perceptual video coding based on ssim inspired divisive normalization we propose a perceptual video coding framework based on the divisive normalization scheme which is found to be an effective approach to model the perceptual sensitivity of biological vision but has not been fully exploited in the context of video coding at the macroblock mb level we derive the normalization factors based on the structural similarity ssim index as an attempt to transform the discrete cosine transform domain frame residuals to a perceptually uniform space we further develop an mb level perceptual mode selection scheme and a frame level global quantization matrix optimization method extensive simulations and subjective tests verify that compared with the h 264 avc video coding standard the proposed method can achieve significant gain in terms of rate ssim performance and provide better visual quality

on monotonicity preserving stabilized finite element approximations of transport problems the aim of this work is to design monotonicity preserving stabilized finite element techniques for transport problems as a blend of linear and nonlinear shock capturing stabilization as linear stabilization we consider and analyze a novel symmetric projection stabilization technique based on a local scott zhang projector next we design a weighting of the aforementioned linear stabilization such that when combined with a finite element discretization enjoying a discrete maximum principle usually attained via nonlinear stabilization it does not spoil these monotonicity properties then we propose novel nonlinear stabilization schemes in the form of an artificial viscosity method where the amount of viscosity is proportional to gradient jumps at either finite element boundaries or nodes for the nodal scheme we prove a discrete maximum principle for time dependent multidimensional transport problems numerical experiments support the numerical analysis and we show that the resulting methods prov

nonlinear image representation for efficient perceptual coding image compression systems commonly operate by transforming the input signal into a new representation whose elements are independently quantized the success of such a system depends on two properties of the representation first the coding rate is minimized only if the elements of the representation are statistically independent second the perceived coding distortion is minimized only if the errors in a reconstructed image arising from quantization of the different elements of the representation are perceptually independent we argue that linear transforms cannot achieve either of these goals and propose instead an adaptive nonlinear image representation in which each coefficient of a linear transform is divided by a weighted sum of coefficient amplitudes in a generalized neighborhood we then show that the divisive operation greatly reduces both the statistical and the perceptual redundancy amongst representation elements we develop an efficient method of inverting this transformation and we demonstrate through simulations that the dual reduction in dependency can greatly improve the visual quality of compressed images

linear transform for simultaneous diagonalization of covariance and perceptual metric matrix in image coding two types ofredundancies are contained in images statistical redundancy and psychovisual redundancy image representation techniques for image coding should remove both redundancies in order to obtain good results in order to establish an appropriate representation the standard approach to transform coding only considers the statistical redundancy whereas the psychovisual factors are introduced after the selection ofthe representation as a simple scalar weighting in the transform domain in this work we take into account the psychovisual factors in the de8nition of the representation together with the statistical factors by means of the perceptual metric and the covariance matrix respectively in general the ellipsoids described by these matrices are not aligned therefore the optimal basis for image representation should simultaneously diagonalize both matrices this approach to the basis selection problem has several advantages in the particular application ofimage coding as the transform domain is euclidean by de8nition the quantizer design is highly simpli8ed and at the same time the use ofscalar quantizers is truly justi8ed the proposed representation is compared to covariance based representations such as the dct and the klt or pca using standard jpeg like and max lloyd quantizers 2003 pattern recognition society published by elsevier science ltd all rights reserved

on the design of general purpose flux limiters for finite element schemes i scalar convection the algebraic flux correction afc paradigm is extended to finite element discretizations with a consistent mass matrix it is shown how to render an implicit galerkin scheme positivity preserving and remove excessive artificial diffusion in regions where the solution is sufficiently smooth to this end the original discrete operators are modified in a mass conserving fashion so as to enforce the algebraic constraints to be satisfied by the numerical solution a node oriented limiting strategy is employed to control the raw antidiffusive fluxes which consist of a convective part and a contribution of the consistent mass matrix the former offsets the artificial diffusion due to upwinding of the spatial differential operator and lends itself to an upwind biased flux limiting the latter eliminates the error induced by mass lumping and calls for the use of a symmetric flux limiter the concept of a target flux and a new definition of upper lower bounds make it possible to combine the advantages of algebraic fct and tvd schemes introduced previously by the author and his coworkers unlike other high resolution schemes for unstructured meshes the new algorithm reduces to a consistent high order galerkin scheme in smooth regions and is designed to provide an optimal treatment of both stationary and time dependent problems its performance is illustrated by application to the linear advection equation for a number of 1d and 2d configurations

variational multiscale element free galerkin vmefg and local discontinuous galerkin ldg methods for solving two dimensional brusselator reaction diffusion system with and without cross diffusion abstract the finite element method fem is one of the basic methods for solving deterministic and stochastic partial differential equations this method is proposed in the 19 decade and after years several modifications for this well known technique such as mortal fem discontinuous galerkin fem extended fem least squares fem spectral fem mixed fem immersed fem adaptive fem etc have been proposed also for improving the accuracy and for considering complex domain shape functions of the moving least squares approximation have been replaced with the traditional shape function of the finite element technique the name of this improved method is element free galerkin efg method which is classified in the category of meshless methods the efg method has been applied for solving many problems in engineering in the current paper we select two numerical procedures that are extracted from fem the discontinuous galerkin approach is a useful technique for solving problems that their exact solutions have discontinuity it should be noted that many enriched ideas have been explained for improving accuracy of efg method in the current paper the local discontinuous galerkin and variational multiscale efg methods are applied for obtaining numerical solution of two dimensional brusselator system with and without cross diffusion the brusselator system is a theoretical model for a type of autocatalytic reaction up to best of authors knowledge the accuracy of the obtained numerical solutions using local discontinuous galerkin method is very related to the used time discrete scheme therefore fourth order exponential time differencing method has been employed for discretizing the time variable also to achieve a full discretization scheme the local discontinuous galerkin finite element method is used moreover several test problems are given that show the acceptable accuracy and efficiency of the proposed schemes

efficient quadtree coding of images and video the quadtree data structure is commonly used in image coding to decompose an image into separate spatial regions to adaptively identify the type of quantizer used in various regions of an image the authors describe the theory needed to construct quadtree data structures that optimally allocate rate given a set of quantizers a lagrange multiplier method finds these optimal rate allocations with no monotonicity restrictions they use the theory to derive a new quadtree construction method that uses a stepwise search to find the overall optimal quadtree structure the search can be driven with either actual measured quantizer performance or ensemble average predicted performance they apply this theory to the design of a motion compensated interframe video coding system using a quadtree with vector quantization

joint optimization of block size and quantization for quadtree based motion estimation a new approach to finding the best block size for quadtree based motion estimation is developed and compared to a conventional fixed block size algorithm the optimal balance between the motion vector bits and the discrete cosine transform dct coefficient bits is achieved by a fast tree optimization technique based on lagrange multiplier

perceptual feedback in multigrid motion estimation using an improved dct quantization in this paper a multigrid motion compensation video coder based on the current human visual system hvs contrast discrimination models is proposed a novel procedure for the encoding of the prediction errors has been used this procedure restricts the maximum perceptual distortion in each transform coefficient this subjective redundancy removal procedure includes the amplitude nonlinearities and some temporal features of human perception a perceptually weighted control of the adaptive motion estimation algorithm has also been derived from this model perceptual feedback in motion estimation ensures a perceptual balance between the motion estimation effort and the redundancy removal process the results show that this feedback induces a scale dependent refinement strategy that gives rise to more robust and meaningful motion estimation which may facilitate higher level sequence interpretation perceptually meaningful distortion measures and the reconstructed frames show the subjective improvements of the proposed scheme versus an h 263 scheme with unweighted motion estimation and mpeg like quantization

differentiable monotonicity preserving schemes for discontinuous galerkin methods on arbitrary meshes this work is devoted to the design of interior penalty discontinuous galerkin dg schemes that preserve maximum principles at the discrete level for the steady transport and convection diffusion problems and the respective transient problems with implicit time integration monotonic schemes that combine explicit time stepping with dg space discretization are very common but the design of such schemes for implicit time stepping is rare and it had only been attained so far for 1d problems the proposed scheme is based on a piecewise linear dg discretization supplemented with an artificial diffusion that linearly depends on a shock detector that identifies the troublesome areas in order to define the new shock detector we have introduced the concept of discrete local extrema the diffusion operator is a graph laplacian instead of the more common finite element discretization of the laplacian operator which is essential to keep monotonicity on general meshes and in multi dimension the resulting nonlinear stabilization is non smooth and nonlinear solvers can fail to converge as a result we propose a smoothed twice differentiable version of the nonlinear stabilization which allows us to use newton with line search nonlinear solvers and dramatically improve nonlinear convergence a theoretical numerical analysis of the proposed schemes shows that they satisfy the desired monotonicity properties further the resulting operator is lipschitz continuous and there exists at least one solution of the discrete problem even in the non smooth version we provide a set of numerical results to support our findings

an extension of multiple correspondence analysis for identifying heterogeneous subgroups of respondents an extension of multiple correspondence analysis is proposed that takes into account cluster level heterogeneity in respondents preferences choices the method involves combining multiple correspondence analysis and k means in a unified framework the former is used for uncovering a low dimensional space of multivariate categorical variables while the latter is used for identifying relatively homogeneous clusters of respondents the proposed method offers an integrated graphical display that provides information on cluster based structures inherent in multivariate categorical data as well as the interdependencies among the data an empirical application is presented which demonstrates the usefulness of the proposed method and how it compares to several extant approaches

stabilized galerkin approximation of convection diffusion reaction equations discrete maximum principle and convergence we analyze a nonlinear shock capturing scheme for h1 conforming piecewise affine finite element approximations of linear elliptic problems the meshes are assumed to satisfy two standard conditions a local quasi uniformity property and the xu zikatanov condition ensuring that the stiffness matrix associated with the poisson equation is an m matrix a discrete maximum principle is rigorously established in any space dimension for convection diffusion reaction problems we prove that the shock capturing finite element solution converges to that without shock capturing if the cell peclet numbers are sufficiently small moreover in the diffusion dominated regime the difference between the two finite element solutions super converges with respect to the actual approximation error numerical experiments on test problems with stiff layers confirm the sharpness of the a priori error estimates

least squares quantization in pcm it has long been realized that in pulse code modulation pcm with a given ensemble of signals to handle the quantum values should be spaced more closely in the voltage regions where the signal amplitude is more likely to fall it has been shown by panter and dite that in the limit as the number of quanta becomes infinite the asymptotic fractional density of quanta per unit voltage should vary as the one third power of the probability density per unit voltage of signal amplitudes in this paper the corresponding result for any finite number of quanta is derived that is necessary conditions are found that the quanta and associated quantization intervals of an optimum finite quantization scheme must satisfy the optimization criterion used is that the average quantization noise power be a minimum it is shown that the result obtained here goes over into the panter and dite result as the number of quanta become large the optimum quautization schemes for 2 b quanta b 1 2 cdots 7 are given numerically for gaussian and for laplacian distribution of signal amplitudes

context coding of depth map images under the piecewise constant image model representation this paper introduces an efficient method for lossless compression of depth map images using the representation of a depth image in terms of three entities 1 the crack edges 2 the constant depth regions enclosed by them and 3 the depth value over each region the starting representation is identical with that used in a very efficient coder for palette images the piecewise constant image model coding but the techniques used for coding the elements of the representation are more advanced and especially suitable for the type of redundancy present in depth images initially the vertical and horizontal crack edges separating the constant depth regions are transmitted by 2d context coding using optimally pruned context trees both the encoder and decoder can reconstruct the regions of constant depth from the transmitted crack edge image the depth value in a given region is encoded using the depth values of the neighboring regions already encoded exploiting the natural smoothness of the depth variation and the mutual exclusiveness of the values in neighboring regions the encoding method is suitable for lossless compression of depth images obtaining compression of about 10 65 times and additionally can be used as the entropy coding stage for lossy depth compression

optimal pruning with applications to tree structured source coding and modeling an algorithm introduced by l breiman et al 1984 in the context of classification and regression trees is reinterpreted and extended to cover a variety of applications in source coding and modeling in which trees are involved these include variable rate and minimum entropy tree structured vector quantization minimum expected cost decision trees variable order markov modeling optimum bit allocation and computer graphics and image processing using quadtrees a concentration on the first of these and a detailed analysis of variable rate tree structured vector quantization are provided it is found that variable rate tree structured vector quantization outperforms not only the fixed rate variety but also full search vector quantization the successive approximation character of variable rate tree structured vector quantization permits it to degrade gracefully if the rate is reduced at the encoder this has applications to the problem of buffer overflow

on spurious oscillations at layers diminishing sold methods for convection diffusion equations part ii analysis for p1 and q1 finite elements abstract an unwelcome feature of the popular streamline upwind petrov galerkin supg stabilization of convection dominated convection diffusion equations is the presence of spurious oscillations at layers a review and a comparison of the most methods which have been proposed to remove or at least to diminish these oscillations without leading to excessive smearing of the layers are given in part i v john p knobloch on spurious oscillations at layers diminishing sold methods for convection diffusion equations part i a review comput methods appl mech engrg 196 2007 2197 2215 in the present paper the most promising of these sold methods are investigated in more detail for p 1 and q 1 finite elements in particular the dependence of the results on the mesh the data of the problems and parameters of the methods are studied analytically and numerically furthermore the numerical solution of the nonlinear discrete problems is discussed and the capability of adaptively refined grids for reducing spurious oscillations is examined our conclusion is that also for simple problems any of the sold methods generally provides solutions with non negligible spurious oscillations

an optimal quadtree based motion estimation and motion compensated interpolation scheme for video compression we propose an optimal quadtree qt based motion estimator for video compression it is optimal in the sense that for a given bit budget for encoding the displacement vector field dvf and the qt segmentation the scheme finds a dvf and a qt segmentation which minimizes the energy of the resulting displaced frame difference dfd we find the optimal qt decomposition and the optimal dvf jointly using the lagrangian multiplier method and a multilevel dynamic program we introduce a new very fast convex search for the optimal lagrangian multiplier spl lambda which results in a very fast convergence of the lagrangian multiplier method the resulting dvf is spatially inhomogeneous since large blocks are used in areas with simple motion and small blocks in areas with complex motion we also propose a novel motion compensated interpolation scheme which uses the same mathematical tools developed for the qt based motion estimator one of the advantages of this scheme is the globally optimal control of the tradeoff between the interpolation error energy and the dvf smoothness another advantage is that no interpolation of the dvf is required since we directly estimate the dvf and the qt segmentation for the frame which needs to be interpolated we present results with the proposed qt based motion estimator which show that for the same dfd energy the proposed estimator uses about 25 fewer bits than the commonly used block matching algorithm we also experimentally compare the interpolated frames using the proposed motion compensated interpolation scheme with the reconstructed original frames

edge stabilization for galerkin approximations of convection diffusion reaction problems n this paper we recall a stabilization technique for finite element methods for convection diffusion reaction equations originally proposed by j douglas jr and t dupont in computing methods in applied sciences second internat sympos versailles 1975 207 216 lecture notes in phys 58 springer berlin 1976 mr0440955 55 13823 the method uses least square stabilization of the gradient jumps across element boundaries we prove that the method is stable in the hyperbolic limit and prove optimal a priori error estimates we address the question of monotonicity of discrete solutions and present some numerical examples illustrating the theoretical results

quantization based clustering algorithm in this paper a quantization based clustering algorithm qbca is proposed to cluster a large number of data points efficiently unlike previous clustering algorithms qbca places more emphasis on the computation time of the algorithm specifically qbca first assigns the data points to a set of histogram bins by a quantization function then it determines the initial centers of the clusters according to this point distribution finally qbca performs clustering at the histogram bin level rather than the data point level we also propose two approaches to improve the performance of qbca further i a shrinking process is performed on the histogram bins to reduce the number of distance computations and ii a hierarchical structure is constructed to perform efficient indexing on the histogram bins finally we analyze the performance of qbca theoretically and experimentally and show that the approach 1 can be easily implemented 2 identifies the clusters effectively and 3 outperforms most of the current state of the art clustering approaches in terms of efficiency

perceptual adaptive insensitivity for support vector machine image coding support vector machine svm learning has been recently proposed for image compression in the frequency domain using a constant spl epsiv insensitivity zone by robinson and kecman however according to the statistical properties of natural images and the properties of human perception a constant insensitivity makes sense in the spatial domain but it is certainly not a good option in a frequency domain in fact in their approach they made a fixed low pass assumption as the number of discrete cosine transform dct coefficients to be used in the training was limited this paper extends the work of robinson and kecman by proposing the use of adaptive insensitivity svms for image coding using an appropriate distortion criterion based on a simple visual cortex model training the svm by using an accurate perception model avoids any a priori assumption and improves the rate distortion performance of the original approach

a neuro fuzzy adaptive control strategy for refuse incineration plants abstract a refuse incineration plant is a complex process whose multi variable control problems cannot be solved conventionally by deriving an exact mathematical model of the process a solution based on advanced fuzzy logic technologies within a suitable development methodology is demonstrated by a controller implemented for the refuse incineration plant in hamburg stapelfeld germany incineration plants are individual constructions to adapt the controller for other plants a method for automated adaptation of the controller is designed

a petrov galerkin finite element method for convection dominated flows an accurate upwinding technique for satisfying the maximum principle abstract in this paper we present a new petrov galerkin method for convection dominated flow problems which is conservative and satisfies the discrete maximum principle this method also possesses no spurious crosswind diffusion and gives very accurate solutions the method is representative of a class of methods which may be described as fixed mesh adaptive

on the design of algebraic flux correction schemes for quadratic finite elements abstract a fully algebraic approach to the design of nonlinear high resolution schemes is revisited and extended to quadratic finite elements the matrices resulting from a standard galerkin discretization are modified so as to satisfy sufficient conditions of the discrete maximum principle for nodal values in order to provide mass conservation the perturbation terms are assembled from skew symmetric internodal fluxes which are redefined as a combination of first and second order divided differences the new approach to the construction of artificial diffusion operators is combined with a node oriented limiting strategy the resulting algorithm is applied to p 1 and p 2 approximations of stationary convection diffusion equations in 1d 2d

sufficient conditions for a discrete maximum principle for high order collocation methods abstract the purpose of this work is to extend earlier results concerning a discrete maximum principle for collocation methods to higher order piecewise polynomial approximations the techniques of this paper use a different set of basis elements for the piecewise polynomial space than that employed in the earlier work for the cubic and quartic cases

on discrete maximum principles for discontinuous galerkin methods the aim of this work is to propose a monotonicity preserving method for discontinuous galerkin dg approximations of convection diffusion problems to do so a novel definition of discrete maximum principle dmp is proposed using the discrete variational setting of the problem and we show that the fulfilment of this dmp implies that the minimum maximum depending on the sign of the forcing term is on the boundary for multidimensional problems then an artificial viscosity av technique is designed for convection dominant problems that satisfies the above mentioned dmp the noncomplete stabilized interior penalty dg method is proved to fulfil the dmp property for the one dimensional linear case when adding such av with certain parameters the benchmarks for the constant values to satisfy the dmp are calculated and tested in the numerical experiments section finally the method is applied to different test problems in one and two dimensions to show its performance

regularization operators for natural images based on nonlinear perception models image restoration requires some a priori knowledge of the solution some of the conventional regularization techniques are based on the estimation of the power spectrum density simple statistical models for spectral estimation just take into account second order relations between the pixels of the image however natural images exhibit additional features such as particular relationships between local fourier or wavelet transform coefficients biological visual systems have evolved to capture these relations we propose the use of this biological behavior to build regularization operators as an alternative to simple statistical models the results suggest that if the penalty operator takes these additional features in natural images into account it will be more robust and the choice of the regularization parameter is less critical

on spurious oscillations at layers diminishing sold methods for convection diffusion equations part i a review abstract an unwelcome feature of the popular streamline upwind petrov galerkin supg stabilization of convection dominated convection diffusion equations is the presence of spurious oscillations at layers since the mid of the 1980s a number of methods have been proposed to remove or at least to diminish these oscillations without leading to excessive smearing of the layers the paper gives a review and state of the art of these methods discusses their derivation proposes some alternative choices of parameters in the methods and categorizes them some numerical studies which supplement this review provide a first insight into the advantages and drawbacks of the methods

a discontinuity capturing crosswind dissipation for the finite element solution of the convection diffusion equation abstract to avoid the local oscillations that still remain using the streamline upwind petrov galerkin formulation for the scalar convection diffusion equation the introduction of a nonlinear crosswind dissipation is proposed it is shown that the method is less overdiffusive than other discontinuity capturing techniques and has better numerical behavior the design of the crosswind diffusion is based on the study of the discrete maximum principle for some simple cases

a discrete maximum principle for collocation methods abstract a discrete maximum principle for collocation approximations is formulated for the cases of piecewise cubic and piecewise quartic c 1 approximations suffiecient conditions for the placement of the collocation points are derived which ensure that the resulting collocation approximations satisfy the discrete maximum principle

best wavelet packet bases in a rate distortion sense a fast rate distortion r d optimal scheme for coding adaptive trees whose individual nodes spawn descendents forming a disjoint and complete basis cover for the space spanned by their parent nodes is presented the scheme guarantees operation on the convex hull of the operational r d curve and uses a fast dynamic programing pruning algorithm to markedly reduce computational complexity applications for this coding technique include r coefman et al s yale univ 1990 generalized multiresolution wavelet packet decomposition iterative subband coders and quadtree structures applications to image processing involving wavelet packets as well as discrete cosine transform dct quadtrees are presented

bit allocation for dependent quantization with applications to multiresolution and mpeg video coders we address the problem of efficient bit allocation in a dependent coding environment while optimal bit allocation for independently coded signal blocks has been studied in the literature we extend these techniques to the more general temporally and spatially dependent coding scenarios of particular interest are the topical mpeg video coder and multiresolution coders our approach uses an operational rate distortion r d framework for arbitrary quantizer sets we show how a certain monotonicity property of the dependent r d curves can be exploited in formulating fast ways to obtain optimal and near optimal solutions we illustrate the application of this property in specifying intelligent pruning conditions to eliminate suboptimal operating points for the mpeg allocation problem for which we also point out fast nearly optimal heuristics additionally we formulate an efficient allocation strategy for multiresolution coders using the spatial pyramid coder as an example we then extend this analysis to a spatio temporal 3 d pyramidal coding scheme we tackle the compatibility problem of optimizing full resolution quality while simultaneously catering to subresolution bit rate or quality constraints we show how to obtain fast solutions that provide nearly optimal typically within 0 3 db full resolution quality while providing much better performance for the subresolution layer typically 2 3 db better than the full resolution optimal solution

combustion control of refuse incineration plant by fuzzy logic abstract refuse incineration plant operations involve many kinds of uncertain factors such as the variable physical properties of refuse as fuel and the complexity of the burning phenomenon that makes it very difficult to apply conventional control methods to the combustion control of the refuse this paper describes a fuzzy control system for the refuse combustion process which applies sensing and controlling rules of skilled operators from a simulation analysis and some test runs on an actual incineration plant it is concluded that the fuzzy control system is effective and practical toward plant automation

rate distortion theory of finite point processes we study the compression of data in the case where the useful information is contained in a set rather than a vector i e the ordering of the data points is irrelevant and the number of data points is unknown our analysis is based on rate distortion theory and the theory of finite point processes we introduce fundamental information theoretic concepts and quantities for point processes and present general lower and upper bounds on the rate distortion function to enable a comparison with the vector setting we concretize our bounds for point processes of fixed cardinality in particular we analyze a fixed number of unordered gaussian data points and show that we can significantly reduce the required rates compared to the best possible compression strategy for gaussian vectors as an example of point processes with variable cardinality we study the best possible compression of poisson point processes for the specific case of a poisson point process with uniform intensity on the unit square our lower and upper bounds are separated by only a small gap and thus provide a good characterization of the rate distortion function

comparison of fuzzy reasoning methods l a zadeh e h mamdani and m mizumoto et al have proposed methods for fuzzy reasoning in which the antecedent involves a fuzzy conditional proposition if x is a then y is b with a and b being fuzzy concepts mizumoto et al have investigated the properties of their methods in the case of generalized modus ponens this paper deals with the properties of their methods in the case of generalized modus tollens and investigates the other new fuzzy reasoning methods obtained by introducing the implication rules of many valued logic systems finally the properties of syllogism and contrapositive are investigated under each fuzzy reasoning method

a video compression scheme with optimal bit allocation among segmentation motion and residual error we present a theory for the optimal bit allocation among quadtree qt segmentation displacement vector field dvf and displaced frame difference dfd the theory is applicable to variable block size motion compensated video coders vbsmcvc where the variable block sizes are encoded using the qt structure the dvf is encoded by first order differential pulse code modulation dpcm the dfd is encoded by a block based scheme and an additive distortion measure is employed we derive an optimal scanning path for a qt that is based on a hilbert curve we consider the case of a lossless vbsmcvc first for which we develop the optimal bit allocation algorithm using dynamic programming dp we then consider a lossy vbsmcvc for which we use lagrangian relaxation and show how an iterative scheme which employs the dp based solution can be used to find the optimal solution we finally present a vbsmcvc which is based on the proposed theory which employs a dct based dfd encoding scheme we compare the proposed coder with h 263 the results show that it outperforms h 263 significantly in the rate distortion sense as well as in the subjective sense

a new approach to inference in approximate reasoning abstract we introduce a new approach to inference in approximate reasoning based on truth value restriction the degree to which the actual given value a of a variable x agrees with the antecedent value b in a production if x is b then y is c is represented as a fuzzy subset of a truth space we introduce a new form of implication based on the exponential operation a new compatibility relation based on the input value a and the antecedent value b is defined a fuzzy truth value true derived from the antecedent value b is also defined it is shown that by mapping this compatibility relation into the truth space a fuzzy truth value is generated which produces an exponential family of the fuzzy truth value true we show that the inferred consequent can be generated from this truth value theoretical results showing the validity of this method to 1 chain rules consisting of several single fuzzy conditional propositions and 2 conjunctive fuzzy conditional propositions are also presented theoretical and simulation results demonstrate that our method is superior to the existing methods when intuitively correct responses are required