翻訳と辞書 Words near each other ・ Extension (telephone) ・ Extension 720 ・ Extension agency ・ Extension and contraction of ideals ・ Extension bell ・ Extension by definitions ・ Extension conflict ・ Extension cord ・ Extension Ensemble ・ Extension Formation ・ Extension Gunners ・ Extension Language Kit ・ Extension mechanisms for DNS ・ Extension method ・ Extension neglect ・ Extension neural network ・ Extension of a Man ・ Extension of a polyhedron ・ Extension of a topological group ・ Extension of the Wish ・ Extension of University Education Act, 1959 ・ Extension Poly(A) Test ・ Extension Reef ・ Extension Scouting ・ Extension Service ・ Extension studies ・ Extension topology ・ Extension transference ・ Extension tube ・ Extension, British Columbia Dictionary Lists mini英和辞書 mini和英辞書 Webster 1913 Latin-English FOLDOC Wikipedia English ウィキペディア

翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Extension neural network ： ウィキペディア英語版 Extension neural network Extension neural network is a pattern recognition method found by M. H. Wang and C. P. Hung in 2003 to classify instances of data sets. Extension neural network is composed of artificial neural network and extension theory concepts. It uses the fast and adaptive learning capability of neural network and correlation estimation property of extension theory by calculating extension distance. ENN was used in: * Failure detection in machinery. * Tissue classification through MRI. * Fault recognition in automotive engine. * State of charge estimation in lead-acid battery. * Classification with incomplete survey data. == Extension Theory == Extension theory was first proposed by Cai in 1983 to solve contradictory problems. While classical mathematic is familiar with quantity and forms of objects, extension theory transforms these objects to matter-element model. where in matter $R$, $N$ is the name or type, $C$ is its characteristics and $V$ is the corresponding value for the characteristic. There is a corresponding example in equation 2. where $Height$ and $Weight$ characteristics form extension sets. These extension sets are defined by the $V$ values which are range values for corresponding characteristics. Extension theory concerns with the extension correlation function between matter-element models like shown in equation 2 and extension sets. Extension correlation function is used to define extension space which is composed of pairs of elements and their extension correlation functions. The extension space formula is shown in equation 3. where, $A$ is the extension space, $U$ is the object space, $K$ is the extension correlation function, $x$ is an element from the object space and $y$ is the corresponding extension correlation function output of element $x$. $K(x)$ maps $x$ to a membership interval $\backslash left\; (-\backslash infin,\backslash infin\; \backslash right)$. Negative region represents an element not belonging membership degree to a class and positive region vice versa. If $x$ is mapped to $\backslash left\; (0,1\; \backslash right)$, extension theory acts like fuzzy set theory. The correlation function can be shown with the equation 4. where, $X\_$ and $X\_$ are called concerned and neighborhood domain and their intervals are (a,b) and (c,d) respectively. The extended correlation function used for estimation of membership degree between $x$ and $X\_$, $X\_$ is shown in equation 5. \\ \frac)} &x\not \in |}} 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Extension neural network」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.