We propose a simulation-based method in the verification of SoC bus system. By the method, constrained-random vector is used to make simulation first;then a coverage analysis is made in the simulation process until a ...
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We propose a simulation-based method in the verification of SoC bus system. By the method, constrained-random vector is used to make simulation first;then a coverage analysis is made in the simulation process until a certain coverage statistics is obtained. Finally, the test vector is manually generated. We use this method to verify a SoC system and get a satisfactory result by reducing the time of simulation effectively.
The translation of inheritance nets to default logic has been discussed by Etherington[9],Touretzky[10],*** and inheritance nets are similar in some aspects and based on methods of translating inheritance nets to defa...
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The translation of inheritance nets to default logic has been discussed by Etherington[9],Touretzky[10],*** and inheritance nets are similar in some aspects and based on methods of translating inheritance nets to default logic,a translation of ontologies to default logic with a priority order on defaults is ***,properties of an ontology and the revision of ontologies can be studied in terms of default *** are assumed to be trees under the subsumption relation between concepts and have deduction rules to infer what are not explicitly *** statements in ontologies are translated to facts of default theories of the ontologies and the default inheritance of properties are represented by normal defaults with a priority order on them due to the intuition that subclasses overriding *** an ontology with a tree structure,it is consistent if and only if the default theory of the ontology has a unique extension.
The optimal partition algorithm (OPA) is applied to the training of parameters in the radial basis function (RBF) neural network. The appropriate modification for the OPA is performed according to the characteristics ...
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The optimal partition algorithm (OPA) is applied to the training of parameters in the radial basis function (RBF) neural network. The appropriate modification for the OPA is performed according to the characteristics of the RBF neural network. The approach for determining the centers and widths of the clustering is added in the modified OPA and applied to choose the centers and widths of the neural network. A method for adjusting the structure of the neural network dynamically is presented by using the difference of the objective functions of the clustering. Thus it is realized to select the number of the hidden nodes adaptively. Simulation results of the stock price prediction demonstrate the effectiveness of the proposed approach. Comparisons with traditional algorithms show that the proposed OPA method possesses obvious advantages in the precision of forecasting, generalization, and forecasting trends. Simulations also show that the algorithm combining the OPA with the orthogonal least squares (OLS) possesses more superior performance in the rightness of forecasting trends.
A formal representation of ontologies is proposed, based on F-logic and O-logic; and the works in the building of ontologies in NKI. An ontology includes class frames, slot frames, class-slot frames, object frames and...
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A formal representation of ontologies is proposed, based on F-logic and O-logic; and the works in the building of ontologies in NKI. An ontology includes class frames, slot frames, class-slot frames, object frames and axioms. The value restrictions of slots are defined in slot frames. For each slot and each class, there is a class-slot frame representing the specific value restrictions of the slot when defining the class; and the relations between class-slot frames and slot frames are discussed. For a slot in a class frame, its values are inherited to its subclasses without blocking; and its default values are inherited to its subclasses taking overriding, revising and conflict resolution into account. After giving the formal representation of ontologies, the semantics of ontologies are discussed, and main results are presented.
Fuzzy cognitive maps (FCMs) can represent and reason causal knowledge with stronger semantics. And the causal knowledge widely exists in knowledge grid. To provide information services with stronger semantics in Knowl...
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Fuzzy cognitive maps (FCMs) can represent and reason causal knowledge with stronger semantics. And the causal knowledge widely exists in knowledge grid. To provide information services with stronger semantics in Knowledge Grid, we need to know the reasoning mechanism and the characteristics of FCMs. In this paper, we have proved that the reasoning process of FCMs is a discrete topological semi- dynamic system. This theory can help us analyze the reasoning process and find the new characteristics of FCMs, which can guide us using FCMs to provide intelligent information services flexibly in knowledge Grid.
Three kinds of constrained traveling salesman problems (TSP) arising from application problems, namely the open route TSP, the end-fixed TSP, and the path-constrained TSP, are proposed. The corresponding approaches ba...
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Three kinds of constrained traveling salesman problems (TSP) arising from application problems, namely the open route TSP, the end-fixed TSP, and the path-constrained TSP, are proposed. The corresponding approaches based on modified genetic algorithms (GA) for solving these constrained TSPs are presented. Numerical experiments demonstrate that the algorithm for the open route TSP shows its advantages when the open route is required, the algorithm for the end-fixed TSP can deal with route optimization with constraint of fixed ends effectively, and the algorithm for the path-constraint could benefit the traffic problems where some cities cannot be visited from each other.
Grid computing presents a new trend to distributed computation and Internet applications, which can construct a virtual single image of heterogeneous resources, provide uniform application interface and integrate wide...
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The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector ma...
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The use of computational-intelligence-based techniques in the optimization of agent initial positions in land combat simulations is studied. A novel method for the reduction of support vectors in the support vector machine (SVM) is presented. The optimization on the width of the Gaussian kernel function and the combination of the SVM with the radial basis function neural network are performed in the proposed method. Simulation results show that the proposed method can improve the running efficiency drastically compared with that using the traditional SVM with the same precision. We also summarize and present some experiences and trends in the study on the optimization problem in land combat simulation.
An operation template is proposed in this paper for describing the mapping between operations and a subset of natural numbers. With such operation template, a job shop scheduling problem (JSSP) can be transformed into...
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