Results 211 to 220 of about 28,445 (248)

Applying fuzzy logic to codesign partitioning

IEEE Micro, 1997
We propose a tool that will allow designers using the codesign approach to partially automate the development of embedded systems. The framework takes advantage of tools already available on the market for VLSI CAD as well as soft computing techniques.
CATANIA, Vincenzo, MALGERI, Michele Giuseppe, RUSSO, Marco   +2 more
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Evaluation of Fuzzy Partitions

Remote Sensing of Environment, 2000
Abstract The aim of this study is the development of tools dedicated to fuzzy partition evaluation in the field of satellite image classification. While a traditional crisp partition only provides qualitative information, a fuzzy partition represents a large amount of quantitative information.
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Fuzzy, I-fuzzy, and H-fuzzy partitions to describe clusters

2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2016
In this paper we discuss how three types of fuzzy partitions can be used to describe the results of three types of cluster structures. Standard fuzzy partitions are suitable for centroid based clusters, and I-fuzzy partitions for clusters represented by segments or lines (e.g., c-varieties). In this paper, we introduce hesitant fuzzy partitions.
Vicenç Torra, Laya Aliahmadipour, Anders Dahlbom   +2 more
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Fuzzy controller architecture using fuzzy partition membership functions

KES'2000. Fourth International Conference on Knowledge-Based Intelligent Engineering Systems and Allied Technologies. Proceedings (Cat. No.00TH8516), 2002
A novel current-mode CMOS circuit is used to implement fuzzy partition membership functions. The architecture, circuit and cadence spectra simulations are presented.
M. Conti, P. Crippa, S. Orcioni, C. Turchetti, V. Catani   +4 more
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Bottom-up fuzzy partitioning in fuzzy decision trees

PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.00TH8500), 2002
FID is a publicly available fuzzy decision tree software package for classifying fuzzy data. This paper describes a new bottom-up domain partitioning technique, which has just been implemented to complement the previously available top-down technique.
M. Fajfer, C.Z. Janikow
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Discovering fuzzy association rules using fuzzy partition methods

Knowledge-Based Systems, 2003
Fuzzy association rules described by the natural language are well suited for the thinking of human subjects and will help to increase the flexibility for supporting users in making decisions or designing the fuzzy systems. In this paper, a new algorithm named fuzzy grids based rules mining algorithm (FGBRMA) is proposed to generate fuzzy association ...
Yi-Chung Hu, Ruey-Shun Chen, Gwo-Hshiung Tzeng   +2 more
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Similarity relations, fuzzy partitions, and fuzzy orderings

Fuzzy Sets and Systems, 1991
Fuzzy relations form a basic and important concept in fuzzy set theory, which was introduced by Zadeh in his very first paper on fuzzy sets. The author of the present paper discusses in detail fuzzy relations, especially fuzzy similarity relations. Then he studies fuzzy partitions and fuzzy orderings.
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Fuzzy reasoning using fuzzy partition and its application

1998 Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.98TH8353), 2002
We introduce in a natural way a new method of fuzzy reasoning by defining the fuzzy partitioned space and some operations. Our proposal method holds the property of Modus Ponens. In addition, for the numerical value inputs, it is equivalent to the Product-Sum-Gravity method and holds the property of monotoneity that the Mamdani method does not.
Y. Okuda, H. Yamashita, J. Inaida
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Spaces with fuzzy partitions and fuzzy transform

Soft Computing, 2017
\par The paper considers a categorical approach to the setting of \(F\)-transforms of \textit{I. Perfilieva} [Fuzzy Sets Syst. 157, No. 8, 993--1023 (2006; Zbl 1092.41022)] from approximation theory. The author builds his machinery over an integral commutative quantale \(Q=(Q,\bigvee, \otimes, 1_Q)\) (see, e.g., [\textit{P.
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Fuzzy Sets in Clustering: On Fuzzy Partitions

2019
Clustering is often classified as an unsupervised machine learning approach. It has been extensively used for data analysis. It permits us to extract some structure from a data set. Clustering can be applied to all types of data.
Vicenç Torra, Aránzazu Jurío, Humberto Bustince, Laya Aliahmadipour   +3 more
openaire   +1 more source