The main ideas of F-transform came from representing expert rules. It would be therefore re reasonable to expect that the more accurately the membership functions describe human reasoning, the more efficient will be the corresponding F-transform formulas. We know that an adequate description of our reasoning corresponds to complicated membership functions -- however, somewhat surprisingly, most efficient applications of F-transform use the simplest possible triangular membership functions. There exist some explanations for this phenomenon which are based on local behavior of the signal. In this paper, we supplement this local explanation by a global one: namely, we prove that triangular membership functions are the only one that provide the...
Fuzzy systems are widely used in research and applications considering complex information like gene...
AbstractThis paper concerns triangular function analysis including triangular function series and tr...
In this paper we will prove that in most of the cases the extended inverse fuzzy transform preserves...
In many practical applications, it is useful to represent a signal or an image by its average values...
Fuzzy techniques describe expert opinions. At first glance, we would therefore expect that the more ...
In principle, in applications of fuzzy techniques, we can have different complex membership function...
In many design problems, it is important to take into account expert knowledge. Expert often describ...
In principle, we can have many different membership functions. Interestingly, however, in many pract...
In many application problems, F-transform algorithms are very efficient. In F-transform techniques, ...
In many practical situations, e.g., in signal processing, image processing, analysis of temporal dat...
Theoretically, we can have membership functions of arbitrary shape. However, in practice, at any giv...
In data fusion, we have several approximations to the desired objects, and we need to fuse them into...
Fast Fourier Transform (FFT) is an efficient algorithm to compute the Discrete Fourier Transform (DF...
A relationship between the discrete F-transform and aggregation functions is analyzed. We show that ...
In this paper we propose a new representation for FFT algorithms called the triangular matrix repres...
Fuzzy systems are widely used in research and applications considering complex information like gene...
AbstractThis paper concerns triangular function analysis including triangular function series and tr...
In this paper we will prove that in most of the cases the extended inverse fuzzy transform preserves...
In many practical applications, it is useful to represent a signal or an image by its average values...
Fuzzy techniques describe expert opinions. At first glance, we would therefore expect that the more ...
In principle, in applications of fuzzy techniques, we can have different complex membership function...
In many design problems, it is important to take into account expert knowledge. Expert often describ...
In principle, we can have many different membership functions. Interestingly, however, in many pract...
In many application problems, F-transform algorithms are very efficient. In F-transform techniques, ...
In many practical situations, e.g., in signal processing, image processing, analysis of temporal dat...
Theoretically, we can have membership functions of arbitrary shape. However, in practice, at any giv...
In data fusion, we have several approximations to the desired objects, and we need to fuse them into...
Fast Fourier Transform (FFT) is an efficient algorithm to compute the Discrete Fourier Transform (DF...
A relationship between the discrete F-transform and aggregation functions is analyzed. We show that ...
In this paper we propose a new representation for FFT algorithms called the triangular matrix repres...
Fuzzy systems are widely used in research and applications considering complex information like gene...
AbstractThis paper concerns triangular function analysis including triangular function series and tr...
In this paper we will prove that in most of the cases the extended inverse fuzzy transform preserves...