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In this paper we propose a framework of customer baseline load (CBL) estimation for demand response in Smart Grid. The introduction of demand response requires quantifying the amount of demand reduction. This process is called the measurement and verification. The proposed framework of CBL estimation is based on the unsupervised learning technique of data mining. Specifically we leverage both the...
The dexterity of body motion when performing skills are being actively studied. In this paper, singular value decomposition is used to extract the dexterous features from the time-series data of body motion. A matrix is composed by overlapping the subsets of the time-series data. The left singular vectors of the matrix are extracted as the patterns of the motion and the singular values as a scalar,...
We propose a joint object pose estimation and categorization approach which extracts information about object poses and categories from the object parts and compositions constructed at different layers of a hierarchical object representation algorithm, namely Learned Hierarchy of Parts (LHOP) [7]. In the proposed approach, we first employ the LHOP to learn hierarchical part libraries which represent...
Current mining algorithms for attributed graphs exploit dependencies between attribute information and edge structure, referred to as homophily. However, techniques fail if this assumption does not hold for the full attribute space. In multivariate spaces, some attributes have high dependency with the graph structure while others do not show any dependency. Hence, it is important to select congruent...
Any trajectory is always generated with its origin and destination. Origin-destination (OD) generation for trips plays an important role in many applications such as trajectory mining, traffic simulation, or marketing. In previous work on traffic pattern recognition, microscopic ODs for limited areas are estimated with probe-car data, while macroscopic ODs for broad areas are usually generated by...
Clustering is the unsupervised classification of patterns into groups. A clustering algorithm partitions a data set into several groups such that similarity within a group is larger than among groups The clustering problem has been addressed in many contexts and by researchers in many disciplines, this reflects its broad appeal and usefulness as one of the steps in exploratory data analysis. There...
Let the observed sequence {yk} be generated by the multivariate ARMAX system A(z)yk = B(z)uk-1 + C(z)wk, where {wk} is the system noise with unknown covariance matrix Rw > 0, and {uk} is a sequence of mutually independent and identically distributed (iid) random vectors. Based on {yk} and {uk}, identification algorithms are proposed to simultaneously estimate the orders (p,q,r), the covariance...
In this article, we consider the estimation for the vector of parameters in a linear regression model by unifying the sample and the prior information. A new Liu-type biased estimator called weighted stochastic restricted Liu estimator is proposed. Furthermore, necessary and sufficient conditions for the superiority of the weighted stochastic restricted Liu estimator over the Liu estimator, the weighted...
In this work, we present a new robust method for calibrating the vision system. With the known intrinsic parameters of the camera, we show that its motion parameters, in terms of translation vector and rotation matrix, can be determined automatically from plane-based homography. In this method, a closed-form solution is provided to increase the computational efficiency and arbitrary motion is allowed...
In the distributed video coding, side information is involved not only in the decoding of the quantized source, but also in the reconstruction of the images. So the quality of side information takes an important role in the distributed video codec. In this paper, a refined approach to SI extraction is proposed. Based on the high correlation between the motion vectors of adjacent blocks, the motion...
This paper proposes a Cross Spectral-Total Least Square (CS-TLS) method to measure the frequencies of the weak signal in colored noise, which clears the fake peaks caused by spectral estimation and overcomes efficiently. These false peaks are caused by the extended-order of the characteristic equation. Thus false peaks are hard to distinguish from the harmonic signal peaks in power spectrum curves...
To estimate intracranial pressure (ICP) noninvasively, a data mining framework was proposed in our previous work. In the procedure, the mapping function plays an important role to estimate ICP based on the feature vector extracted from arterial blood pressure (ABP) and flow velocity (FV), which is translated to the estimated errors by the mapping function for each entry in the database. In this paper,...
This paper discusses people counting of crowd open scene according to statistics. Firstly, 16 features of texture of scene image is obtained based on grey level dependence matrix which is called feature vector, and feature matrix is construct based on those vectors. Then the most significant features are taken based on principal component analysis and the statistical model of number of people which...
This paper addresses a state-estimation problem for nonlinear systems with non-Gaussian noise and interval constraints on the state vector. We proposed a new Gaussian sum filtering algorithm to deal with non-Gaussian noises. Validity of the proposed method is illustrated in a numerical example.
The problem of joint input and state estimation is addressed in this paper for linear discrete-time stochastic systems without direct feedthrough from unknown inputs to outputs. With the weighted least squares estimation for an extended state vector including unknown inputs and states, a recursive filter approach referred to as Kalman filter with unknown inputs without direct feedthrough (KF-UI-WDF)...
We examine vectors and attitude in Engineering with greater attention to detail than in earlier works on the subject. This tutorial is an expansion of part of a survey of attitude representations. The most salient characteristic of this work is a greater emphasis on the distinction between physical vectors and their representation as column vectors. The need for such a treatment arises most strongly...
We propose an affine projection type multiuser detection for the DS-CDMA (direct sequence code division multiple access) system. This proposed algorithm estimates the desired information symbols using the conventional method based on affine projection algorithm, and then modifies the constraints of the conventional method in order to achieve the good MAI (multiple access interference) suppression...
In the past few years, there has been increased research interest in detecting previously unidentified events from Web resources. Our focus in this paper is to detect events from the click-through data generated by Web search engines. Existing event detection algorithms, which mainly study the news archive data, cannot be employed directly because of the following two unique features of click-through...
This passage mainly in the study of grey vectors, how to solve the vector and vector function, as well as how to construct a vector between two gray fitting function relationship.
This paper addresses the problem of source localization and waveform estimation in array processing applications. We present two nonparametric user parameter free algorithms, namely the iterative adaptive approach (IAA) and the maximum likelihood based IAA (IAA-ML). Both IAA and IAA-ML can work with arbitrary array geometries and uncorrelated as well as coherent sources. We extend IAA and IAA-ML to...
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