The Experts below are selected from a list of 199557 Experts worldwide ranked by ideXlab platform
D Rees - One of the best experts on this subject based on the ideXlab platform.
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design and practical implementation of internet based predictive control of a servo system
IEEE Transactions on Control Systems and Technology, 2008Co-Authors: Senchun Chai, D ReesAbstract:This brief discusses the design and practical implementation of an Internet-based predictive control strategy. This novel control strategy can compensate for the Random Network delay and data dropout in an active way. In order to test the performance of the proposed control scheme, the offline simulation and practical implementation of an Internet-based servo control system are carried out. At the same time, the stability of the control scheme is also studied. The simulation and experimental results illustrate the feasibility and efficiency of the proposed Internet-based predictive control scheme.
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Networked predictive control of systems with Random Network delays in both forward and feedback channels
IEEE Transactions on Industrial Electronics, 2007Co-Authors: Guoping Liu, Yuanqing Xia, Jie Chen, D ReesAbstract:The design problem of Networked control systems (NCS) with constant and Random Network delay in the forward and feedback channels, respectively, is considered in this paper. A novel Networked predictive control (NPC) scheme is proposed to overcome the effects of Network delay and data dropout. Stability criteria of closed-loop NPC systems are presented. The necessary and sufficient conditions for the stability of closed-loop NCS with constant time delay are given. Furthermore, it is shown that a closed-loop NPC system with bounded Random Network delay is stable if its corresponding switched system is stable. Both simulation study and practical experiments show the effectiveness of the control scheme
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design and stability criteria of Networked predictive control systems with Random Network delay in the feedback channel
Systems Man and Cybernetics, 2007Co-Authors: D Rees, Wenshan HuAbstract:This paper is concerned with the design of Networked control systems (NCSs) with Random Network delay in the feedback channel and gives stability criteria of closed-loop Networked predictive control systems. The principle of predictive control is adopted to overcome the effects of Network time delay. The necessary and sufficient conditions on the stability of the closed-loop NCS are derived, which provides useful analytical stability criteria. The closed-loop Networked predictive control system with bounded Random Network delay is stable if the corresponding switched system is stable. Simulation and real-time results give an illustration of the proposed control strategies
Frank R. Kschischang - One of the best experts on this subject based on the ideXlab platform.
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universal weakly secure Network coding
Information Theory Workshop, 2009Co-Authors: Danilo Silva, Frank R. KschischangAbstract:This paper considers the problem of secure Network coding under the weak (and practically appealing) security requirements of Bhattad and Narayanan. Weak security allows communication at maximum rate while ensuring that only meaningless information is leaked to a wiretapper. Differently from the approach of Bhattad and Narayanan, which requires a joint design of the underlying Network code and the outer security scheme, we propose a universal approach that is completely independent of the Network code. In particular, the field size for linear Network coding operations does not need to be enlarged. The scheme is also compatible with Random Network coding.
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a rank metric approach to error control in Random Network coding
IEEE Transactions on Information Theory, 2008Co-Authors: Danilo Silva, Frank R. Kschischang, R KoetterAbstract:The problem of error control in Random linear Network coding is addressed from a matrix perspective that is closely related to the subspace perspective of Rotter and Kschischang. A large class of constant-dimension subspace codes is investigated. It is shown that codes in this class can be easily constructed from rank-metric codes, while preserving their distance properties. Moreover, it is shown that minimum distance decoding of such subspace codes can be reformulated as a generalized decoding problem for rank-metric codes where partial information about the error is available. This partial information may be in the form of erasures (knowledge of an error location but not its value) and deviations (knowledge of an error value but not its location). Taking erasures and deviations into account (when they occur) strictly increases the error correction capability of a code: if mu erasures and delta deviations occur, then errors of rank t can always be corrected provided that 2t les d - 1 + mu + delta, where d is the minimum rank distance of the code. For Gabidulin codes, an important family of maximum rank distance codes, an efficient decoding algorithm is proposed that can properly exploit erasures and deviations. In a Network coding application, where n packets of length M over F(q) are transmitted, the complexity of the decoding algorithm is given by O(dM) operations in an extension field F(qn).
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a rank metric approach to error control in Random Network coding
Information Theory Workshop, 2007Co-Authors: Danilo Silva, Frank R. Kschischang, R KoetterAbstract:The problem of error control in Random Network coding is considered, and a formulation of the problem is given in terms of rank-metric codes. This formulation allows many of the tools developed for rank-metric codes to be applied to Random Network coding. A Random Network code induces a generalized decoding problem for rank-metric codes in which the channel may supply partial information about the error in the form of erasures (knowledge of an error location not its values) and deviations (knowledge of an error value but not its location).
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coding for errors and erasures in Random Network coding
International Symposium on Information Theory, 2007Co-Authors: R Koetter, Frank R. KschischangAbstract:The problem of error-control in a "noncoherent" Random Network coding channel is considered. Information transmission is modelled as the injection into the Network of a basis for a vector space V and the collection by the receiver of a basis for a vector space U. A suitable coding metric on subspaces is defined, under which a minimum distance decoder achieves correct decoding if the dimension of the space V U is large enough. When the dimension of each codeword is restricted to a fixed integer, the code forms a subset of the vertices of the Grassmann graph. Sphere-packing, sphere-covering bounds and a Singleton bound are provided for such codes. A Reed-Solomon-like code construction is provided and decoding algorithm given.
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coding for errors and erasures in Random Network coding
arXiv: Information Theory, 2007Co-Authors: R Koetter, Frank R. KschischangAbstract:The problem of error-control in Random linear Network coding is considered. A ``noncoherent'' or ``channel oblivious'' model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear Network coding is vector-space preserving, information transmission is modelled as the injection into the Network of a basis for a vector space $V$ and the collection by the receiver of a basis for a vector space $U$. A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum distance decoder for this metric achieves correct decoding if the dimension of the space $V \cap U$ is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the Singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style ``list-1'' minimum distance decoding algorithm is provided.
R Koetter - One of the best experts on this subject based on the ideXlab platform.
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a rank metric approach to error control in Random Network coding
IEEE Transactions on Information Theory, 2008Co-Authors: Danilo Silva, Frank R. Kschischang, R KoetterAbstract:The problem of error control in Random linear Network coding is addressed from a matrix perspective that is closely related to the subspace perspective of Rotter and Kschischang. A large class of constant-dimension subspace codes is investigated. It is shown that codes in this class can be easily constructed from rank-metric codes, while preserving their distance properties. Moreover, it is shown that minimum distance decoding of such subspace codes can be reformulated as a generalized decoding problem for rank-metric codes where partial information about the error is available. This partial information may be in the form of erasures (knowledge of an error location but not its value) and deviations (knowledge of an error value but not its location). Taking erasures and deviations into account (when they occur) strictly increases the error correction capability of a code: if mu erasures and delta deviations occur, then errors of rank t can always be corrected provided that 2t les d - 1 + mu + delta, where d is the minimum rank distance of the code. For Gabidulin codes, an important family of maximum rank distance codes, an efficient decoding algorithm is proposed that can properly exploit erasures and deviations. In a Network coding application, where n packets of length M over F(q) are transmitted, the complexity of the decoding algorithm is given by O(dM) operations in an extension field F(qn).
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a rank metric approach to error control in Random Network coding
Information Theory Workshop, 2007Co-Authors: Danilo Silva, Frank R. Kschischang, R KoetterAbstract:The problem of error control in Random Network coding is considered, and a formulation of the problem is given in terms of rank-metric codes. This formulation allows many of the tools developed for rank-metric codes to be applied to Random Network coding. A Random Network code induces a generalized decoding problem for rank-metric codes in which the channel may supply partial information about the error in the form of erasures (knowledge of an error location not its values) and deviations (knowledge of an error value but not its location).
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coding for errors and erasures in Random Network coding
International Symposium on Information Theory, 2007Co-Authors: R Koetter, Frank R. KschischangAbstract:The problem of error-control in a "noncoherent" Random Network coding channel is considered. Information transmission is modelled as the injection into the Network of a basis for a vector space V and the collection by the receiver of a basis for a vector space U. A suitable coding metric on subspaces is defined, under which a minimum distance decoder achieves correct decoding if the dimension of the space V U is large enough. When the dimension of each codeword is restricted to a fixed integer, the code forms a subset of the vertices of the Grassmann graph. Sphere-packing, sphere-covering bounds and a Singleton bound are provided for such codes. A Reed-Solomon-like code construction is provided and decoding algorithm given.
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coding for errors and erasures in Random Network coding
arXiv: Information Theory, 2007Co-Authors: R Koetter, Frank R. KschischangAbstract:The problem of error-control in Random linear Network coding is considered. A ``noncoherent'' or ``channel oblivious'' model is assumed where neither transmitter nor receiver is assumed to have knowledge of the channel transfer characteristic. Motivated by the property that linear Network coding is vector-space preserving, information transmission is modelled as the injection into the Network of a basis for a vector space $V$ and the collection by the receiver of a basis for a vector space $U$. A metric on the projective geometry associated with the packet space is introduced, and it is shown that a minimum distance decoder for this metric achieves correct decoding if the dimension of the space $V \cap U$ is sufficiently large. If the dimension of each codeword is restricted to a fixed integer, the code forms a subset of a finite-field Grassmannian, or, equivalently, a subset of the vertices of the corresponding Grassmann graph. Sphere-packing and sphere-covering bounds as well as a generalization of the Singleton bound are provided for such codes. Finally, a Reed-Solomon-like code construction, related to Gabidulin's construction of maximum rank-distance codes, is described and a Sudan-style ``list-1'' minimum distance decoding algorithm is provided.
Danilo Silva - One of the best experts on this subject based on the ideXlab platform.
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universal weakly secure Network coding
Information Theory Workshop, 2009Co-Authors: Danilo Silva, Frank R. KschischangAbstract:This paper considers the problem of secure Network coding under the weak (and practically appealing) security requirements of Bhattad and Narayanan. Weak security allows communication at maximum rate while ensuring that only meaningless information is leaked to a wiretapper. Differently from the approach of Bhattad and Narayanan, which requires a joint design of the underlying Network code and the outer security scheme, we propose a universal approach that is completely independent of the Network code. In particular, the field size for linear Network coding operations does not need to be enlarged. The scheme is also compatible with Random Network coding.
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a rank metric approach to error control in Random Network coding
IEEE Transactions on Information Theory, 2008Co-Authors: Danilo Silva, Frank R. Kschischang, R KoetterAbstract:The problem of error control in Random linear Network coding is addressed from a matrix perspective that is closely related to the subspace perspective of Rotter and Kschischang. A large class of constant-dimension subspace codes is investigated. It is shown that codes in this class can be easily constructed from rank-metric codes, while preserving their distance properties. Moreover, it is shown that minimum distance decoding of such subspace codes can be reformulated as a generalized decoding problem for rank-metric codes where partial information about the error is available. This partial information may be in the form of erasures (knowledge of an error location but not its value) and deviations (knowledge of an error value but not its location). Taking erasures and deviations into account (when they occur) strictly increases the error correction capability of a code: if mu erasures and delta deviations occur, then errors of rank t can always be corrected provided that 2t les d - 1 + mu + delta, where d is the minimum rank distance of the code. For Gabidulin codes, an important family of maximum rank distance codes, an efficient decoding algorithm is proposed that can properly exploit erasures and deviations. In a Network coding application, where n packets of length M over F(q) are transmitted, the complexity of the decoding algorithm is given by O(dM) operations in an extension field F(qn).
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a rank metric approach to error control in Random Network coding
Information Theory Workshop, 2007Co-Authors: Danilo Silva, Frank R. Kschischang, R KoetterAbstract:The problem of error control in Random Network coding is considered, and a formulation of the problem is given in terms of rank-metric codes. This formulation allows many of the tools developed for rank-metric codes to be applied to Random Network coding. A Random Network code induces a generalized decoding problem for rank-metric codes in which the channel may supply partial information about the error in the form of erasures (knowledge of an error location not its values) and deviations (knowledge of an error value but not its location).
J C Berengut - One of the best experts on this subject based on the ideXlab platform.
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power law intensity distribution of γ decay cascades nuclear structure as a scale free Random Network
Physical Review Letters, 2021Co-Authors: Keisuke Fujii, J C BerengutAbstract:By modeling the transition paths of the nuclear $\ensuremath{\gamma}$-decay cascade using a scale-free Random Network, we uncover a universal power-law distribution of $\ensuremath{\gamma}$-ray intensity ${\ensuremath{\rho}}_{I}(I)\ensuremath{\propto}{I}^{\ensuremath{-}2}$, with $I$ the $\ensuremath{\gamma}$-ray intensity of each transition. This property is consistently observed for all datasets with a sufficient number of $\ensuremath{\gamma}$-ray intensity entries in the National Nuclear Data Center database, regardless of the reaction type or nuclei involved. In addition, we perform numerical simulations that support the model's predictions of level population density.