用基于叠层元的h－p方式自适应有限元计算磁场问题（Ⅱ）

本文是文献［１］的继续。针对二维恒定磁场的边值问题，通过一系列模型题的计算，得到自适应有限元计算时估计误差和实际误差的关系曲线；使得不存在解析解的工程问题，只要算出估计误差，即可由此确定实际误差的值，从而解决了工程上普遍关心的有限元磁场计算的精度问题，为设计和研究工作提供了可靠的依据。     

一种机器人的自适应控制

针对机器人的动态模型,提出一种自适应控制方法,它不但可以消除参数不确定和各关节之间的耦合作用,而且也保证了整个系统的收敛性。整个控制器分为两部分:一是常规控制,用于将机器人的实际运动轨迹控制在期望轨迹的某一邻域、一是自适应控制,用于清除伺误差,并强迫实际运动以渐近方式趋于期望轨迹。计算机仿真的结果用来讨论了在不同环境条件下的系统性能。     

通信自适应干扰对消系统的性能分析

文章对现在的通信自适应干扰对消系统，进行了详细的性能分析，找出了单级的对消系统的对消比不能提高的原因，在此基础上提出了用级联的对消方式来提高对消比。     

参数有约束系统的自适应控制

在脑颅抽液系统中,我们可以把系统描写为自回归滑动平均模型,而该模型的参数是约束在一个超平面上的.本文给出了参数有约束系统的识别公式,讨论了参数有约束系统识别的收敛性,给出了参数有约束系统的自适应控制的一种算法.     

VLSI Implementation of Fuzzy Adaptive Resonance and Learning Vector Quantization

We present a mixed-mode VLSI chip performing unsupervised clustering and classification, implementing models of Fuzzy Adaptive Resonance Theory (ART) and Learning Vector Quantization (LVQ), and extending to variants such as Kohonen Self-Organizing Maps (SOM). The parallel processor classifies analog vectorial data into a digital code in a single clock, and implements on-line learning of the analog templates, stored locally and dynamically using the same adaptive circuits for on-chip quantization and refresh. The unit cell performing fuzzy choice and vigilance functions, adaptive resonance learning and long-term analog storage, measures 43 m×43 m in 1.2 m CMOS technology. Experimental learning results from a fabricated 8-input, 16-category prototype are included.     

遗传算法中交叉和变异概率选择的自适应方法及作用机理

在指出了传统遗传算法中交叉和变异概率的选择具有盲目性的基础上, 提出了遗传算法中交叉和变异概率选择的改进措施, 对其作用机理进行了深入的分析, 指出改进算法体现了自适应策略. 用一个非常复杂的数学函数对新算法进行了测试, 结果表明改进算法克服了传统遗传算法难以解决的早熟和局部收敛的问题.     

Adaptive robust control of nonholonomic systems with stochastic disturbances

Based on the Brockett’s necessary condition for feedback asymptotic stabilization[1], nonholonomic systems fail to be stabilized at the origin by any static continuous state feedback though they are open loop controllable. There are two novel approaches …     

Convergence analysis of cautious control

~~Convergence analysis of cautious control1 Goodwin G C, Sin, K S. Adaptive Filtering, Prediction and Control. Englewood Cliffs, NJ: Prentice Hall, 1984 2 Cains P E. Linear Stochastic Systems. New York: Wiley, 1988 3 Astrom K J, Wittenmark B. Adaptive…     

Addressing spatiotemporal and computational heterogeneity in structured adaptive mesh refinement

Structured adaptive mesh refinement (SAMR) techniques can provide accurate and cost- effective solutions to realistic scientific and engineering simulations modeling complex physical phenomena. However, the adaptive nature and inherent space–time heterogeneity of SAMR applications result in significant runtime management challenges. Moreover, certain SAMR applications involving reactive flows exhibit pointwise varying workloads and cannot be addressed by traditional parallelization approaches, which assume homogeneous loads. This paper presents hierarchical partitioning, bin-packing based load balancing, and Dispatch structured partitioning strategies to manage the spatiotemporal and computational heterogeneity in SAMR applications. Experimental evaluation of these schemes using 3-D Richtmyer–Meshkov compressible turbulence and 2-D reactive-diffusion kernels demonstrates the improvement in overall performance.     

Adaptive learning of fuzzy BSB and GBSB neural models

This article deals with a special class of neural autoassociative memory, namely, with fuzzy BSB and GBSB models and their learning algorithms. These models defined on a hypercube solve the problem of fuzzy clusterization of a data array owing to the fact that the vertices of the hypercube act as point attractors. A membership function is introduced that allows one to classify data that belong to overlapping clusters. __________ Translated from Kibernetika i Sistemnyi Analiz, No. 6, pp. 18–28, November–December 2006.