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A method is proposed to annotate editorials and news articles for sentences that most accurately represent the opinion of the speaker towards the issue. The speaker's point of view or level of discernment of the issue is whittled out. A list of informative and related keywords is extracted from the document based on their frequency of occurrence. Subsequently, pronominal anaphora is resolved at the...
This paper presents computational intelligence techniques for software cost estimation. We proposed a new recurrent architecture for genetic programming (GP) in the process. Three linear ensembles based on (i) arithmetic mean (ii) geometric mean and (iii) harmonic mean are implemented. We also performed GP based feature selection. The efficacy of these techniques viz multiple linear regression, polynomial...
Information retrieval (IR) has been widely investigated these last decades and significant results have been applied to several domains like e-commerce, e-library and automatic medical diagnostics. However, very few studies in this area deal with artificial intelligence or AI tools. Knowing the power of meta-heuristics in problem solving, we suggest exploring information retrieval with an evolutionary...
This paper proposes an affine projection algorithm (APA) using the inner product between input vectors. The existing APAs have fast convergence rate but large steady-state estimation errors. In order to reduce the estimation errors, the proposed algorithm adjusts the number of the input vectors by grouping of the input vectors. The grouping process uses the angle between a current input vector and...
A new formulation facilitating the determination of the autocorrelation lags, and consequently the autocorrelation matrix, of an autoregressive moving average signal of arbitrary order (ARMA(p, q)) is presented. The main features of our formulation, stated as a set of linear equations to be solved, are 1) its conceptual simplicity 2) its reliance only on primary parameters of the ARMA(p, q) model,...
The paper provides a novel approach to emotion recognition from facial expression and voice of subjects. The subjects are asked to manifest their emotional exposure in both facial expression and voice, while uttering a given sentence. Facial features including mouth-opening, eye-opening, eyebrow-constriction, and voice features including, first three formants: F1, F2, and F3, and respective powers...
This paper proposes a new fast multi-reference picture motion estimation algorithm which uses the relation of motion vector with distance of each frame. The proposed algorithm reduces search areas of motion estimation using linear feature of object's motion for fast motion estimation. Search areas in reference picture 2, 3 and 4 are minimized using a distance of each frame and motion vectors of reference...
Geometric problems in visual computing (computer graphics, computer vision, and image processing) are typically modeled and solved using linear algebra (LA). Thus, vectors are used to represent directions and points in space, while matrices are used to model transformations. LA, however, presents some well-known limitations for performing geometric computations. As a result, one often needs to aggregate...
This paper presents a novel methodology to perform matching between image points described by their respective features. Traditionally, such correspondences are determined by computing the similarity between descriptor vectors associated to each point which are obtained by invariant descriptors. Our methodology first obtains a coarse global registration among images, which constrains the correspondence...
In this paper we propose a universal strategy for the automatic interpretation of sensor signals. We focus on acoustic signals. However, any time series may be used. We assume that changes in an object's state cause a typical and reproducible change in the characteristics of the acquired sensor signal. In such cases we can train pattern recognizers basing on Hidden-Markov-Models or support vector...
It is well known that there is a one-to-one correspondence between the entropy vector of a collection of n random variables and a certain group-characterizable vector obtained from a finite group and n of its subgroups. However, if one restricts attention to abelian groups then not all entropy vectors can be obtained. This is an explanation for the fact shown by Dougherty et al that linear network...
Erasure coding techniques are used to increase the reliability of distributed storage systems while minimizing storage overhead. Also of interest is minimization of the bandwidth required to repair the system following a node failure. In a recent paper, Wu et al. characterize the tradeoff between the repair bandwidth and the amount of data stored per node. They also prove the existence of regenerating...
This is a tale of two linear programming decoders, namely channel coding linear programming decoding (CC-LPD) and compressed sensing linear programming decoding (CS-LPD). So far, they have evolved quite independently. The aim of the present paper is to show that there is a tight connection between, on the one hand, CS-LPD based on a zero-one measurement matrix over the reals and, on the other hand,...
We study network error correction with unequal link capacities. Previous results on network error correction assume unit link capacities. We consider network error correction codes that can correct arbitrary errors occurring on up to z links. We find the capacity of a network consisting of parallel links, and a generalized Singleton outer bound for any arbitrary network. We show by example that linear...
It has been conjectured that complex Gaussian interference channels with constant channel coefficients have only one degree-of-freedom (DoF) regardless of the number of users. While several examples are known of constant channels that achieve more than 1 DoF, these special cases only span a subset of measure zero. In other words, for almost all channel coefficient values, it is not known if more than...
In this paper we study the maximum throughput of network coding schemes for a single multicast session in wireless networks. We adapt ??deterministic channel model?? proposed in for modeling wireless interference. We introduce a novel rotational coding scheme that can achieve the well-known minimum cutset bound. This coding scheme has lower encoding complexity in comparison with the existing random...
Consider the standard linear regression model y = X??* + w, where y ?? Rn is an observation vector, X ?? Rn??d is a measurement matrix, ??* ?? Rd is the unknown regression vector, and w ~ N (0, ??2 I) is additive Gaussian noise. This paper determines sharp minimax rates of convergence for estimation of ??* in ??2 norm, assuming that ??* belongs to a weak ??b-ball Bq(Rq) for some q ?? [0, 1]. We show...
The classification of quaternary [21s+t,3,d] codes with dges16s and without zero coordinates is reduced to the classification of quaternary [21c(3,s,t)+t,k,d] code for sges1 and 0lestles20, where c(3,s,t)les min{s, 3t} is a function of 3, s, and t. Quaternary optimal Hermitian self-orthogonal codes are characterized by systems of linear equations. Based on these two results, the complete classification...
In this paper, we propose an efficient method for resolving the optimal discriminant vectors of generalized discriminant analysis (GDA) and point out the drawback of high computational complexity in the traditional class-incremental GDA [W. Zheng, "Class-Incremental Generalized Discriminant Analysis", Neural Computation 18, 979-1006 (2006)]. Because there is no need to compute the mean of...
The properties of value vector and coefficient vector of symmetric Boolean functions with maximum algebraic immunity are studied by applying combinatory and Lucas formula. Basing on that, we proved the algebraic immunity of three classes (2m -2)-variable symmetric Boolean functions with mges3 is not maximum.
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