Abstract:Smalltalk-80 is the archetypal object-oriented programming language and environment. This paper briefly introduces a formal model of Smalltalk-80. The static and dynamic denotational semantics of Smalltalk-80 are described through the formal model.
Hu Peng , Shi Chunyi , Wang Kehong
Abstract:Flat-structured Problems (FP) are an important class of Cooperative Distributed Problem Solving applications which include speech understanding, vehicle monitoring, transport dispatching and so on. So far, a number of approaches to FPs have been developed such as those in Hearsay-II and DVMT. Most of these approaches use predictions or goals to guide bottom-up problem solving. However, most predictions and goals in these approaches are based on local view of problem solving states. Although the improved architecture of DVMT allowed a high-level view, no explicit algorithm was given. This paper gives an integrated approach to FPs which makes top-down predictions from global problem solving states, guides bottom-up solving by predictions, verifies and modifies predictions by newly-created hypotheses, and guide bottom--up solving once again. This approach not only enhances the directing role of predictions obtained from global problem solving states, but also makes problem solving flexible due to the prediction verification mechanism.
Tian Laisheng , Huang Lianshu , Xia Bin
Abstract:DC is a programming language which supports distributed programming. It is an upward-compatible parallel extension of C. This paper presents design and implementation of DC and its run-time support system in a workstation network. It also provides the test results.
Abstract:Programming language FOPL is a hybrid language which supports functional programming style and object-oriented programming style. In this paper, the type concepts of FOPL are presented. Also, the rules for purity judgement of expressions, typing expressions and equivalence judgement of expressions are discussed. These rules describe the semantics of FOPL on equational logic.
Abstract:Common pumping lemma for regular languages characterizes the necessary condition that a language is regular. This paper gives several necessary and sufficient conditions and common pumping lemma and generalized pumping lemma are obtained as their consequence.
Abstract:In this paper, a new geometric method for solving TS problem is presented.Let n be the number of points in the point set, and m be the number of vertexes in convex hulls of the point set. The time complexity of the algorithm is: the number of computation distance is O(nm), the number of comparisons is O(max(nm,nlogn)) and the number of computation included angle is O(n2/m).
Cheng Xiaochun , Sun Jigui , Liu Xuhua
Abstract:The authors prove 350 theorems of "Principia Mathematica" by a theorem proving system based on generalized resolution. Compared it with traditional resolution,they complement new strategy, avoid self-resolution, and discuss its time and space complexity.
Wu Qiaoquan , Shen Ping , Zhang Defu
Abstract:This paper has presented a method of parallel program design based on task graph and discussed design of task graph. In this paper, the authors develop letter half of the method for choosing topological structure by task graph and mapping parallel algorithm to parallel architecture.
Feng Yucai , Song Enmin , Sun Xiaowei , Liu Hong
Abstract:Layering map image by colour, which is one of important steps for automatical recognizing map image by computer, is researched in this paper. The algorithm for layering is proposed, and some problems about layering efficiency and effect are discussed.Some methods to solve these problems are given. The algorithm has been implemented,and it is ideal.
Zhang Ling , Wu Fuchao , Zhang Bo , Han Mei
Abstract:A new learning algorithm-forward propagation (FP) of multilayered feed-forward neural networks is presented in this paper. The authors show that as an associative memory the network constructed by the FP algorithm has several advantages. (1)Each training sample is an attractive center. (2) The attractive radius of each training sample reaches the maximum. (3) There is no spurious attractive center in the network.(4) The network has minimal number of elements. (5) The order of its learning complexity is optimal. The FP learning algorithm is also an effective synthesis tool, i. e., the network architecture can be constructed during its learning process.