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世界著名神经元网络专家、神经元网络创始人之一,美国科学院士、加州理工学院计算与神经系主任、化学及生物学教授John J. Hopfield博士,应我国863高技术计划智能计算机专家组和南京航空学院的联合邀请,在南航作了为期2.5周“人工神经网络”讲座。Hopfield教授系统地讲授了神经网络基本原  相似文献   

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Possibility distribution introduced by Zadeh ["Fuzzy sets as a basis for a theory of possibility theory", Fuzzy Sets Syst. 1 (1978) 3-28] in his introductory paper of possibility theory assumes a normal distribution, in the sense that it supposes the existence of at least one element s 0 of the universe of discourse U , for which the distribution ~ is fully compatible with the context of interest: ~ (s 0 )=1. However, when such element does no longer exist, it leads to a subnormal possibility distribution. This situation may arise from incomplete data, inconsistent statements, or contradictory beliefs. To deal with such case, many authors like Yager ["On the relationships of methods of aggregation evidence in expert systems", Cybern. Syst. , 16 (1985) 1-21; "A modification of the certainty measure to handle subnormal distributions", Fuzzy Sets Syst. , 20 (1986) 317-324], Dubois and Prade ["An alternative approach to the handling of subnormal possibility distributions--A critical comment on a proposal of Yager", Fuzzy Sets Syst. , 24 (1987) 123-126] have put forward some proposals in order to keep track of the consistency of the basic axioms attached to possibility and necessity measures. In this paper, the proposals are reviewed in the light of new results regarding some appealing criteria. Particularly, when subnormal distribution and normal distribution are encountered in the same level, intuitively, two approaches are possible: Either the subnormal distributions are risen up to a normal distribution level, or the normal ones are flatted down to agree with the normal ones. In both cases there is a sort of gaining or losing information. We review some of the proposal solutions. The flatting approach is mainly related to fuzzy arithmetic calculus while the rising effect is motivated by Dempster-Shafer theory of evidence and its normalization paradigm. The two approaches will also be investigated with respect to some appealing criteria like preference preservation, distance minimization, entropy, minimum/maximum specificity, and, further, particular interest is focused on information based uncertainty preservation. Later on, the proposals are discussed according to the f -certainty qualification where the greatest value h of the subnormal distribution is understood as a degree of certainty that must be attached to the resulting normal distribution.  相似文献   

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你喜欢随身携带哪种机器?这一问题随着新的轻便型个人电脑在今年进入市场而变得更加复杂了。对于那些带着便携机经常四处奔波的人来说,更小、更轻的设备——即我们曾经说过的个人数字助理(PDAs),其历史可以追溯到Apple的Newton造成巨大轰动的年代——是一种奢望。但当时那些设备的用途与现在的差别甚大,而且只能提供很少  相似文献   

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宋斐 《互联网周刊》2003,(20):20-22
很多人觉得,沉稳、踏实的风格其实正是企业管理软件的用户所需要的,他们不喜欢冒险,他们更喜欢一个多年以来都在持续、稳定地专注于这一领域的厂商,比如J.D.Edwards。  相似文献   

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E.J.戴维森教授是加拿大皇家科学院院士,多伦多大学电子工程系系统控制室主任,IEEE的会士(Fellow),1983年度IEEE自动控制杂志总编辑。 他1938年出生于加拿大多伦多市,1957年毕业于多伦多皇家音乐学校(钢琴),1960年取得多伦多大学工程物理学学士,1961年取得该大学应用数学硕士,1964年在英国剑桥大学获得控制工程博士学位(Ph.D.),1977年荣获该校的科学博士(Sc.D.)。  相似文献   

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《Ergonomics》2012,55(10):1254-1255
This study aimed to examine the effects of passive and non-computer work time on the estimation of computer use times by electronic activity monitoring. A total of 20 subjects with computers were monitored for 3 h. Average relative error for total computer use time estimation was about 4%, given that non-computer work time was 20% of the 3-h monitored period. No significant impact of passive computer use time was found in this study. Non-computer work time of 40% or less is suggested as criteria for the application of electronic activity monitoring to ensure reliability in the physical work loading assessment.

Statement of Relevance: This research studied the criteria of non-computer work time for the appropriate use of electronic activity monitoring to ensure reliability in the assessment of physical work loading. It is suggested that it should be set to 40% or less of the 3-h monitoring period.  相似文献   

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陈玉 《机器人》1981,3(4):63-63
美国斯坦福研究所人工智能中心主任N.J尼尔逊博士应中国科学院沈阳自动化研究所邀请于今年九月份来我国访问。本文对美国斯坦福研究所人工智能中心和N.J尼尔逊博士做一简要介绍。 尼尔逊博士1933年生于美国密执安州。  相似文献   

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The paper presents new refinements of homomorphisms that are needed in order to deal with partial algebraic systems; namely, weak, strong and Very strong homomorphisms and the laws of their compositions. Further, it describes loose and tight congruences and the canonical factorization of various kinds of homomorphisms. The results have important applications in cognitive modelling, general systems relational models, knowledge representation schemes in Expert Systems and formal methods of Software Engineering,  相似文献   

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