approximate controllability of impulsive differential equations with state dependent delay in order to describe various real world problems in physical and engineering sciences subject to abrupt changes at certain instants during the evolution process impulsive differential equations have been used to describe the system model in this article the problem of approximate controllability for nonlinear impulsive differential equations with state dependent delay is investigated we study the approximate controllability for nonlinear impulsive differential system under the assumption that the corresponding linear control system is approximately controllable using methods of functional analysis and semigroup theory sufficient conditions are formulated and proved finally an example is provided to illustrate the proposed theory

controllability of nonlinear integro differential third order dispersion system in this short article sufficient condition for controllability of nonlinear dispersion system is studied the result is obtained by using the schaefer fixed point theorem this work extends the work of chalishajar george and nandakumaran d n chalishajar r k george a k nandakumaran exact controllability of the third order nonlinear dispersion equation j math anal appl 332 2007 1028 1044 usually authors assume the compactness of semigroup while studying the controllability here we drop this assumption and prove the controllability result

quantization of harmonic amplitudes representing speech in a speech coding and decoding system in which a timewise segment of an acoustic speech signal is represented by a frame of a data signal characterized by a fundamental frequency and spectral harmonics a current frame is reconstructed using a set of prediction signals based on the number of spectral harmonics for the current frame and a preceding frame and reconstructed signal parameters characterizing the preceding frame the number of spectral harmonics for the current and preceding frames are reconstructed from at least a pair of digitally encoded signals that are generated using error protection codes for all of their bits

scene segmentation from visual motion using global optimization this paper presents results from computer experiments with an algorithm to perform scene disposition and motion segmentation from visual motion or optic flow the maximum a posteriori map criterion is used to formulate what the best segmentation or interpretation of the scene should be where the scene is assumed to be made up of some fixed number of moving planar surface patches the bayesian approach requires first specification of prior expectations for the optic flow field which here is modeled as spatial and temporal markov random fields and secondly a way of measuring how well the segmentation predicts the measured flow field the markov random fields incorporate the physical constraints that objects and their images are probably spatially continuous and that their images are likely to move quite smoothly across the image plane to compute the flow predicted by the segmentation a recent method for reconstructing the motion and orientation of planar surface facets is used the search for the globally optimal segmentation is performed using simulated annealing

robust optic flow computation this paper formulates the optic flow problem as a set of over determined simultaneous linear equations it then introduces and studies two new robust optic flow methods the first technique is based on using the least median of squares lmeds to detect the outliers then the inlier group is solved using the least square technique the second method employs a new robust statistical method named the least median of squares orthogonal distances lmsod to identify the outliers and then uses total least squares to solve the optic flow problem the performance of both methods are studied by experiments on synthetic and real image sequences these methods outperform other published methods both in accuracy and robustness

existence of nondensely defined evolution equations with nonlocal conditions abstract this paper is concerned with the existence for nondensely defined evolution equations with nonlocal conditions using the techniques of fixed point theory and approximate solutions existence results are obtained for integral solutions when the nonlocal item is lipschitz continuous or continuous respectively examples are also given to illustrate our results

approximate controllability of fractional nonlinear differential inclusions fractional differential equations have wide applications in both physical and social sciences this paper addresses the issue of approximate controllability for a class of fractional nonlinear differential inclusions in banach spaces a new set of sufficient conditions are formulated and proved for the approximate controllability of fractional nonlinear differential inclusions in particular the results are established with the assumption that the associated linear part of system is approximately controllable further the result is extended to obtain the conditions for the solvability of controllability results for fractional inclusions with nonlocal conditions finally an example is presented to illustrate the theory of the obtained result

a unified existence theory for evolution equations and systems under nonlocal conditions abstract we investigate the effect of nonlocal conditions expressed by linear continuous mappings over the hypotheses which guarantee the existence of global mild solutions for functional differential equations in a banach space a progressive transition from the volterra integral operator associated to the cauchy problem to fredholm type operators appears when the support of the nonlocal condition increases from zero to the entire interval of the problem the results are extended to systems of equations in a such way that the system nonlinearities behave independently as much as possible and the support of the nonlocal condition may differ from one variable to another

on the approximate controllability of fractional evolution equations with compact analytic semigroup in this paper we discuss the approximate controllability of fractional evolution equations involving caputo fractional derivative the results are obtained with the help of the theory of fractional calculus semigroup theory and the schauder s fixed point theorem under the assumption that the corresponding linear system is approximately controllable finally an example is provided to illustrate the obtained results

global existence for semilinear evolution equations with nonlocal conditions abstract in this paper we study the global existence of solutions for semilinear evolution equations with nonlocal conditions via a fixed point analysis approach using the leray schauder alternative we derive conditions under which a solution exists globally

bayesian estimation of motion vector fields a stochastic approach to the estimation of 2d motion vector fields from time varying images is presented the formulation involves the specification of a deterministic structural model along with stochastic observation and motion field models two motion models are proposed a globally smooth model based on vector markov random fields and a piecewise smooth model derived from coupled vector binary markov random fields two estimation criteria are studied in the maximum a posteriori probability map estimation the a posteriori probability of motion given data is maximized whereas in the minimum expected cost mec estimation the expectation of a certain cost function is minimized both algorithms generate sample fields by means of stochastic relaxation implemented via the gibbs sampler two versions are developed one for a discrete state space and the other for a continuous state space the map estimation is incorporated into a hierarchical environment to deal efficiently with large displacements

methods for speech quantization and error correction the redundancy contained within the spectral amplitudes is reduced and as a result the quantization of the spectral amplitudes is improved the prediction of the spectral amplitudes of the current segment from the spectral amplitudes of the previous is adjusted to account for any change in the fundamental frequency between the two segments the spectral amplitudes prediction residuals are divided into a fixed number of blocks each containing approximately the same number of elements a prediction residual block average prba vector is formed each element of the prba is equal to the average of the prediction residuals within one of the blocks the prba vector is vector quantized or it is transformed with a discrete cosine transform dct and scalar quantized the perceived effect of bit errors is reduced by smoothing the voiced unvoiced decisions an estimate of the error rate is made by locally averaging the number of correctable bit errors within each segment if the estimate of the error rate is greater than a threshold then high energy spectral amplitudes are declared voiced

existence of solutions for nonlocal impulsive partial functional integrodifferential equations via fractional operators in this paper by using the leray schauder alternative we have investigated the existence of mild solutions to first order impulsive partial functional integrodifferential equations with nonlocal conditions in an a norm we assume that the linear part generates an analytic compact bounded semigroup and that the nonlinear part is a lipschitz continuous function with respect to the fractional power norm of the linear part an example is also given to illustrate our main results

estimation of occlusion and dense motion fields in a bidirectional bayesian framework this paper presents new mrf markov random field models in a bidirectional bayesian framework for accurate motion and occlusion field estimation with careful selection of the five free parameters required by the models good experimental results have been obtained the resultant computational speed is also 5 5 times faster compared with the conventional iterated conditional mode relaxation using the proposed fast bidirectional relaxation

existence results for systems with coupled nonlocal initial conditions abstract in this paper an existence theory is developed for first order differential systems with coupled nonlocal conditions given by stieltjes integrals the approach is based on the fixed point theorems of perov schauder and schaefer and on a vector method for treating systems which uses matrices having spectral radius less than one when the nonlocal conditions depend on functionals restricted to a proper subinterval the nonlinear integral operator associated to the system splits into two parts one of fredholm type and another one of volterra type correspondingly the sufficient conditions for the existence results will differ in the two parts of the interval some examples are presented to illustrate the theory

dense estimation and object based segmentation of the optical flow with robust techniques we address the issue of recovering and segmenting the apparent velocity field in sequences of images as for motion estimation we minimize an objective function involving two robust terms the first one cautiously captures the optical flow constraint while the second a priori term incorporates a discontinuity preserving smoothness constraint to cope with the nonconvex minimization problem thus defined we design an efficient deterministic multigrid procedure it converges fast toward estimates of good quality while revealing the large discontinuity structures of flow fields we then propose an extension of the model by attaching to it a flexible object based segmentation device based on deformable closed curves different families of curve equipped with different kinds of prior can be easily supported experimental results on synthetic and natural sequences are presented including an analysis of sensitivity to parameter tuning

robust reweighted map motion estimation this paper proposes a motion estimation algorithm that is robust to motion discontinuity and noise the proposed algorithm is constructed by embedding the least median squares lmeds of robust statistics into the maximum a posteriori map estimator difficulties in accurate estimation of the motion field arise from the smoothness constraint and the sensitivity to noise to cope robustly with these problems a median operator and the concept of reweighted least squares rls are applied to the map motion estimator resulting in the reweighted robust map rrmap the proposed rrmap motion estimation algorithm is also generalized for multiple image frame cases computer simulation with various synthetic image sequences shows that the proposed algorithm reduces errors compared to three existing robust motion estimation algorithms that are based on m estimation total least squares tls and hough transform it is also observed that the proposed algorithm is statistically efficient and robust to additive gaussian noise and impulse noise furthermore the proposed algorithm yields reasonable performance for real image sequences

phase information and space filling curves in noisy motion estimation this correspondence presents a novel approach for translational motion estimation based on the phase of the fourier transform it exploits the equality between the averaging of a group of successive frames and the convolution of the reference one with an impulse train function the use of suitable space filling curves allows to reduce the error in motion estimation making the proposed approach robust under noise experimental results show that the proposed approach outperforms available techniques in terms of objective psnr and subjective quality with a lower computational effort

a region based selective optical flow back projection for genuine motion vector estimation motion vector plays one significant feature in moving object segmentation however the motion vector in this application is required to represent the actual motion displacement rather than regions of visually significant similarity in this paper region based selective optical flow back projection rsofb which back projects optical flows in a region to restore the region s motion vector from gradient based optical flows is proposed to obtain genuine motion displacement the back projection is performed based on minimizing the projection mean square errors of the motion vector on gradient directions as optical flows of various magnitudes and directions provide various degrees of reliability in the genuine motion restoration the optical flows to be used in the rsofb are optimally selected based on their sensitivity to noises and their tendency in causing motion estimation errors in this paper a deterministic solution is also derived for performing the minimization and obtaining the genuine motion magnitude and motion direction

fast approximate energy minimization via graph cuts many tasks in computer vision involve assigning a label such as disparity to every pixel a common constraint is that the labels should vary smoothly almost everywhere while preserving sharp discontinuities that may exist e g at object boundaries these tasks are naturally stated in terms of energy minimization the authors consider a wide class of energies with various smoothness constraints global minimization of these energy functions is np hard even in the simplest discontinuity preserving case therefore our focus is on efficient approximation algorithms we present two algorithms based on graph cuts that efficiently find a local minimum with respect to two types of large moves namely expansion moves and swap moves these moves can simultaneously change the labels of arbitrarily large sets of pixels in contrast many standard algorithms including simulated annealing use small moves where only one pixel changes its label at a time our expansion algorithm finds a labeling within a known factor of the global minimum while our swap algorithm handles more general energy functions both of these algorithms allow important cases of discontinuity preserving energies we experimentally demonstrate the effectiveness of our approach for image restoration stereo and motion on real data with ground truth we achieve 98 percent accuracy

a note on approximate controllability of semilinear systems abstract for the following distributed parameter semilinear system x ax f x bu naito 5 showed that under suitable hypotheses approximate contrallability is attainable if f x m 1 x for some m 0 and some 0 1 in this paper this condition is simplified to requiring only that lim x f x x 0 in addition a uniform lipschitz continuity assumption on f is replaced by requiring f being locally lipschitz continuous

controllability of neutral functional integrodifferential systems in banach spaces abstract sufficient conditions for controllability of neutral functional integrodifferential systems in a banach space are established the results are obtained by using the schaefer fixed point theorem an example is provided to illustrate the theory

controllability of functional semilinear integrodifferential systems in banach spaces sufficient conditions for controllability of functional semilinear integrodifferential systems in a banach space are established the results are obtained by using the schaefer fixed point theorem

a study on controllability of semilinear integrodiferential systems in banach spaces abstract sufficient conditions for controllability of semilinear integrodifferential systems in a banach space are established the results are obtained by using the semigroup theory and the schaefer fixed point theorem an example is provided to illustrate the theory

image flow segmentation and estimation by constraint line clustering image flow is the velocity field in the image plane caused by the motion of the observer objects in the scene or apparent motion and can contain discontinuities due to object occlusion in the scene an algorithm that can estimate the image flow velocity field when there are discontinuities due to occlusions is described the constraint line clustering algorithm uses a statistical test to estimate the image flow velocity field in the presence of step discontinuities in the image irradiance or velocity field particular emphasis is placed on motion estimation and segmentation in situations such as random dot patterns where motion is the only cue to segmentation experimental results on a demanding synthetic test case and a real image are presented a smoothing algorithm for improving the velocity field estimate is also described the smoothing algorithm constructs a smooth estimate of the velocity field by approximating a surface between step discontinuities it is noted that the velocity field estimate can be improved using surface reconstruction between velocity field boundaries

nonlocal nonlinear differential equations with a measure of noncompactness in banach spaces abstract in this paper we give the existence of integral solutions for nonlinear differential equations with nonlocal initial conditions under the assumptions of the hausdorff measure of noncompactness in separable and uniformly smooth banach spaces

existence of solutions of nonlinear differential equations with nonlocal conditions in this paper we investigate the existence of mild solutions to first order semilinear differential equations in banach spaces with nonlocal conditions we shall rely on a fixed point theorem for compact maps due to schaefer

approximate controllability for a class of semilinear abstract equations in this paper a class of control systems governed by the semilinear abstract equation dot y ay f y bv is considered a sufficient condition for the approximate controllability is obtained which improves j henry s results on a nonlinear parabolic control systems with some more serious restrictions it is suitable not only to the infinite dimensional case but also to the finite dimensional case two examples are given to explain the applications of the theory

method for modeling speech harmonic magnitudes a system or method for modeling a signal such as a speech signal wherein harmonic frequencies and amplitudes are identified 106 and the harmonic magnitudes are interpolated 110 to obtain spectral magnitudes at a set of fixed frequencies an inverse transform is applied 112 to the spectral magnitudes to obtain a pseudo auto correlation sequence from which linear prediction coefficients are calculated 114 from the linear prediction coefficients model harmonic magnitudes are generated by sampling the spectral envelope 118 defined by the linear prediction coefficients a set of scale factors are then calculated 120 as the ratio of the harmonic magnitudes to the model harmonic magnitudes and interpolated to obtain a second set of scale factors 122 at the set of fixed frequencies the spectral envelope magnitudes at the set of fixed frequencies 124 are multiplied by the second set of scale factors 126 to obtain new spectral magnitudes and the process is iterated to obtain final linear prediction coefficients

estimating piecewise smooth optical flow with global matching and graduated optimization this paper presents a new method for estimating piecewise smooth optical flow we propose a global optimization formulation with three frame matching and local variation and develop an efficient technique to minimize the resultant global energy this technique takes advantage of local gradient global gradient and global matching methods and alleviates their limitations experiments on various synthetic and real data show that this method achieves highly competitive accuracy

robust optical flow computation based on least median of squares regression an optical flow estimation technique is presented which is based on the least median of squares lmeds robust regression algorithm enabling more accurate flow estimates to be computed in the vicinity of motion discontinuities the flow is computed in a blockwise fashion using an affine model through the use of overlapping blocks coupled with a block shifting strategy redundancy is introduced into the computation of the flow this eliminates blocking effects common in most other techniques based on blockwise processing and also allows flow to be accurately computed in regions containing three distinct motions a multiresolution version of the technique is also presented again based on lmeds regression which enables image sequences containing large motions to be effectively handled an extensive set of quantitative comparisons with a wide range of previously published methods are carried out using synthetic realistic computer generated images of natural scenes with known flow and natural images both angular and absolute flow errors are calculated for those sequences with known optical flow displaced frame difference error used extensively in video compression is used for those natural scenes with unknown flow in all of the sequences tested a comparison with those methods that result in a dense flow field greater than 80 spatial coverage show that the lmeds technique produces the least error irrespective of the error measure used

controllability of sobolev type integrodifferential systems in banach spaces sufficient conditions for controllability of sobolev type integrodifferential systems in banach spaces are established the results are obtained using compact semigroups and the schauder fixed point theorem as an example is provided to illustrate the results

computation of component image velocity from local phase information we present a technique for the computation of 2d component velocity from image sequences initially the image sequence is represented by a family of spatiotemporal velocity tuned linear filters component velocity computed from spatiotemporal responses of identically tuned filters is expressed in terms of the local first order behavior of surfaces of constant phase justification for this definition is discussed from the perspectives of both 2d image translation and deviations from translation that are typical in perspective projections of 3d scenes the resulting technique is predominantly linear efficient and suitable for parallel processing moreover it is local in space time robust with respect to noise and permits multiple estimates within a single neighborhood promising quantiative results are reported from experiments with realistic image sequences including cases with sizeable perspective deformation

existence results of semilinear differential equations with nonlocal initial conditions in banach spaces abstract in this paper we establish the existence results for semilinear differential systems with nonlocal initial conditions in banach spaces the approaches used are fixed point theorems combined with convex power condensing operators the first result obtained will be applied to a class of semilinear parabolic equations

multimodal estimation of discontinuous optical flow using markov random fields the estimation of dense velocity fields from image sequences is basically an ill posed problem primarily because the data only partially constrain the solution it is rendered especially difficult by the presence of motion boundaries and occlusion regions which are not taken into account by standard regularization approaches in this paper the authors present a multimodal approach to the problem of motion estimation in which the computation of visual motion is based on several complementary constraints it is shown that multiple constraints can provide more accurate flow estimation in a wide range of circumstances the theoretical framework relies on bayesian estimation associated with global statistical models namely markov random fields the constraints introduced here aim to address the following issues optical flow estimation while preserving motion boundaries processing of occlusion regions fusion between gradient and feature based motion constraint equations deterministic relaxation algorithms are used to merge information and to provide a solution to the maximum a posteriori estimation of the unknown dense motion field the algorithm is well suited to a multiresolution implementation which brings an appreciable speed up as well as a significant improvement of estimation when large displacements are present in the scene experiments on synthetic and real world image sequences are reported

on abstract differential equations with state dependent non local conditions abstract in this paper we introduce the concept of state dependent nonlocal condition and study the existence and uniqueness of solution for a general class of abstract differential equations with state dependent delay subject to this class of conditions in this type of problem the nonlocal condition can be dependent on times or time intervals determined by the unknown solution some examples on partial differential equations with state dependent delay arising in population dynamics are presented

controllability of semilinear control systems dominated by the linear part while various equivalent conditions for controllability have been obtained in the case of linear control systems controllability problems of semilinear control systems usually require some complicated and limited assumptions in this paper we show the approximate controllability of an abstract semilinear control system under the assumption which has a simple form and can be easily checked in many examples