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This paper addresses a partial spatial-differencing (PSD) approach for the direction of arrival estimation in a low-grazing angle (LGA) condition. By dividing the sample covariance matrix into several column subvectors, we first form the corresponding reconstructed subarray covariance matrices (RSCMs). We then calculate the spatial differencing matrix for the noise parts of RSCMs, while the non-noise...
This paper addresses the orientation estimation in digital images using gradient-based methods. In particular, the second-moment matrix is used to extract the information about the local orientation and the degree of anisotropy in the image, mainly in structured and sinusoid-like textured images. Keeping in mind that the extent of gradient fields smoothing should be decent to extract as faithfully...
Classification is the one of the most important techniques in Datamining for data analysis. In Datamining, different Classification Techniques are available to predict outcome for a given dataset. There are many classification techniques for predicting and estimating accuracy, one such famous technique is Naïve Bayes Classifier. Naïve Bayes is very popular as it is easy to build, not so complex and...
Many practical applications of clustering involve data collected over time. In these applications, evolutionary clustering can be applied to the data to track changes in clusters with time. In this paper, we consider an evolutionary version of spectral clustering that applies a forgetting factor to past affinities between data points and aggregates them with current affinities. We propose to use an...
The task of finding authoritative people within an organization has received increased interest over the past few years. To identify an expert in a specific field, expertise evidence of candidates should be collected in the enterprise corpora to represent one's knowledge and skills. Though there have been various methods proposed for evidence collecting and expertise modeling, little work has been...
We describe four problems inherent to Grid scheduling that could be identified by means of measurements in the D-Grid. These problems make meta-scheduling nearly always a delicate task. In the face of this, we developed a new hybrid methodology to schedule application workflows which presumably supersedes existing methods. Our algorithm combines existing scheduling strategies for the Grid and for...
We consider the problem of attitude stabilization using exclusively visual sensory input, and we look for a solution which can satisfy the constraints of a ??bio-plausible?? computation. We obtain a PD controller which is a bilinear form of the goal image, and the current and delayed visual input. Moreover, this controller can be learned using classic neural networks algorithms. The structure of the...
This paper proposes a new fixed-lag smoother for state estimation in discrete-time state space models, which is called the unbiased, fixed-lag, and optimal (UFO) smoother. The proposed UFO smoother is obtained by directly solving an optimization problem with the unbiasedness constraint using only the most recent finite observations. Therefore, the proposed UFO smoother is both unbiased and optimal...
Expert finding is the task of identifying persons with expertise on a given topic. Existing methods try to model the dependencies between candidates and terms with distance measure or sequential measure, which have been proven to be effective. However, to the best of our knowledge, no work has been conducted on the combination of the two dependencies. In this paper, we propose a language model based...
N-grams can be used for spelling check and correction processes. The first step to use n-grams is to find the language specific n-grams by using a corpus. But a corpus cannot be big enough to contain all the possible word n-grams. Back-off smoothing technique is one of the techniques to estimate the frequency of the unknown n-grams in a corpus. By using Back-off technique and the Minimum Edit Distance...
Geographic masking displaces points to hide their identities. It has been used in health-related studies to protect patients' confidentialities. The main concern in this process is the balance between the protection of confidentiality and the preservation of the original spatial pattern. However, there is paucity in literature on quantification of this balance. We conducted a preliminary research...
Compressed sensing (CS) lowers the number of measurements required for reconstruction and estimation of signals that are sparse when expanded over a proper basis. Traditional CS approaches deal with time-invariant sparse signals, meaning that, during the measurement process, the signal of interest does not exhibit variations. However, many signals encountered in practice are varying with time as the...
In this paper, we extend Razdan and Bae's second-order local fitting method to construct an effective third-order fitting patch. Compared to other estimation algorithms, this weighted bicubic Bezier patch more accurately obtains the normal vector and curvature estimation of a triangular mesh model. Furthermore, we define the principal geodesic torsion of each vertex on the mesh model and estimate...
This paper proposes a novel approach to advertisement evaluation using automatic salient regions. The salient regions are detected using a predicting model, in which the estimation are obtained by the space variant foveated image. The saliency is defined as the difference between the input image and its estimation. Then an advertisement is determined as attractive if the detected salient regions are...
In this paper, we establish a global error bound for the generalized linear complementarity problem in engineering modeling (GLCP), based on we propose a new type of solution method to solve the GLCP. The global and quadratic rate of convergence is established without nondegenerate solution. These conclusions can be viewed as extensions of previously known results.
We propose an autonomous system for personalized production of basketball videos from multi-sensored data under limited display resolution. We propose criteria for optimal planning of viewpoint coverage and camera selection for improved story-telling and perceptual comfort. By using statistical inference, we design and implement the estimation process. Experiments are made to verify the system, which...
In this paper, variable selection issue is considered in a nonparametric regression setting. Two stepwise procedures based on variance estimators are proposed for selecting the significant variables in a general nonparametric regression model. These procedures do not require multidimensional smoothing at intermediate steps and they are based on formal rests of hypotheses as opposed to existing methods...
A new channel order estimation method is proposed for single-input multi-output (SIMO) systems. The method is based on a cost function which is constructed from the channel output error (COE). Proposed method uses the least-squares-smoothing (LSS) technique for channel estimation and Moore-Penrose pseudoinverse for the estimation of input. Channel outputs are obtained using the estimated channel coefficients...
To accurately describe the high frequency electromagnetic scattering of the radar objects, the full-polarization GTD model is established based on the combination of the full-polarization information and the geometric theory of diffraction model. Meanwhile, A novel method, MUSIC based on polarization linear variation method (PL-MUSIC) is proposed. The estimation accuracy is improved and the computational...
Self-consistency is a fundamental principle in statistics for retaining maximum amount of information in the data. In this paper this principle is applied to develop a new method for nonparametric spectrum estimation with missing data. One major advantage of the proposed method is that it can be coupled with any complete data nonparametric spectrum estimation procedure, including kernel smoothing,...
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