Image processing using cellular neural networks based on multi-valued and universal binary neurons

Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiple-valued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.An erratum to this article can be found at     

Issues in nonlinear stochastic grey box identification

Grey box identification refers to the practice of identifying dynamical systems in model structures exploiting partial prior information. This contribution reviews a method for stochastic grey box identification and surveys experiences and lessons of applying it to a number of industrial processes. Issues to be addressed include advantages and costs of introducing stochastics into the model, the question of what contribution must be expected from the model designer as opposed to what can be formalized in computer algorithms, and an outlook on future plans to resolve present shortcomings.     

Hierarchical intelligent control with flexible AC transmission systems application

A novel hierarchical intelligent controller configuration is proposed using an artificial neural network as a control-mode classifier in the supervisory level and a set of pre-designed controllers in the lower level. Controller outputs are modified nonlinearly by the classifying signals in a structure resembling one artificial neuron with adaptively changed weights. The lower-level local controllers are implemented using neural networks. An illustrative example of this approach is based on the transient stabilization of a single-machine infinite-bus system studied in Flexible AC Transmission Systems (FACTS) research.     

Two-level optimal output feedback stabilizer design

The paper addresses the design of two-level power system stabilizers using an optimal reduced order model whose state variables are torque angles and speeds. The reduced order model retains their physical meaning and is used to design a two-level linear feedback controller that takes into account the realities and constraints of electrical power systems. The two-level control strategy is used, and a global control signal is generated from the output variables to minimize the effect of interactions. The effectiveness of this controller is evaluated and a multimachine system is given as an example to illustrate the advantages of the proposed method. Responses of the system with a two-level scheme and an optimal reduced order scheme are included for comparative analysis.     

CAL delivery selection criteria and authoring systems

Abstract  In the past, authoring systems have been used to generate computer-assisted learning materials that have often followed the rather restrictive programmed learning format. A number of innovative ways of using recently developed systems to develop CAL packages that include a wider range of learning activities (access to data bases, simulations, interactive video, etc.) are described. Analogous to the concept of a media selection model, a computer delivery mode selection model is presented as an aid to decision making for designers. This increase in flexibility should broaden the applicability of computerassisted learning (CAL) to a wider range of educational objectives and raise the level of the cognitive emphasis in learning packages, as well as facilitate the implementation of visually appealing materials. The paper also implies a standard of acceptability for authoring systems.     

大学英语读写课堂教师提问的逻辑性调查分析

教师提问、学生回答是语言课堂中的一个逻辑过程。教师的提的问题和课堂模式具有逻辑艺术,与学生产生思维共振,教与学才能统一。通过对大学英语读、写、译课堂观摩调查结果的分析,提出重视课堂提问的逻辑性,让学习者开动脑筋把注意力从学什么转移到怎样学和怎样思考的问题上,从而提高语言学习者的学习能力、理解能力和表达能力。     

互文性视角下的杨译《红楼梦》典故的翻译策略

《红楼梦》中有大量的典故,充满着丰富的互文性。翻译过程中的互文指涉蕴含着深厚的历史文化沉淀。从互文性角度探讨杨宪益、戴乃迭夫妇所译《红楼梦》中典故翻译。认为译者充分发挥了主体性,把保留原语互文关系和文化特色放在首位,这对提高翻译质量和更好地传递典故的文化内涵有着重要的作用。     

提高高等学校课堂教学有效性的应对策略

探讨高等学校课堂教学现状,分析存在的问题,找寻其中原因,提出应对策略：学生提高自我管理能力、转变学习方法、明确学习目的和增加专业认同感;教师端正教学态度、改变教学方法、提高教学能力;学校实行样本课程、完善教学基础设施、健全和改革学生和教师评价制度等.