The concept of an optical fuzzy flip-flop, as an essential and basic component for the effectiΒ¨e processing of fuzzy information, is introduced. A design based on the area-encoding technique and a multiple-imaging system is proposed to implement two types of fuzzy JαK flip-flops.
Fuzzy Integral Filters: Properties and Parallel Implementation
β Scribed by Hongchi Shi; Paul D. Gader; Wentsong Chen
- Publisher
- Elsevier Science
- Year
- 1998
- Tongue
- English
- Weight
- 110 KB
- Volume
- 4
- Category
- Article
- ISSN
- 1077-2014
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β¦ Synopsis
Properties and Parallel Implementation *
uzzy integrals as image filters provide a standard representational form which generalize linear filters such as the averaging filter, morphological filters such as flat dilations and erosions, and For der statistic filters such as the median filter. However, fuzzy integral filters are computationally intensive. Computing the output value obtained by fuzzy integral filtering at a point involves sorting all the pixels in a neighborhood of the point according to their values and then computing the ordered weighted sum or maximum with respect to an appropriate fuzzy measure. In this paper we discuss some properties of fuzzy integral filters and describe a method for enhancing the processing elements of single instruction, multiple data (SIMD) mesh computers with comparators and counters to efficiently implement fuzzy integral filters.
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The important properties and applications of the adapti¨e weighted fuzzy mean AWFM filter are presented in this paper. AWFM is an extension of the weighted fuzzy mean Ž . WFM filter to overcome the drawback of WFM in fine signal preservation. It not only preserves the high performance of WFM on heav