The architecture of a field-programmable gate-array (FPGA) implementation of a low-density parity-check (LDPC) decoder for the Digital Video Broadcasting - Second Generation via Satellite (DVB-S2) standard is presente...
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The architecture of a field-programmable gate-array (FPGA) implementation of a low-density parity-check (LDPC) decoder for the Digital Video Broadcasting - Second Generation via Satellite (DVB-S2) standard is presented. algorithms are devised to systematically apply the values given in DVB-S2 to implement a memory mapping scheme, which allows for 360 functional units (FUs) to be used in decoding and supports both normal and short frames. A design of a parity-check module (PCM) is presented that verifies the parity-check equations of the LDPC codes. Furthermore, a special characteristic of five of the codes defined in DVB-S2 and their influence on the decoder design is discussed. Two versions of the LDPC decoder are synthesized for two families of FPGAs. The results show that the decoder presented uses fewer hardware resources than a DVB-S2 LDPC decoder found in the current literature that also uses FPGA, while improving the maximum frequency of the decoder. Crown Copyright (C) 2011 Published by Elsevier Ltd. All rights reserved.
We show in this paper that the BGS model of abstract state machines can be simulated by random access machines with at most a polynomial time overhead. This result is already stated in [5] with a very brief proof sket...
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We show in this paper that the BGS model of abstract state machines can be simulated by random access machines with at most a polynomial time overhead. This result is already stated in [5] with a very brief proof sketch. The present paper gives a detailed proof of the result. We represent hereditarily finite sets, which are the typical BGS ASM objects, by membership graphs of the transitive closure of the sets. Testing for equality between BGS objects can be done in linear time in our representation.
This paper is a study on the hybrid position/force control of a two-fingered miniature gripper driven by piezoelectric bimoph cells. The system is composed of the flexible cantilevers and a compact force sensor attach...
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This paper is a study on the hybrid position/force control of a two-fingered miniature gripper driven by piezoelectric bimoph cells. The system is composed of the flexible cantilevers and a compact force sensor attached to the tip of one finger. Control action is applied by two piezoelectric bimorph strips placed at the base of each finger. The theoretical model of the electro-mechanical system is developed and applied to the study of a control problem where the gripper is commanded to grasp its object with a time-constant force 0.01 N at a prescribed commanded fingertip position. The PID control algorithm is introduced to drive the gripper. The system control behaviour is examined both theoretically and experimentally.
Default unification operations combine strict information with information from one or more defeasible feature structures. Many such operations require finding the maximal subsets of a set of atomic constraints that a...
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Default unification operations combine strict information with information from one or more defeasible feature structures. Many such operations require finding the maximal subsets of a set of atomic constraints that are consistent with each other and with the strict feature structure, where a subset is maximally consistent with respect to the subsumption ordering if no constraint can be added to it without creating an inconsistency. Although this problem is NP-complete, there are a number of heuristic optimizations that can be used to substantially reduce the size of the search space. In this article, we propose a novel optimization, leaf pruning, which in some cases yields an improvement in running time of several orders of magnitude over previously described algorithms. This makes default unification efficient enough to be practical for a wide range of problems and applications.
This paper is concerned with the distributed H-infinity-consensus control problem over the finite horizon for a class of discrete time-varying multi-agent systems with random parameters. First, by utilizing the propos...
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This paper is concerned with the distributed H-infinity-consensus control problem over the finite horizon for a class of discrete time-varying multi-agent systems with random parameters. First, by utilizing the proposed information matrix, a new formula is established to calculate the weighted covariance matrix of random matrix. Next, by allowing every agent to track the average of the neighbor agents, a novel local H-infinity-consensus performance constraint is presented to cater to the local performance analysis. Then, by means of the proposed definition of the stochastic vector dissipativity-like over the finite horizon, a set of sufficient conditions for every agent is obtained such that the controlled outputs of the closed-loop multi-agent systems satisfy the proposed H-infinity-consensus performance constraint. As a result, the proposed consensus control algorithm can be executed on each agent in an indeed distributed manner. Finally, a simulation example is employed to verify the effectiveness of the proposed algorithm. (C) 2017 Published by Elsevier Ltd on behalf of The Franklin Institute.
The ability to identify the fault type and to locate the fault in extra high voltage transmission lines is very important for the economic operation of modern power systems. Accurate algorithms for fault classificatio...
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The ability to identify the fault type and to locate the fault in extra high voltage transmission lines is very important for the economic operation of modern power systems. Accurate algorithms for fault classification and location based on artificial neural network are suggested in this paper. Two fault classification algorithms are presented;the first one uses the single ANN approach and the second one uses the modular ANN approach. A comparative study of two classifiers is done in order to choose which ANN fault classifier structure leads to the best performance. Design and implementation of modular ANN-based fault locator are presented. Three fault locators are proposed and a comparative study of the three fault locators is carried out in order to determine which fault locator architecture leads to the accurate fault location. Instantaneous current and/or voltage samples were used as inputs to ANNs. For fault classification, only the pre-fault and post-fault samples of three-phase currents were used. For fault location, pre-fault and post-fault samples of three-phase currents and/or voltages were used. The proposed algorithms were evaluated under different fault scenarios. Studied simulation results which are presented confirm the effectiveness of the proposed algorithms.
A command sequence replanning and control method, which enables the slave system to autonomously recover from error conditions, is proposed in a telerobot system. A task model described as a form of the controlled Pet...
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A command sequence replanning and control method, which enables the slave system to autonomously recover from error conditions, is proposed in a telerobot system. A task model described as a form of the controlled Petri net (CPN) is used as a prior knowledge for the slave system to carry out the given task successfully without the operator's aid even in unexpected error conditions. The CPN model incorporates the contact states and transitional motions between them that possibly exist in the task execution process. The motion command is automatically generated from the master system and transmitted to the slave whenever the contact state changes in the master model. Referring to the CPN model and the given motion commands, the slave system detects if the actual contact state is unexpected and then plans the recovery path from the unexpected state. The feasibility of the command sequence replanning and control algorithm is verified through an example to perform a simple part-mating task. (C) 2001 John Wiley & Sons, Inc.
The applicability of term rewriting to program transformation is limited by the lack of control over rule application and by the context-free nature of rewrite rules. The first problem is addressed by languages suppor...
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The applicability of term rewriting to program transformation is limited by the lack of control over rule application and by the context-free nature of rewrite rules. The first problem is addressed by languages supporting user-definable rewriting strategies. The second problem is addressed by the extension of rewriting strategies with scoped dynamic rewrite rules. Dynamic rules are defined at run-time and can access variables available from their definition context. Rules defined within a rule :,cope are automatically retracted at the end of that scope. In this paper, we explore the design space of dynamic rules, and their application to transformation problems. The technique is formally defined by extending the operational semantics underlying the program transformation language Stratego, and illustrated by means of several program transformations in Stratego, including constant propagation, bound variable renaming, dead code elimination, function inlining, and function specialization.
To identify multiple acoustic duct modes, conventional beam-forming, CLEAN as well as L-2 (i.e. pseudo-inverse) and L-1 generalized-inverse beam-forming are applied to phased-array pressure data A tone signal of a pre...
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To identify multiple acoustic duct modes, conventional beam-forming, CLEAN as well as L-2 (i.e. pseudo-inverse) and L-1 generalized-inverse beam-forming are applied to phased-array pressure data A tone signal of a prescribed mode or broadband signal is generated upstream of a curved rectangular duct, and acoustic fields formed in both upstream and downstream stations of the test section are measured with identical wall mounted microphone arrays. Sound power distributions of several horizontal and vertical modes including upstream- and downstream propagating waves can be identified with phased array techniques, and the results are compared among the four approaches. The comparisons using synthetic data demonstrate that the L-2 generalized inverse algorithm can sufficiently suppress undesirable noise levels and detect amplitude distributions accurately in over determined cases (i.e. the number of microphones is more than the number of cut on modes) with minimum computational cost. As the number of cut on modes exceeds the number of microphones (i.e. under-determined problems), the L-1 algorithm is necessary to retain better accuracy. The comparison using Lest data acquired in the curved duct Lest rig (CDTR) at NASA Langley Research Center suggests that the L-1/L-2 generalized-inverse approach as well as CLEAN can improve the dynamic range of the detected mode by as much as 10 dB relative to conventional beam-forming even with mean flow of M=05. (C) 2015 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.
The purpose of this paper is to present a sliding mode control method that can be used to perform a spacecraft large angle maneuver with minimum time. An algorithm of minimum-time SMC is developed to provide the robus...
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The purpose of this paper is to present a sliding mode control method that can be used to perform a spacecraft large angle maneuver with minimum time. An algorithm of minimum-time SMC is developed to provide the robust tracking control. The simulation results are compared with previous developed control schemes, eigenaxis quaternion regulator, to demonstrate the superiority of the proposed sliding mode control algorithm. (C) 2003 Elsevier Ltd. All rights reserved.
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