Showing papers in "Information Sciences in 1994"

TL;DR: If the graph G is formed from G1 and G2 by one of the operations of Cartesian product, composition, union, and join, then necessary and sufficient conditions for an arbitrary fuzzy subgraph of G also to be formed by the same operation from fuzzy sub graphs of G2.

TL;DR: This model aims to solve each problem of representation and handling of fuzzy information taking into account its specific nature, and hence it allows the user to choose the comparison operator and the fuzzy compatibility measure to be used in a query.

TL;DR: A genetic algorithm that can automatically generate test cases to test a selected path and a fitness function named SIMILARITY is defined to determine which test cases should survive if the final test case has not been found.

TL;DR: This work proposes to decompose the overall task to fit in the behavior-based control architecture, and then to evolve the separate behavior modules and arbitrators using an evolutionary approach, so the job of defining fitness functions becomes more straightforward and the tasks easier to achieve.

TL;DR: It is proved that a special class of fuzzy normal subgroups constitutes a modular sublattice of the lattice of fuzzy subgroups of a given group.

TL;DR: A new approach to study fuzzy group theory is given using the concept of fuzzy space and fuzzy binary operation, which can be considered as a generalization and reformulation of the Rosenfeld theory of fuzzy subgroups.

TL;DR: The asymptotic stability of the proposed neural networks and solvability of simultaneous linear equations by using the neural networks are substantiated and an extension of the recurrent neural networks for solving quadratic programming problems subject to equality constraints is discussed.

TL;DR: An attempt to demonstrate genetic algorithms effectiveness to search a global optimal solution to select a decision boundary for a pattern recognition problem using a multilayer perceptron using a new concept of nonlinear selection for creating mating pools and a weighted error as a fitness function.

TL;DR: The problem formulation suggested in this paper constitutes a realistic framework for estimation problems with geographically dispersed sensors such as the multiple sensor tracking problem.

TL;DR: Directed mutation deterministically introduces new points in the population guided by the information acquired in the previous generations by expediting the algorithm using an acceleration function which can be based on gradient or extrapolation.

TL;DR: The notion of fuzzy orders of the elements of a group is introduced and it is shown that most of the basic properties of orders of elements in the group theory are valid in the theory of fuzzy groups.

TL;DR: It is shown that the time concept event time is needed to correctly model retroactive and proactive updates, as it is not possible to model them using only the valid and transaction times as thought earlier.

TL;DR: A learning algorithm is proposed and it is shown that it enables perfect learning provided the training set forms a consistent conceptual structure and the set of all stable points forms a complete lattice.

TL;DR: This paper evaluates four Time Warp memory management algorithms: fossil collection, message sendback, cancelback and artificial rollback and shows that if an algorithm satisfies this second criterion, then the amount of memory consumed by Time Warp simulation is bounded by the amount consumed by sequential simulation.

TL;DR: It is proved that every lattice L of finite length can be represented by a fuzzy set on the collection X of meet-irreducible elements of L, and the representation theorem for a finite distributive lattice by the lattice of all isotone functions is obtained.

TL;DR: It is found that the Backpropagation algorithm is much more computation-intensive than the Kak algorithms that have comparable generalization performance.

TL;DR: An attempt is made to demonstrate the ability of fuzzy versions of Kohonen's net and the multilayer perceptron for classification of certain linearly nonseparable pattern classes with nonconvex decision regions.

TL;DR: A new Cartesian product approach to conditional events is taken and the result is a full Boolean algebra (or (σ-algebra) setting for all results)—unlike the essential non-Boolean character of the former approach.

TL;DR: It is proved that this maximum entropy approach to the fuzzy case leads to maximally stable controls, if, instead of maximizing, the authors minimize entropy, they get maximally smooth controls.

TL;DR: Three genetic algorithms are proposed, developed specifically for the task of training layered feedforward neural networks, that use an adaptive technique which takes advantage of the network architecture.

TL;DR: An adaptive system based on fuzzy logic that can refine its representation of a region in the phase space if that region requires it, and does so by adaptively generating more fuzzy rules to model a region onlyif that region has very violent dynamics.

TL;DR: The SDG is further extended so that it handles a grammar with additional constructs and a new method is described to calculate the transitive dependences and therefore build the SDG, which is based on a parse tree instead of statements.

TL;DR: The model of choice in which the option estimation is given as a utility function and the error function is dependent on a feasible set of options is studied, and corresponding choice functions are studied in terms of pseudocriteria.

TL;DR: Numerical results in the Gaussian channel indicate that for two sensors and under the imposed assumptions, only the OR combining rule at the fusion results in performance that degrades gracefully as the coverage factor decreases.

TL;DR: This problem will be formalized as a special fuzzy sequential decision problem to which it is possible to extend the Bayes nonfuzzy decision procedures when the Bayesian framework is assumed.

TL;DR: The proposed measure of fuzzy subsethood bears the information of similarity of two fuzzy messages in the n -cube space besides the subsethood, which leads to a fuzzy version of Bayesian's theorem.

TL;DR: Continuity of the entropy and attaining the minimum entropy are proved in the case where the mixture is finite, and new results concerning the entropy lower bound are derived.

TL;DR: An innovative approach for dynamically analyzing a user's dialog behavior and inferring a users' domain knowledge level simultaneously that combines neural networks, fuzzy cognitive maps, and fuzzy production rules is proposed.

TL;DR: This work presents a logical query language permitting the formulation of structural queries over hyperdocuments, based on prepositional modal logic and admits a simple and efficient implementation over available hypermedia storage systems.

TL;DR: This work considers the LQG problem in systems with discrete time and continuous time dynamics in the presence of fixed delays in the transmission of measurements and control actions and derives the optimal estimator and controller in a recursive form for both cases.