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Learning a sequence of target locations when the sequence is uncorrelated with a sequence of responses and target location is not the response dimension (pure perceptual-based sequence learning) was examined. Using probabilistic sequences of target locations, the author shows that such learning can be implicit, is unaffected by distance between target locations, and is mostly limited to first-order transition probabilities. Moreover, the mechanism underlying learning affords processing of information at anticipated target locations and appears to be attention based. Implications for hypotheses of implicit sequence learning are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved) 相似文献
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In this paper, a feedback model predictive control method is presented to tackle control problems with constrained multivariables for uncertain discrete‐time nonlinear Markovian jump systems. An uncertain Markovian jump fuzzy system (MJFS) is obtained by employing the Takagi‐Sugeno (T‐S) fuzzy model to represent a discrete‐time nonlinear system with norm bounded uncertainties and Markovain jump parameters. To achieve more generality, the transition probabilities of the Markov chain are assumed to be partly unknown and partly accessible. The predictive formulation adopts an on‐line optimization paradigm that utilizes the closed‐loop state feedback controller and is solved using the standard semi‐definite programming (SDP). To reduce the on‐line computational burden, a mode independent control move is calculated at every sampling time based on a stochastic fuzzy Lyapunov function (FLF) and a parallel distributed compensation (PDC) scheme. The robust mean square stability, performance minimization and constraint satisfaction properties are guaranteed under the control move for all admissible uncertainties. A numerical example is given to show the efficiency of the developed approach. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献
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Bo-Chao Zheng 《International journal of systems science》2014,45(10):1999-2011
In this paper, based on sliding mode control approach, the robust stabilisation problem for a class of continuous-time Markovian jump linear uncertain systems with partly unknown transition rates is investigated. The transition rate matrix under consideration covers completely known, boundary known and completely unknown elements. By making use of linear matrix inequalities technique, sufficient conditions are presented to derive the linear switching surface and guarantee the stochastic stability of sliding mode dynamics. Then a sliding mode control law is designed to drive the state trajectory of the closed-loop system to the specified linear switching surface in finite time in spite of the existing uncertainties and unknown transition rates. Finally, an example is given to verify the validity of the theoretical results. 相似文献
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Device-to-Device (D2D) communication can reduce the mobile devices' energy consumption and increase the spectral efficiency in D2D underlaid cellular networks. However, D2D users will interfere with co-channel cellular users, which can lead to cellular communication access failures. There are two reasons for cellular communication access failures: (1)D2D interference and (2)insufficient spectrum resources. To address the absence of research on the performance of cellular services' access in D2D underlaid cellular networks, this paper defines the new services' access failure probability and handoff services' access failure probability to evaluate the effect of both D2D interference and limited resources on cellular communication access. Based on the stochastic geometry and stochastic process, a random network model is presented to estimate the access failure probabilities, which can provide guidelines for network design to ensure cellular services' access. The accuracy of the estimated access failure probability is validated through extensive simulations. 相似文献
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Exponential stability of stochastic singular delay systems with general Markovian switchings 下载免费PDF全文
In recent years, Markovian jump systems have received much attention. However, there are very few results on the stability of stochastic singular systems with Markovian switching. In this paper, the discussed system is the stochastic singular delay system with general transition rate matrix in terms of uncertain and partially unknown transition rate matrix. The aim is to answer the question whether there are conditions guaranteeing the underlying system having a unique solution and being exponentially admissible simultaneously. The proposed results show that all the features of the underlying system such as time delay, diffusion, and general Markovian switchings play important roles in the system analysis of exponential admissibility. A numerical example is used to demonstrate the effectiveness of the proposed methods. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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This article addresses the output feedback control for discrete‐time Markov jump linear systems. With fully known transition probability, sufficient conditions for an internal model based controller design are obtained. For the case where the transition probabilities are uncertain and belong to a convex polytope with known vertices, we provide a sufficient LMI condition that guarantees the norm of the closed‐loop system is below a prescribed level. That condition can be improved through an iterative procedure. Additionally, we are able to deal with the case of cluster availability of the Markov mode, provided that some system matrices do not vary within a given cluster, an assumption that is suitable to deal with packet dropout models for networked control systems. A numerical example shows the applicability of the design and compares it with previous results. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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提出一种基于词内部模式的新词识别算法,该算法在重复串查找的基础上,结合词内部模式的特征提出改进位置成词概率和首尾单字成词概率的加权,依次判断互信息、邻接类别等统计量,对新词进行识别。通过不同的实验对比发现,该算法在一定程度上能有效提取新词。 相似文献