Showing papers in "Information Sciences in 1992"

TL;DR: A representation of gradual inference rules of the form “The more X is F , the more Y is G ” by means of fuzzy sets turns out to be based on a special implication function already considered in multiple-valued logic.

TL;DR: New entropy measures such as higher order fuzzy entropy and hybrid entropy of a set have been introduced and various properties along with their proofs have been included.

TL;DR: By employing equivalence classes from domain partitions, this work defines functional dependencies and normal forms for the fuzzy relational model and extends the corresponding classical definitions.

TL;DR: Feedforward neural networks are proposed as a means of controlling this generality as well as providing the parallel computation necessary for fuzzy logic and it is demonstrated that these networks can learn and extrapolate complex relationships between antecedents and consequents for rules containing single and conjunctive antecedent clauses.

TL;DR: This paper examines one paradigm—problem relaxation by constraint deletion—which has been used to develop many admissible heuristics and introduces the following extension to this methodology: by criticizing the feasibility of a relaxed solution, it arrives at a closer approximation of the solution to the original problem.

TL;DR: A suboptimal but computationally efficient algorithm is developed to solve for the sensor and fusion thresholds sequentially and numerical results are provided to demonstrate the closeness of the solutions obtained by theSuboptimal algorithm to the optimal solutions.

TL;DR: A linguistic recognition system based on approximate reasoning has been described which is capable of handling various imprecise input patterns and of providing a natural decision, thus providing a low rate of misclassification as compared to the conventional two-state system.

TL;DR: This work provides a complete mathematical formulation of the problem of Histogram sharpening and thresholding by minimizing greyness ambiguity using the measures of fuzziness in a set in order that both fuzzy and crisp segmentation result.

TL;DR: A set of algorithms for image segmentation (both fuzzy and nonfuzzy) has been formulated and a relation between the correlation coefficient and the index of fuzziness is theoretically established and experimentally verified.

TL;DR: The present work investigates some additional properties (in the light of both probability theory and fuzzy set theory) of this new entropy definition to ensure its greater range of applications.

TL;DR: An approach to addressing the problem of representing and manipulating typical or default knowledge which has the advantage of also being able to work in environments in which the knowledge is imprecise is suggested.

TL;DR: This work introduces the concept of a fuzzy generalized bi-ideal of a semigroup, and characterize regular semigroups and both intraregular and left quasiregular semig groups in terms of fuzzy generalizedBi-ideals.

TL;DR: An algorithm for automatic ranking of the individual feature importance for pattern recognition problems by evaluating the importance of any subset of features collectively and providing an average feature evaluation index considering all the classes is developed.

TL;DR: The general zookeeper route problem is NP-hard, necessary and sufficient conditions for the existence of a zookeep route are presented, and an O( n 2 ) algorithm is given for the case where P is a simple polygon and the polygons in P ′ are attached to the boundary of P .

TL;DR: The concept of fuzzy congruences on a groupoid and a group is introduced, and fuzzy Congruences On a group in terms of fuzzy normal subgroups are characterized.

TL;DR: It is shown that the formal system for binary decompositions of database relations applies successfully to binary decomPOSitions of probability distributions and graphs too.

TL;DR: Two generalizations of the classical Tower of Hanoi problem 0, i.e., to transfer n discs from one peg to another by a series of legal moves, are considered and some mathematical background is developed to construct simple algorithms that solve problems 1 and 2 correctly and return the minimum number of moves.

TL;DR: It is shown that if the authors represent two consonant belief structures in a commensurate manner then their aggregations are closed with respect to consonance, provided that the additional requirement that the underlying probability distributions satisfy a condition of correlation is imposed.

TL;DR: A class of fuzzy linear regression models, where both input data and output data are fuzzy numbers, is introduced by using the three indices for equalities between fuzzy numbers using linear programming based methods for solving the formulated problems.

TL;DR: Fuzzy sets and fuzzy relations, depending on the situations, can be interpreted either in a conjunctive manner or as subsets of mutually exclusive possible values for variables whose precise values are ill-known (disjunctive view).

TL;DR: Using the four indices for ranking two fuzzy numbers, four types of Pareto optimality are defined, and the relationships among them are examined in detail.

TL;DR: A matrix characterizing a CA is formulated and it is emphasized how group and nongroup CAs are characterized by this matrix, and the discussion of the CA properties connected with length reveals considerable universal behavior shown by the CAs.

TL;DR: It is proved that a fuzzy language is generated by a fuzzy grammar if and only if it is recursively enumerable (that is its set of fuzzy points is recurringly enumerable).

TL;DR: The scale of exponential entropies of order (α, β) is introduced and it is shown that the scale can represent the extent of a probability distribution, i.e. its degree of concentration with regard to a reference measure.

TL;DR: A sufficient condition for reducing the extended relations to four kinds is discussed when fuzzy sets are bounded and normal, and some examples are given to illustrate it.

TL;DR: It has been shown that the new concept of spectral fuzzy sets can be considered as a useful tool for the management of uncertainty since it allows the implementation of soft decisions on the basis of various opinions on membership functions resulting in a band of thresholds with their respective uncertainties.

TL;DR: The main goal is to unify the various possible fuzzy primary representations of a fuzzy ideal to prepare the way for the study of fuzzy nonlinear systems of equations.

TL;DR: This article discusses the use of associative memories for obtaining preliminary parameter estimates for nonlinear systems using LaSalle's inequality for linear systems.

TL;DR: Conditions under which a homomorphic image of a fuzzy normal subgroup is fuzzy normal are investigated and it is proved that a fuzzy subgroup of order p n − 1 of a group ofOrder p n is a fuzzynormal subgroup if p is a prime.

TL;DR: An O( n ) time algorithm for covering a horizontally convex orthogonal polygon with the minimum number of Orthogonal star-shaped polygons with important applications in robotics and pattern recognition is presented.