A field-programmable gate array (FPGA)-based recurrent wavelet neural network (RWNN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM). First, the structure and operating pri...
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A field-programmable gate array (FPGA)-based recurrent wavelet neural network (RWNN) control system is proposed to control the mover position of a linear ultrasonic motor (LUSM). First, the structure and operating principles of the LUSM are introduced. Since the dynamic characteristics and motor parameters of the LUSM are non-linear and time-varying, an RWNN controller is designed to improve the control performance for the precision tracking of various reference trajectories. The network structure and its on-line learning algorithm using delta adaptation law of the RWNN are described in detail. Moreover, the connective weights, translations and dilations of the RWNN are trained on-line. Furthermore, to guarantee the convergence of the tracking error, analytical methods based on a discrete-type Lyapunov function are proposed to determine the varied learning rates of the RWNN. In addition, an FPGA chip is adopted to implement the developed control algorithm for possible low-cost and high-performance industrial applications. Finally, the effectiveness of the proposed control system is verified by some experimental results.
It is often hard to write programs that are efficient yet reusable. For example, an efficient implementation of Gaussian elimination should be specialized to the structure and known static properties of the input matr...
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It is often hard to write programs that are efficient yet reusable. For example, an efficient implementation of Gaussian elimination should be specialized to the structure and known static properties of the input matrix. The most profitable optimizations, such as choosing the best pivoting or memoization, cannot be expected of even an advanced compiler because they are specific to the domain, but expressing these optimizations directly makes for ungainly source code. Instead, a promising and popular way to reconcile efficiency with reusability is for a domain expert to write code generators. Two pillars of this approach are types and effects. Typed multilevel languages such as MetaOCaml ensure safety and early error reporting: a well-typed code generator neither goes wrong nor generates code that goes wrong. Side effects such as state and control ease correctness and expressivity: An effectful generator can resemble the textbook presentation of an algorithm, as is familiar to domain experts, yet insert let for memoization and if for bounds checking, as is necessary for efficiency. Together, types and effects enable structuring code generators as compositions of modules with well-defined interfaces, and hence scaling to large programs. However, blindly adding effects renders multilevel types unsound. We introduce the first multilevel calculus with control effects and a sound type system. We give small-step operational semantics as well as a one-pass continuation-passing-style translation. For soundness, our calculus restricts the code generator's effects to the scope of generated binders. Even with this restriction, we can finally write efficient code generators for dynamic programming and numerical methods in direct style, like in algorithm textbooks, rather than in continuation-passing or monadic style.
This study presents a new numerical algorithm for fault location on transmission lines. It does not require line parameters, it is settings-free, which is a radical step forward compared to the existing approaches tha...
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This study presents a new numerical algorithm for fault location on transmission lines. It does not require line parameters, it is settings-free, which is a radical step forward compared to the existing approaches that require this information. Line parameters are only approximately constant, they differ as the loading and weather conditions vary;this affects the accuracy of the existing fault location algorithms. Thus, an approach that does not require line parameters would be more robust, accurate, flexible and cost-effective than those approaches that do require line parameter information to determine the location of the fault. This is essential for the fast and secure elimination of faults on transmission lines;consequently, the solution leads to a significant improvement in the quality of the energy supply. The new algorithm is based on the emerging synchronised measurement technology, using synchronised data sampling at both line terminals. The study presents the algorithm derivation and the results of thorough testing using the ATP-EMTP simulations.
Dense deployment of femtocells can cause serious intra-tier interference in femtocell networks. In this paper, a new cooperative interference management approach which allows the femtocell user equipment (FUE) to merg...
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Dense deployment of femtocells can cause serious intra-tier interference in femtocell networks. In this paper, a new cooperative interference management approach which allows the femtocell user equipment (FUE) to merge into cooperative groups, that is, coalitions, for the uplink transmissions in a femtocell network is proposed, so as to reduce the intra-tier interference and improve the system performance. Taking into account the power cost for cooperation, we claim that all the FUEs are impossible to merge together, and we formulate the proposed cooperative problem as a coalitional game in partition form with an externality due to the interference between the formed coalitions. To get the solution, a novel distributed coalition formation algorithm that takes advantage of the characteristics of femtocell network and allows the FUEs to interact and individually decide on which coalitions to participate in is proposed. Furthermore, we analyze the convergence and stability of the proposed algorithm. Simulations are conducted to illustrate the behavior and the performance of the proposed coalition formation algorithm among FUEs. Results show that the proposed algorithm can improve the system performance with much lower complexity than some previously proposed coalition formation algorithms.
Searching and retrieving the demanded correct information is one important problem in networks;especially, designing an efficient search algorithm is a key challenge in unstructured peer-to-peer (P2P) networks. Breadt...
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Searching and retrieving the demanded correct information is one important problem in networks;especially, designing an efficient search algorithm is a key challenge in unstructured peer-to-peer (P2P) networks. Breadth-first search (BFS) and depth-first search (DFS) are the current two typical search methods. BFS-based algorithms show the perfect performance in the aspect of search success rate of network resources, while bringing the huge search messages. On the contrary, DFS-based algorithms reduce the search message quantity and also cause the dropping of search success ratio. To address the problem that only one of performances is excellent, we propose two memory function degree search algorithms: memory function maximum degree algorithm (MD) and memory function preference degree algorithm (PD). We study their performance including the search success rate and the search message quantity in different networks, which are scale-free networks, random graph networks, and small-world networks. Simulations show that the two performances are both excellent at the same time, and the performances are improved at least 10 times.
During the drug development, nonlinear mixed effects models are routinely used to study the drug's pharmacokinetics and pharmacodynamics. The distribution of random effects is of special interest because it allows...
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During the drug development, nonlinear mixed effects models are routinely used to study the drug's pharmacokinetics and pharmacodynamics. The distribution of random effects is of special interest because it allows to describe the heterogeneity of the drug's kinetics or dynamics in the population of individuals studied. Parametric models are widely used, but they rely on a normality assumption which may be too restrictive. In practice, this assumption is often checked using the empirical distribution of random effects' empirical Bayes estimates. Unfortunately, when data are sparse ( like in patients phase III clinical trials), this method is unreliable. In this context, nonparametric estimators of the random effects distribution are attractive. Several nonparametric methods ( estimators and their associated computation algorithms) have been proposed but their use is limited. Indeed, their practical and theoretical properties are unclear and they have a reputation for being computationally expensive. Four nonparametric methods in comparison with the usual parametric method are evaluated. Statistical and computational features are reviewed and practical performances are compared in simulation studies mimicking real pharmacokinetic analyses. The nonparametric methods seemed very useful when data are sparse. On a simple pharmacokinetic model, all the nonparametric methods performed roughly equivalently. On a more challenging pharmacokinetic model, differences between the methods were clearer. (C) 2008 Elsevier B. V. All rights reserved.
In this study, the authors study the relays assignment problem in cooperative wireless networks with self-interested nodes. The authors propose a cooperation mechanism which includes the cooperative relationship forma...
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In this study, the authors study the relays assignment problem in cooperative wireless networks with self-interested nodes. The authors propose a cooperation mechanism which includes the cooperative relationship formation stage and cooperation maintenance stage. The cooperative relationship among the nodes can be modelled as an exchange market game where nodes trade transmission power between each other to obtain diversity gain. The exchange games have a basic assumption that each node conforms to trade agreement so that each agent has the option to trade its good to obtain a better one. In such a game, strict core is considered as individual rational, Pareto optimal and relationship-stable solution. A cooperation cycle formation (CCF) algorithm is proposed to obtain the strict core solution. However, in networks, some deviated nodes may break the cooperation agreement to obtain more utility gain. Such deviated behaviours in the cooperation cycles can totally destroy the cooperation relationship. However, the data transmissions in networks have the repeated element. Hence, based on the cooperative cycle formed by CCF, the authors introduce a repeated game model for cooperation maintenance in the second stage. A dynamic punishment and recover mechanism is proposed to punish the deviated behaviours and recover cooperation.
This article classifies a group of complicated relational calculus queries whose search algorithms run in time O(I Log(d) I + U) and space 0(1), where I and U are the sizes of the input and output, and d is a constant...
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This article classifies a group of complicated relational calculus queries whose search algorithms run in time O(I Log(d) I + U) and space 0(1), where I and U are the sizes of the input and output, and d is a constant depending on the query (which is usually, but not always, equal to zero or one). Our algorithm will not entail any preprocessing of the data. (C) 2002 Elsevier Science (USA).
The authors consider an integrated switching element with a shared buffer memory and a constant hardware delay. This hardware delay is caused by the hardware operations required to process the routing information of i...
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The authors consider an integrated switching element with a shared buffer memory and a constant hardware delay. This hardware delay is caused by the hardware operations required to process the routing information of incoming cells. A general uncorrelated cell arrival process in the switch, an independent and uniform routing process of cells from the inlets to the outlets of the switch and a first-come-first-served queueing discipline are assumed. The performance of the switching element is evaluated by means of an analytical technique based on an extensive use of probability generating functions. Explicit expressions for the probability generating functions, the mean values, the variances and the tail probabilities of the occupancy and the cell delay of the switch are obtained. Numerical examples show that the hardware delay has an important impact on the switch performance.
The numerical algorithm for tracing exact frequency-dependent rays, which makes it possible to trace these rays in arbitrary media is proposed. In addition, a numerical investigation of the properties of rays under co...
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The numerical algorithm for tracing exact frequency-dependent rays, which makes it possible to trace these rays in arbitrary media is proposed. In addition, a numerical investigation of the properties of rays under consideration and comparison of them with the standard ray theory and finite-difference simulation was performed. The results of numerical experiments for a number of models, including the Sigsbee model, containing a salt body of complex shape are presented.
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