Gross error detection has great importance and is the necessary step in process data reconciliation.Many methods have been published to solve this problem,but no one can guarantee consistently finding all of gross err...Gross error detection has great importance and is the necessary step in process data reconciliation.Many methods have been published to solve this problem,but no one can guarantee consistently finding all of gross errors.A combinatory method based upon measurement test (MT) and nodal test (NT) is developed for practical use. The MT-NT combinatory approach makes use of both MT and NT tests and avoids any artificial manipulation.It also eliminates the huge combinatorial problem that is created in the combinatory method based upon nodal test or in the serial elimination method in the case of more than one gross errors in a large process system.展开更多
Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can sig...Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.展开更多
Efficient reconciliation is a crucial step in continuous variable quantum key distribution. The progressive-edge-growth(PEG) algorithm is an efficient method to construct relatively short block length low-density pari...Efficient reconciliation is a crucial step in continuous variable quantum key distribution. The progressive-edge-growth(PEG) algorithm is an efficient method to construct relatively short block length low-density parity-check(LDPC) codes. The qua-sicyclic construction method can extend short block length codes and further eliminate the shortest cycle. In this paper, by combining the PEG algorithm and quasi-cyclic construction method, we design long block length irregular LDPC codes with high error-correcting capacity. Based on these LDPC codes, we achieve high-efficiency Gaussian key reconciliation with slice recon-ciliation based on multilevel coding/multistage decoding with an efficiency of 93.7%.展开更多
文摘Gross error detection has great importance and is the necessary step in process data reconciliation.Many methods have been published to solve this problem,but no one can guarantee consistently finding all of gross errors.A combinatory method based upon measurement test (MT) and nodal test (NT) is developed for practical use. The MT-NT combinatory approach makes use of both MT and NT tests and avoids any artificial manipulation.It also eliminates the huge combinatorial problem that is created in the combinatory method based upon nodal test or in the serial elimination method in the case of more than one gross errors in a large process system.
基金Supported by the Funds for 0utstanding Young Researchers from the National Natural Science Foundation of China （No.60025308） and the Key Technologies R＆D Program in the National ＂10th 5-year Plan＂ （No.2001BA204B07）.
文摘Data reconciliation is an effective technique for providing accurate and consistent value for chemical process. However, the presence of gross errors can severely bias the reconciled results. Robust estimators can significantly reduce the effect of gross errors and yield less-biased results. In this article, a new method is proposed to solve the robust data reconciliation problem of nonlinear chemical process. By using several technologies including linearization method, penalty function, virtual observation equation, and equivalent weights method, the robust data reconciliation problem can be transformed into least squares estimator problem which leads to the convenience in computation. Simulation results in a nonlinear chemical process demonstrate the efficiency of the proposed method.
基金supported by the National Natural Science Foundation of China(Grant No.61378010)the Natural Science Foundation of Shanxi Province(Grant No.2014011007-1)
文摘Efficient reconciliation is a crucial step in continuous variable quantum key distribution. The progressive-edge-growth(PEG) algorithm is an efficient method to construct relatively short block length low-density parity-check(LDPC) codes. The qua-sicyclic construction method can extend short block length codes and further eliminate the shortest cycle. In this paper, by combining the PEG algorithm and quasi-cyclic construction method, we design long block length irregular LDPC codes with high error-correcting capacity. Based on these LDPC codes, we achieve high-efficiency Gaussian key reconciliation with slice recon-ciliation based on multilevel coding/multistage decoding with an efficiency of 93.7%.
基金Funds for Outstanding Young Researchers from the National Natural Science Foundation of China(No.60025308) and the Key Technologies R&D Program in the National “10th 5-year Plan” (No.2001BA204B07).
