X-tron: an incremental connectionist model for category perception
نویسندگان
چکیده
منابع مشابه
X-tron: an incremental connectionist model for category perception
A connectionist model for categorization (self-organization) even in the presence of multiple or mixed patterns has been presented. During self-organization, the network automatically adjusts the number of nodes in the hidden and output layers, depending on the complexity or nature of overlap between the patterns. An ambiguity measure is given based on how well the features are being interprete...
متن کاملAn Incremental Connectionist Phrase Structure Parser
This abstract outlines a parser implemented in a connectionist model of short term memory and reasoning 1 . This connectionist architecture, proposed by Shastri in [Shastri and Ajjanagadde, 1990], preserves the symbolic interpretation of the information it stores and manipulates, but does its computations with nodes which have roughly the same computational properties as neurons. The parser rec...
متن کاملan application of equilibrium model for crude oil tanker ships insurance futures in iran
با توجه به تحریم های بین المملی علیه صنعت بیمه ایران امکان استفاده از بازارهای بین المملی بیمه ای برای نفتکش های ایرانی وجود ندارد. از طرفی از آنجایی که یکی از نوآوری های اخیر استفاده از بازارهای مالی به منظور ریسک های فاجعه آمیز می باشد. از اینرو در این پایان نامه سعی شده است با استفاده از این نوآوری ها با طراحی اوراق اختیارات راهی نو جهت بیمه گردن نفت کش های ایرانی ارائه نمود. از آنجایی که بر...
Lexical Category Acquisition as an Incremental Process
Psycholinguistic studies suggest that early on children acquire robust knowledge of the abstract lexical categories such as nouns, verbs and determiners (e.g., Gelman & Taylor, 1984; Kemp et al., 2005). Children’s grouping of words into categories might be based on various cues, including the phonological and morphological properties of a word, the distributional information about its surroundi...
متن کاملALCOVE: A Connectionist Model of Human Category Learning
ALCOVE is a connectionist model of human category learning that fits a broad spectrum of human learning data. Its architecture is based on wellestablished psychological theory, and is related to networks using radial basis functions. From the perspective of cognitive psychology, ALCOVE can be construed as a combination of exemplar-based representation and errordriven learning. From the perspect...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Neural Networks
سال: 1995
ISSN: 1045-9227
DOI: 10.1109/72.410354