نتایج جستجو برای: fuzzy k
تعداد نتایج: 464929 فیلتر نتایج به سال:
High-dimensional data are by their very nature often difficult to handle by conventional machine-learning algorithms, which is usually characterized as an aspect of the curse of dimensionality. However, it was shown that some of the arising high-dimensional phenomena can be exploited to increase algorithm accuracy. One such phenomenon is hubness, which refers to the emergence of hubs in high-di...
معادلات انتگرال دیفرانسیل در مدل بندی مسائلی کاربردی چون انتقال گرما، پدیده انتشار و پخش نوترون مورد استفاده قرار می گیرند و نیز در برخی کاربردهای فیزیک و زیست شناسی و مهندسی استفاده وافر دارند و به تبع آن معادلات انتگرال دیفرانسیل فازی نیز مورد توجه قرار گرفته اند. معادله انتگرال دیفرانسیل غیر خطی زیر را در نظر می گیریم. در صورتی که توابع معلوم a(t)و k(t,s,x(t)) و f(t,x(t)) توابعی ف...
This paper shows that the k-means quantization of a signal can be interpreted both as a crisp indicator function and as a fuzzy membership assignment describing fuzzy clusters and fuzzy boundaries. Combined crisp and fuzzy indicator functions are defined here as natural generalizations of the ordinary crisp and fuzzy indicator functions, respectively. An application to iris segmentation is pres...
The concept of fuzzy flip-flop was introduced in the middle of 1980’s by Hirota (with his students). The Hirota Lab recognized the essential importance of the concept of a fuzzy extension of a sequential circuit and the notion of fuzzy memory. From this point of view they proposed alternatives for “fuzzifying” digital flip-flops. The starting elementary digital units were the binary J-K flipflo...
In this paper, we present reliable algorithms for fuzzy k-means and C-means that could improve MRI segmentation. Since the k-means or FCM method aims to minimize the sum of squared distances from all points to their cluster centers, this should result in compact clusters. Therefore the distance of the points from their cluster centre is used to determine whether the clusters are compact. For th...
Data clustering is an important area of data mining. This is an unsupervised study where data of similar types are put into one cluster while data of another types are put into different cluster. Fuzzy C means is a very important clustering technique based on fuzzy logic. Also we have some hard clustering techniques available like K-means among the popular ones. In this paper a comparative stud...
all practical digital circuits are usually a mixture of combinational and sequential logic. flip–flops are essential to sequential logic therefore fuzzy flip–flops are considered to be among the most essential topics of fuzzy digital circuit. the concept of fuzzy digital circuit is among the most interesting applications of fuzzy sets and logic due to the fact that if there has to be an ultimat...
In our previous work we proposed a Multilayer Perceptron Neural Networks (MLP NN) consisting of fuzzy flipflops (F3) based on various operations. We showed that such kind of fuzzy-neural network had good learning properties. In this paper we propose an evolutionary approach for optimizing fuzzy flip-flop networks (FNN). Various popular fuzzy operation and three different fuzzy flip-flop types w...
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