Due to the existence of measurement error and approximate theory of network model parameters, the result of power system state estimation is uncertain. Interval analysis based on iterative solution method can estimate...
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In this paper, we obtain fundamental L-p bounds in sequential prediction and recursive algorithms via an entropic analysis. Both classes of problems are examined by investigating the underlying entropic relationships ...
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ISBN:
(纸本)9781728140841
In this paper, we obtain fundamental L-p bounds in sequential prediction and recursive algorithms via an entropic analysis. Both classes of problems are examined by investigating the underlying entropic relationships of the data and/or noises involved, and the derived lower bounds may all be quantified in a conditional entropy characterization. We also study the conditions to achieve the generic bounds from an innovations' viewpoint.
A new algorithm for the maximum a posteriori (MAP) decoding of linear block codes is presented. The proposed algorithm can be regarded as a conventional BCJR algorithm for a section trellis diagram, where branch metri...
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A new algorithm for the maximum a posteriori (MAP) decoding of linear block codes is presented. The proposed algorithm can be regarded as a conventional BCJR algorithm for a section trellis diagram, where branch metrics of the trellis are computed by the recursive MAP algorithm proposed by the authors. The decoding complexity of the proposed algorithm depends on the sectionalization of the trellis. A systematic way to find the optimum sectionalization which minimizes the complexity is also presented. Since the algorithm can be regarded as a generalization of both of the BCJR and the recursive MAP algorithms, the complexity of the proposed algorithm cannot be larger than those algorithms, as far as the sectionalization is chosen appropriately.
This paper describes an algorithm obtained by merging a recursive star-identification algorithm with a recently developed adaptive singular-value-decomposition-based estimator of the angular-velocity vector (QuateRA)....
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This paper describes an algorithm obtained by merging a recursive star-identification algorithm with a recently developed adaptive singular-value-decomposition-based estimator of the angular-velocity vector (QuateRA). In a recursive algorithm, the more accurate the angular-velocity estimate is, the quicker and more robust to noise is the resultant recursive algorithm. Hence, combining these two techniques produces an algorithm capable of handling a variety of dynamics scenarios. The speed and robustness of the algorithm are highlighted in a selection of simulated scenarios. First, a speed comparison is made with the state-of-the-art lost-in-space star-identification algorithm, Pyramid. This test shows that in the best case, the algorithm is on average an order of magnitude faster than Pyramid. Next, the recursive algorithm is validated for a variety of dynamic cases, including a ground-based "Stellar Compass" scenario, a satellite in geosynchronous orbit, a satellite during a reorientation maneuver, and a satellite undergoing non-pure-spin dynamics.
A new batch least square (LS) identification algorithm with recursive formulation is proposed to deal with the problems occurred when the ordinary LS algorithm is applied to real-time and on-line identification. The f...
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ISBN:
(纸本)7312012035
A new batch least square (LS) identification algorithm with recursive formulation is proposed to deal with the problems occurred when the ordinary LS algorithm is applied to real-time and on-line identification. The fundamental feature of this algorithm is to fix the observation matrix's dimension, making use of definite amount of newly obtained data and ignoring the older data. Taking advantage of recursive formulation, this algorithm avoids the inverse operation and thus reduces the calculation, making itself capable of application in real-time and on-line identification case, Simulation shows that this algorithm has rather good precision and tracking ability, which are greatly influenced by the dimension of the observation matrix.
The deployment of a cable from two moving platforms is examined. The cable is regarded as a collection of links whose number increases with time. An order-n algorithm is constructed for the simulation of the motion of...
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The deployment of a cable from two moving platforms is examined. The cable is regarded as a collection of links whose number increases with time. An order-n algorithm is constructed for the simulation of the motion of the cable during deployment, incorporating a novel, three-pass procedure for the identification of constraint forces appearing in the equations of motion and a procedure for the release of the cable from both platforms. The algorithm is described, and the use of the associated simulation program is illustrated by means of an example.
In this paper, a recursive Measurement Error Estimation Identification algorithm has been proposed for identifying multiple interacting bad data in power system static state estimation. A set of linearized formulae ha...
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In this paper, a recursive Measurement Error Estimation Identification algorithm has been proposed for identifying multiple interacting bad data in power system static state estimation. A set of linearized formulae have been developed and used to recursively calculate normalized residuals and normalized measurement error estimates upon which the bad data identification method is based. Sparse vector and partial factor modification techniques have been made full use of in the recursive identification calculations. Neither W(ss) nor state re-estimation is needed in the whole identification process. Digital tests on various power systems including a 171 bus real system have been done to show the validity and efficiency of the proposed bad data identification method.
This paper explores the problems of generalized center conditions and integrability of resonant infinity for a complex polynomial differential system. The method is based on converting resonant infinity into an elemen...
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This paper explores the problems of generalized center conditions and integrability of resonant infinity for a complex polynomial differential system. The method is based on converting resonant infinity into an elementary singular point by a homeomorphic transformation. The calculation of generalized singular point quantities is an effective way of finding necessary conditions for integrable systems. A new recursive algorithm for computing generalized singular point quantities at the origin of the transformed system is derived. At the same time, a necessary and sufficient condition for resonant infinity to be a generalized complex center is presented. As an application of the new recursive algorithm, the generalized center conditions for resonant infinity for a class of cubic systems are discussed. To the best of our knowledge, this is the first time that the generalized center problem has been considered for p : -q resonant infinity. (C) 2011 Elsevier Ltd. All rights reserved.
The theoretical model of direct diffraction phase-contrast imaging with partially coherent x-ray source is expressed by an operator of multiple integral. It is presented that the integral operator is linear. The probl...
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The theoretical model of direct diffraction phase-contrast imaging with partially coherent x-ray source is expressed by an operator of multiple integral. It is presented that the integral operator is linear. The problem of its phase retrieval is described by solving an operator equation of multiple integral. It is demonstrated that the solution of the phase retrieval is unstable. The numerical simulation is performed and the result validates that the solution of the phase retrieval is unstable.
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