3d surface given in digitized form is considered the suggested approach combines recently developed length estimators for digitized 3d curves with well known algorithms for computing shortest paths in sparse graphs to estimate the minimal distances and the corresponding shortest paths in a systematic computationally efficient way in comparison to differential geometry techniques for solving the continuous geodesic problem and to computational geometry algorithms for solving the discrete geodesic probelm the suggested hybrid continuous discrete approach is well suited to applications in which continuous surfaces are given in digitized form computation time must be relatively short and an approximate solution is acceptable in particular the suggested method can be used to efficiently obtain a good initial approximation as an input to other algorithms thus improving their speed of convergence and reducing their tendency to converge to insignificant local minima some confusion has recently arisen with respect to the relation between the design of length estimators and the optimization of local distances for distance transformations since 3d length estimation is a central concept in the suggested approach an effort is made to resolve discrepancies and to highlight the similarities and differences between these problems it is shown that while in two dimensions the design of length estimators and the design of local weights for distance transformations are rather similar in three dimensions digital geometry dictates that these problems are different the contexts in which each of the two approaches should be preferred are identified

a continuum based shell theory for non linear applications the paper introduces a non linear shell theory which provides a complete three dimensional state of stress since the theory is derived from simple three dimensional continuum mechanics it is very easy to understand as an example the theory is applied to quadrilateral shell elements which provide only displacement degrees of freedom located at nodes on the outer surfaces and one degree of freedom at the middle surface it is proposed to eliminate this degree of freedom on element level so that the elements have the same layout as the equivalent brick elements but have a better behaviour in bending have stress resultants and are cheaper with respect to computational effort the advantages with respect to implementation in a finite element program as well as in special applications are obvious however well known conditioning problems in thin shell applications must be expected therefore emphasis is put on this issue in the example problems it is shown that the elements can give acceptable answers in engineering applications and offer a potential for material non linear applications which will be considered in a forthcoming paper

bayes error estimation using parzen and k nn procedures the use of k nearest neighbor k nn and parzen density estimates to obtain estimates of the bayes error is investigated under limited design set conditions by drawing analogies between the k nn and parzen procedures new procedures are suggested and experimental results are given which indicate that these procedures yield a significant improvement over the conventional k nn and parzen procedures we show that by varying the decision threshold many of the biases associated with the k nn or parzen density estimates may be compensated and successful error estimation may be performed in spite of these biases experimental results are given which demonstrate the effect of kernel size and shape parzen the size of k k nn and the number of samples in the design set

data efficient blind ofdm channel estimation using receiver diversity we investigate non data aided channel estimation for cyclically prefixed orthogonal frequency division multiplexing ofdm systems by exploiting channel diversity using only two receive antennas a blind deterministic algorithm is proposed identifiability conditions are derived that guarantee the perfect channel retrieval in the absence of noise in the presence of noise the proposed method has the desired property of being data efficient only a single ofdm block is needed to achieve good estimation performance for a wide range of snr values the algorithm is also robust to input symbols as it does not have any restriction on the input symbols with regard to their constellation or their statistical properties in addition this diversity based algorithm is computationally efficient and its performance compares favorably to most existing blind algorithms

digital topology and geometry in medical imaging a survey digital topology and geometry refers to the use of topologic and geometric properties and features for images defined in digital grids such methods have been widely used in many medical imaging applications including image segmentation visualization manipulation interpolation registration surface tracking object representation correction quantitative morphometry etc digital topology and geometry play important roles in medical imaging research by enriching the scope of target outcomes and by adding strong theoretical foundations with enhanced stability fidelity and efficiency this paper presents a comprehensive yet compact survey on results principles and insights of methods related to digital topology and geometry with strong emphasis on understanding their roles in various medical imaging applications specifically this paper reviews methods related to distance analysis and path propagation connectivity surface tracking image segmentation boundary and centerline detection topology preservation and local topological properties skeletonization and object representation correction and quantitative morphometry a common thread among the topics reviewed in this paper is that their theory and algorithms use the principle of digital path connectivity path propagation and neighborhood analysis

sufficient conditions for regularity and strict identifiability in mimo systems we consider regularity and identifiability of convolutive multi input multi output mimo systems with additive white gaussian noise modeling the source and finite impulse response fir channel sequences as deterministic unknowns in the blind context the mimo system is not locally identifiable hence its fisher information matrix fim is not regular in fact the dimension of the complex valued blind fim null space is at least the number of sources squared because the fim is singular additional information about the system is required to resolve the degrees of uncertainty and thereby obtain a valid cramer rao bound crb therefore it is of interest to know under what conditions the blind fim nullity reaches its lower bound we develop sufficient conditions for the complex fim to attain its minimum nullity refining previous necessary conditions and extending single input multi output simo results we show that the sufficient conditions for the complex fim to have minimum nullity are also equivalent to sufficient conditions for mimo strict identifiability these provide sufficient conditions on the richness of the sources the required diversity and the source lengths under these conditions additional constraints such as training may be employed to yield an identifiable system with no ambiguities remaining

computing distance transformations in convex and non convex domains abstract it is shown that the well known two pass sequential local transformation algorithm for computing a distance transformation in rectangular domains may fail in some convex integer domains but that a four pass algorithm is sufficient in all two dimensional convex domains for non convex domains the number of passes necessary is shown to be generally greater two propagation algorithms for computing the distance transformation are described and shown theoretically and experimentally to be computationally more efficient than the sequential local transformation algorithm in non convex domains of complex shape the relationship of the distance transformation in non convex domains to some more general transformations is explored

automatic aneurysm neck detection using surface voronoi diagrams a new automatic approach for saccular intracranial aneurysm isolation is proposed in this work due to the inter and intra observer variability in manual delineation of the aneurysm neck a definition based on a minimum cost path around the aneurysm sac is proposed that copes with this variability and is able to make consistent measurements along different data sets as well as to automate and speedup the analysis of cerebral aneurysms the method is based on the computation of a minimal path along a scalar field obtained on the vessel surface to find the aneurysm neck in a robust and fast manner the computation of the scalar field on the surface is obtained using a fast marching approach with a speed function based on the exponential of the distance from the centerline bifurcation between the aneurysm dome and the parent vessels in order to assure a correct topology of the aneurysm sac the neck computation is constrained to a region defined by a surface voronoi diagram obtained from the branches of the vessel centerline we validate this method comparing our results in 26 real cases with manual aneurysm isolation obtained using a cut plane and also with results obtained using manual delineations from three different observers by comparing typical morphological measures

on the complexity of iqml algorithms the authors study the computational complexity of two methods for solving least squares and maximum likelihood modal analysis problems in particular they consider the steiglitz mcbride and iterative quadratic maximum likelihood iqml algorithms j h mcclellan and d lee ibid vol 39 no 2 p 509 12 1991 have shown the iterations of the two methods to be equivalent however they suggest that the steiglitz mcbride algorithm may be computationally preferable a method for reducing the dimension of the matrix inversion required at each iteration of iqml is provided the resulting reduction in the computation makes the computational complexity of iqml commensurate with that of the steiglitz mcbride algorithm

edge preserving smoothing using a similarity measure in adaptive geodesic neighbourhoods this paper introduces a novel image dependent filtering approach derived from concepts known in mathematical morphology and aiming at edge preserving smoothing of natural images like other adaptive methods it assumes that the neighbourhood of a pixel contains the essential information required for the estimation of local features in the image the proposed strategy essentially consists in a weighted averaging combining both spatial and tonal information for that purpose a twofold similarity measure is calculated from local geodesic time functions this way no prior operator definition is required since a weighting neighbourhood and a weighting kernel are determined automatically from the unfiltered input data for each pixel location by designing relevant geodesic masks two adaptive filtering algorithms are derived that are particularly efficient at smoothing heterogeneous areas while preserving relevant structures in greyscale and multichannel images

regularity and strict identifiability in mimo systems we study finite impulse response fir multi input multi output mimo systems with additive noise treating the finite length sources and channel coefficients as deterministic unknowns considering both regularity and identifiability in blind estimation the ambiguity set is large admitting linear combinations of the sources we show that the fisher information matrix fim is always rank deficient by at least the number of sources squared and develop necessary and sufficient conditions for the fim to achieve its minimum nullity tight bounds are given on the required source data lengths to achieve minimum nullity of the fim we consider combinations of constraints that lead to regularity i e to a full rank fim and thus a meaningful cramer rao bound exploiting the null space of the fim we show how parameters must be specified to obtain a full rank fim with implications for training sequence design in multisource systems together with constrained cramer rao bounds crbs this approach provides practical techniques for obtaining appropriate mimo crbs for many cases necessary and sufficient conditions are also developed for strict identifiability id the conditions for strict id are shown to be nearly equivalent to those for the fim nullity to be minimized

on the boundary conditions of the geometrically nonlinear kirchhoff love shell theory abstract the present paper addresses the problem of establishing the boundary conditions of a geometrically nonlinear thin shell model especially the kinematic ones our model is consistently derived from general 3d continuum mechanics statements generalized cross sectional strains and stresses are based on the deformation gradient and the first piola kirchhoff stress tensor since only the bending deformation is included in this model no special technique needs to be adopted in order to avoid shear locking the theory is derived in such a way that any material model can be considered as a constitutive relation once the zero transverse normal stress assumption is properly taken into account special attention is given to the question of devising the appropriate shell boundary conditions several parameters are proposed to characterize the boundary rotation for an arbitrary spatial shell configuration the appearance of corner concentrated forces related to jumps of torsion moments is captured and justified a weak form of the equilibrium is presented which is suitable for implementation by means of any numerical technique that provides c 1 continuity approximation it is prone to be used with both interpolative like the finite element method and non interpolative methods like the element free galerkin method the latter is used to exemplify the proposed approach

multistep linear predictors based blind identification and equalization of multiple input multiple output channels channel estimation and blind equalization of multiple input multiple output mimo communications channels is considered using primarily the second order statistics of the data such models arise when single receiver data from multiple sources is fractionally sampled assuming that there is excess bandwidth or when an antenna array is used with or without fractional sampling we consider the estimation of partial channel impulse response and design of finite length minimum mean square error mmse blind equalizers we extend the multistep linear prediction approach to mimo channels where the multichannel transfer function need not be column reduced moreover we allow infinite impulse response iir channels as well as the case where the subchannel transfer functions have common zeros in the past this approach has been confined to simo finite impulse response fir channels with no common subchannel zeros a related existing approach applicable to mimo channels is restricted to fir column reduced systems with equal length subchannels in our approach the knowledge of the nature of the underlying model fir or iir or the model order is not required our approach works when the subchannel transfer functions have common zeros as long as the common zeros are minimum phase zeros the sources are recovered up to a unitary mixing matrix and are further unmixed using higher order statistics of the data illustrative computer simulation examples are provided

deterministic linear prediction methods for blind channel estimation based on dual concept of zero forcing equalization this paper investigates a class of second order blind channel estimation algorithms based on deterministic linear prediction which includes double sided as well as forward and backward single sided for single input multiple output simo finite impulse response fir channels by introducing the dual problem of well known zero forcing equalization concept we first derive a double sided deterministic linear prediction d dlp algorithm that has good channel estimation performance with the knowledge of exact channel order by further exploiting the interference subspace cancellation technique and the triangular block toeplitz structure of a portion of the channel filtering matrix upper left or lower right part we obtain the forward and backward single sided deterministic linear prediction fs dlp and bs dlp algorithms that can work in the absence of knowledge of channel order with a cost of relatively poor channel estimate moreover a channel order estimation method is also studied based on results from both fs dlp and bs dlp simulation examples are finally presented to demonstrate the potential of the proposed methods

generalization of the c1 tuba plate finite elements to the geometrically exact kirchhoff love shell model abstract the finite element implementation of a geometrically exact thin shell model is reported in the present paper the shell kinematics is based on the kirchhoff love assumption and is characterized by the deformation gradient which yielded the generalized cross section strain measures stretches and curvatures written in terms of first and second order derivatives of displacements the energetically conjugate quantity the first piola kirchhoff stress tensor is used to define the generalized stresses the shell s initial geometry is exactly represented using a mapping from a reference configuration a neo hookean material functional supplemented by the plane stress condition is incorporated in the constitutive level of the model both configuration dependent and independent forces are considered for the domain and boundary loading the consistent linearization of the rendered weak form is addressed the tuba family of plate finite elements is adopted for the discretization of the displacement vector field these triangular elements with necessarily straight sides in the reference configuration provide c 1 continuous approximations a sine qua non property for a consistent discretization of the kirchhoff love model the family contains 3 pairs of elements primary and reduced which provide polynomial approximants of degrees k 5 6 and 7 respectively the reduced elements have a simpler structure and a smaller number of nodes but still guarantee c 1 continuity the boundary normal derivative of the approximation in these elements is constrained such that its order is reduced by one unit from k 1 at the primary elements to k 2 due to complexity of the elements degrees of freedom which are the function value its normal first and second order derivatives the imposition of the essential boundary conditions requires some preliminary analysis of the boundary behavior such study is presented for the most common practical cases six benchmark examples are presented to demonstrate the model usefulness and efficiency

residual coding in document image compression symbolic document image compression relies on the detection of similar patterns in a document image and construction of a prototype library compression is achieved by referencing multiple pattern instances components through a single representative prototype to provide a lossless compression however the residual difference between each component and its assigned prototype must be coded since the size of the residual can significantly affect the compression ratio efficient coding is essential we describe a set of residual coding models for use with symbolic document image compression that exhibit desirable characteristics for compression and rate distortion and facilitate compressed domain processing the first model orders the residual pixels by their distance to the prototype edge grouping pixels based on this distance value allows for a more compact coding and lower entropy this distance model is then extended to a model that defines the structure of the residue and uses it as a basis for continuous and packet reconstruction which provides desired functionality for use in lossy compression and progressive transmission

maximum likelihood methods for direction of arrival estimation five methods of direction of arrival doa estimation which can be derived from the maximum likelihood ml principle are considered the ml method mlm results from the application of the ml principle to the statistics of the observed raw data the standard multiple signal classification music procedure called music 1 is obtained as a brute force approximation of the mlm an improved music procedure named music 2 is obtained by applying the ml principle to the statistics of certain linear combinations of the sample noise space eigenvectors a procedure which compromises between the good performance of the mlm and the computational simplicity of music is a method of direction estimation mode 1 which is derived as a large sample realization of the mlm a fifth method called mode 2 is obtained by using the ml principle on the statistics of certain linear combinations of the sample eigenvectors mode 2 is computationally less demanding than the mlm it is of the same complexity as mode 1 and statistically more efficient a numerical comparison of these five doa estimation methods is presented it confirms the analytic results on their theoretical performance levels

nonparametric maximum likelihood estimation by the method of sieves maximum likelihood estimation often fails when the parameter takes values in an infinite dimensional space for example the maximum likelihood method cannot be applied to the completely nonparametric estimation of a density function from an operatorname iid sample the maximum of the likelihood is not attained by any density in this example as in many other examples the parameter space positive functions with area one is too big but the likelihood method can often be salvaged if we first maximize over a constrained subspace of the parameter space and then relax the constraint as the sample size grows this is grenander s method of sieves application of the method sometimes leads to new estimators for familiar problems or to a new motivation for an already well studied technique we will establish some general consistency results for the method and then we will focus on three applications

cross relation based blind simo identifiability in the presence of near common zeros and noise the blind identification of single input multiple output simo systems is often performed by exploiting a cross relation cr between channel pairs it has been shown that this property allows an estimation of channel impulse responses up to a common gain factor if certain identifiability conditions are met in this case the estimated channels can be evaluated by a gain compensated system distance known as normalized projection misalignment npm current algorithms for blind channel identification however suffer in the presence of insufficient channel diversity and observation noise in this paper we first demonstrate that in the absence of noise the cr identification error for channels with exact common zeros is given by a single channel pole zero transfer function next we extend our analysis to the realistic case of near common zeros and noise for which we show that the effective error can still be approximated by a common transfer function as long as the distance between the channel zeros remains below a signal to noise ratio dependent threshold a finite impulse response fir modeling of the error then enables us to define a common filter error compensated system distance termed normalized filter projection misalignment nfpm which establishes a natural extension to the npm analysis by finally considering realistic channels which we blindly estimate with the adaptive multichannel least mean square mclms algorithm we demonstrate that the nfpm reliably reaches the noise floor confirming that the effective error can be approximated by a common fir filter

an efficient uniform cost algorithm applied to distance transforms the uniform cost algorithm is a special case of the a algorithm for finding the shortest paths in graphs in the uniform cost algorithm nodes are expanded in order of increasing cost an efficient version of this algorithm is developed for integer cost values nodes are sorted by storing them at predefined places bucket sort keeping the overhead low the algorithm is applied to general distance transformation a constrained distance transform is an operation which calculates at each pixel of an image the distance to the nearest pixel of a reference set distance being defined as minimum path length the uniform cost algorithm in the constrained case proves to be the best solution for distance transformation it is fast the processing time is independent of the complexity of the image and memory requirements are moderate

a blind approach to closed loop identification of hammerstein systems this paper is a continuing study of the blind approach for the hammerstein identification in sun et al 1999 and bai and fu 2002 in the framework of a closed loop sampled data system the output is sampled faster than the updating period of the input the parameters of the linear dynamics are consistently estimated from the information of the output only after which the unmeasurable inner signal is uniquely reconstructed the noise effect is explicitly considered in both the parameter and inner signal estimation the estimation of the system orders and time delay are studied on the basis of two groups of basic equations obtained by polyphase decomposition the proposed blind approach is validated and illustrated by a simulated numerical example

shell curvature as an initial deformation a geometrically exact finite element approach an alternative approach for the analysis of arbitrarily curved shells is developed in this paper based on the idea of initial deformations by alternative we mean that neither differential geometry nor the concept of degeneration is invoked here to describe the shell surface we begin with a flat reference configuration for the shell mid surface after which the initial curved geometry is mapped as a stress free deformation from the plane position the actual motion of the shell takes place only after this initial mapping in contrast to classical works in the literature this strategy enables the use of only orthogonal frames within the theory and therefore objects such as christoffel symbols the second fundamental form or three dimensional degenerated solids do not enter the formulation furthermore the issue of physical components of tensors does not appear another important aspect but not exclusive of our scheme is the possibility to describe exactly the initial geometry the model is kinematically exact encompasses finite strains in a totally consistent manner and is here discretized under the light of the finite element method although implementation via mesh free techniques is also possible assessment is made by means of several numerical simulations copyright 2009 john wiley sons ltd

stress resultant plasticity for shells revisited in this work we revisit the stress resultant elastoplastic geometrically exact shell finite element formulation that is based on the ilyushin shapiro two surface yield function with isotropic and kinematic hardening the main focus is on implicit projection algorithms for computation of updated values of internal variables for stress resultant shell elastoplasticity four different algorithms are derived and compared three of them yield practically identical final results yet they differ considerably in computational efficiency and implementation complexity since they solve different sets of equations and they use different procedures that choose active yield surfaces one algorithm does not provide acceptable accuracy it turns out that the most simple and straightforward algorithm performs surprisingly well and efficiently several numerical examples are presented to illustrate the ilyushin shapiro stress resultant shell formulation and the numerical performance of the presented integration algorithms