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Crowdsourcing is a new trend for pervasively discovering traffic information due to its low deployment and maintenance cost as compared with traditional infrastructure-based approaches, e.g., loop detectors and CCTV. Mining techniques and the penetration rate of participators in the discovery process are two major issues in such approaches. In this work, we first point out the shockwave phenomenon...
Effectively utilizing readily available auxiliary data to improve predictive performance on new modeling tasks is a key problem in data mining. In this research the goal is to transfer knowledge between sources of data, particularly when ground truth information for the new modeling task is scarce or is expensive to collect where leveraging any auxiliary sources of data becomes a necessity. Towards...
With the growing prevalence of phasor measurement units (PMUs), an abundance of high-resolution data is becoming available for analysis. The problem arises of how to use the data to obtain information about the operating conditions of the system. We examine the use of data from PMUs to expose information about the underlying system topology. An equivalent network at the PMU buses is obtained. Changes...
Mass estimation, an alternative to density estimation, has been shown recently to be an effective base modelling mechanism for three data mining tasks of regression, information retrieval and anomaly detection. This paper advances this work in two directions. First, we generalise the previously proposed one-dimensional mass estimation to multidimensional mass estimation, and significantly reduce the...
Population data is great significance for government departments to make policies. Census data is high accuracy but it cost more time and a lot of money. Apply remote sensing to population estimation is very effective and costs less. In this article, zoning land use density method which originated from built area. The method of land use density was used to establish the estimation model for population...
Solution of the problem of fault accommodation in nonlinear dynamic systems is related to constructing the control law which provides full decoupling with respect to fault effects. Existing conditions are formulated and calculating relations are given for the control law.
Product failure distribution research is a basic research for product advanced design and manufacture, and has an important role in intelligent computing. Traditional analysis of the failure distribution about small samples has some limitations, for example, the weibull distribution test is better as the sample size is more than 10; the Figure test is better as the sample size is more than 20; the...
An algorithm based on extended Kalman filter applied to the sensorless PMSM drives to estimate rotor position and speed are described in this paper. The EKF is an optimal recursive estimation algorithm for estimating the states of dynamic nonlinear systems. The system simulation model is established in MATLAB/Simulink. And the sensorless PMSM drive system is implemented on the DSP employed field oriented...
Double-difference carrier-phase relative positioning can realize GPS high-precision positioning. In the designing and implementation of post-processing technique, the key is resolving integer ambiguities. Applying with VC++ combining with MATCOM, the transformation from two dimension array to matrix has been realized, and matrix calculation is implemented in MATCOM, in which the LAMBDA algorithm has...
Wireless Sensor Networks (WSNs) have been of high interest during the past couple of years. One of the most important aspects of WSN research is location estimation. As a good solution of fine grained localization Reichenbach et al. introduced the Distributed Least Squares (DLS) algorithm, which splits the costly localization process in a complex precalculation and a simple postcalculation which is...
We characterize the stability and achievable performance of networked estimation under correlated packet losses described by the Gilbert-Elliot model. For scalar continuous-time linear systems, we derive closed-form expressions for the mean-square distortion of the optimal estimator. The conditions for stable mean square estimation error are equivalent to those obtained previously for stability of...
In this paper, a new distributed Kalman filter is proposed for state estimation of systems with acyclic digraph, namely acyclic systems. This method can be applied to a number of large-scale systems including sensor networks and formation flying missions. An acyclic system can be represented by an overlapping block-diagonal state space (OBDSS) model, which requires an extensive communication overhead...
Wireless sensor networks (WSNs) have been of high interest during the past couple of years. One of the most important aspects of WSN research is location estimation. As a good solution of fine grained localization Reichenbach et al. introduced the distributed least squares (DLS) algorithm, which splits the costly localization process in a complex precalculation and a simple postcalculation which is...
In order to reduce the computational load of the recursive least squares (RLS) algorithm, a decomposition based least squares algorithm is developed for non-uniformly sampled multirate systems. The main ideal is to decompose the identification model of the non-uniformly sampled systems into several submodels with smaller dimensions and fewer parameters based on the hierarchical identification principle...
This paper studies the velocity-consensus problem of multi-agent systems with second-order agent dynamics and proposes an asynchronous distributed consensus protocol allowing for switching interaction topology, time-varying delays and intermittent information transmission. Unlike the existing works, the agreement of position-like states is not required in this paper. Velocity consensus is a prerequisite...
The Two-Stage Algorithm (TSA) has been extensively used and adapted for the identification of block-oriented nonlinear systems including Hammerstein systems. This paper revisits an optimality result established by Bai in 1998 showing that the TSA provides the optimal estimation of a bilinearly parameterized Hammerstein system in the sense of a weighted nonlinear least-squares (LS) criterion formulated...
Ordinary differential equation with small parameter is considered in this paper. This kind of problem changes rapidly in both side of boundary layer. Firstly, the asymptotic solution of the problem is presented in order one. The asymptotic solution is used to solve the problem outside the boundary layer. Secondly, the analytical solution is decomposed into the smooth component and the singular component...
The projective recovery of 3D point structure from multiple images has been one of the classical problems in computer vision. Existing methods for projective reconstruction usually require a priori estimation of a consistent set of projective depths which in turn require the estimation of the projection matrices or the fundamental matrices in advance. Those methods are usually nonlinear, time-consuming,...
Predicting latency between nodes on the Internet can have a significant impact on the performance of many services that use latency distances among nodes as a decision making input. Coordinate-based approaches are among the family of latency prediction techniques where latency between each pair of nodes is modeled as the virtual distance among those nodes over a virtual system. This article proposes...
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