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Fuzzy feature evaluation index and connectionist realization — II: Theoretical analysis

Jayanta Basak, Rajat K. De, Sankar K. Pal
1998 Information Sciences  
The present article deals with a theoretical analysis of our earlier investigation [1] where we developed a neuro-fuzzy model for feature evaluation.  ...  This includes derivation of a fixed upper bound and a varying lower bound of the feature evaluation index.  ...  Section 2 provides, in brief, our previous work on the fuzzy feature evaluation index and its connectionist realization [1] for the convenience of the readers.  ... 
doi:10.1016/s0020-0255(97)10031-7 fatcat:bfsfunvyxvesreme2zapssohtu

Fuzzy feature evaluation index and connectionist realization

Sankar K. Pal, Jayanta Basak, Rajat K. De
1998 Information Sciences  
A new t~ature evaluation index based on fuzzy set theory and a connectionist model for its evaluation are provided.  ...  The overall importance of the features is evaluated both individually and in a group considering their dependence as well as independence.  ...  Conclusions In this article, we have presented a new feature evaluation index based on fuzzy set theory and a neuro-fuzzy approach for feature evaluation.  ... 
doi:10.1016/s0020-0255(97)10023-8 fatcat:gxaw3zrssvdv5povwwyqwexkpm

Page 5705 of Mathematical Reviews Vol. , Issue 99h [page]

1999 Mathematical Reviews  
) ; De, Rajat K. (6-ISI-MU; Calcutta); Pal, Sankar K. (6-ISI-MU; Calcutta) Fuzzy feature evaluation index and connectionist realization.  ...  II. Theoretical analysis. (English summary) Inform. Sci. 111 (1998), no. 1-4, 1-17. Summary: “The present article deals with a theoretical analysis of our earlier investigation [Part I, Inform.  ... 

Unsupervised feature selection using a neuro-fuzzy approach

Jayanta Basak, Rajat K. De, Sankar K. Pal
1998 Pattern Recognition Letters  
A neuro-fuzzy methodology is described which involves connectionist minimization of a fuzzy feature evaluation index with unsupervised training.  ...  Besides, the investigation includes the development of another algorithm for ranking of dierent feature subsets using the aforesaid fuzzy evaluation index without neural networks.  ...  The work is partly supported by Grant No. 25(0093)/97/EMR-II of CSIR, New Delhi. The work was partly done when Jayanta Basak was in RIKEN Brain Science Institute, Wakoshi, Saitama, Japan.  ... 
doi:10.1016/s0167-8655(98)00083-x fatcat:v3kz2b7evbc7df4rnw3ha5o6hq

A stochastic connectionist approach for global optimization with application to pattern clustering

G.P. Babu, N.M. Murty, S.S. Keerthi
2000 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
This approach is used to cluster selected data sets and the results obtained are compared with that of the K-means algorithm and a simulated annealing (SA) approach.  ...  The amenability of the connectionist approach to parallelization enables effective use of parallel hardware.  ...  Fuzzy clustering approaches make use of fuzzy set theoretic concepts in order to find fuzzy clusters [11] , [12] .  ... 
doi:10.1109/3477.826943 pmid:18244725 fatcat:ge4sinxybrbs7i33p4axvjphlu

A NEURO-FUZZY BASED DOCUMENT TRACKING & CLASSIFICATION SYSTEM

Ituma C, James G. G, Onu F. U
2020 International Journal of Engineering Applied Sciences and Technology  
The structured systems analysis and design methodology and the neuro-fuzzy clustering technique were employed to study and classify the documents into groups of similar topics for specific knowledge.  ...  This paper takes a critical study of document tracking and classification systems and presents a Neuro-fuzzy based model for classification of search results based on the strength of words in the query  ...  II.  ... 
doi:10.33564/ijeast.2020.v04i10.075 fatcat:smpuymhssnfozdzwh5x6uqe77u

Neuro-fuzzy rule generation: survey in soft computing framework

S. Mitra, Y. Hayashi
2000 IEEE Transactions on Neural Networks  
The neuro-fuzzy approach, symbiotically combining the merits of connectionist and fuzzy approaches, constitutes a key component of soft computing at this stage.  ...  Rules learned and generated for fuzzy reasoning and fuzzy control are also considered from this wider viewpoint. Models are grouped on the basis of their level of neuro-fuzzy synthesis.  ...  This allows ranking and evaluation of the extracted knowledge.  ... 
doi:10.1109/72.846746 pmid:18249802 fatcat:3y2gnxmiorbbfocd2pp7ygrwiy

Supervised and Unsupervised Pattern Recognition: Feature Extraction and Computational Intelligence [Book Review]

K. Chen, V. Kvasnicka, P.C. Kanen, S. Haykin
2001 IEEE Transactions on Neural Networks  
Generic feature extraction methods reported include waveletbased analysis, invariant moments, entropy, cepstrum analysis, and fractal dimension.  ...  Dasey and E. Micheli-Tzanakou on fuzzy neural networks.  ... 
doi:10.1109/tnn.2001.925570 fatcat:cjrvu3xkvrc6jbj3hc2tt3rhha

A Multi Views Approach for Remote Sensing Fusion Based on Spectral, Spatial and Temporal Information [chapter]

Farah Imed
2011 Image Fusion  
Finally, it is interesting to get a quality index in addition to results after fusion process. This quality index serves to evaluate the chosen method and to adjust additional information.  ...  Adopted neuro-fuzzy architecture is the FALCON model (Fuzzy Adaptive Learning Control Network) (Lin, 1997 ), a connectionist model that can be contrasted with a traditional fuzzy logic and decision system  ... 
doi:10.5772/14748 fatcat:geahp6sw6vg5bkfotne3hmmorm

A review on image segmentation techniques

Nikhil R Pal, Sankar K Pal
1993 Pattern Recognition  
Attempts have been made to cover both fuzzy and non-fuzzy techniques including color image segmentation and neural network based approaches.  ...  Adequate attention is paid to segmentation of range images and magnetic resonance images. It also addresses the issue of quantitative evaluation of segmentation results.  ...  , affect feature analysis and recognition.  ... 
doi:10.1016/0031-3203(93)90135-j fatcat:ws4tjtqyajfrjgrq4igfokn4zm

Forecast and Evaluation of Educational Economic Contribution Based on Fuzzy Neural Network

RuiFeng Liu, Min Wu, Zhihan Lv
2021 Complexity  
This article combines fuzzy theory and neural network theory to construct an empirical model for the analysis of the contribution of education economy and conduct an empirical analysis of statistical data  ...  Analysis shows that there is a great correlation between per capita years of education and per capita GDP, especially the number of college students per million people has a greater correlation with per  ...  , and self-organizing feature mapping theory.  ... 
doi:10.1155/2021/1056295 fatcat:xvxg6boccnaifivlpoobrtlrry

Neural Network Combining Classifier Based on Dempster-Shafer Theory for Semantic Indexing in Video Content [chapter]

Rachid Benmokhtar, Benoit Huet
2006 Lecture Notes in Computer Science  
Classification is a major task in many applications and in particular for automatic semantic-based video content indexing and retrieval.  ...  Experiments are conducted in the framework of TrecVid high level feature extraction task that consists of ordering shots with respect to their relevance to a given semantic class.  ...  The evaluation is realized in the context of TrecVid'05 and we use the common evaluation measure from the information retrieval community: the Average Precision.  ... 
doi:10.1007/978-3-540-69429-8_20 fatcat:llhyeyutsrhwpawvc6idg4i4xa

FCMAC-BYY: Fuzzy CMAC Using Bayesian Ying–Yang Learning

M.N. Nguyen, D. Shi, C. Quek
2006 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Index Terms-Bayesian Ying-Yang (BYY) learning, cerebellar model articulation controller (CMAC), fuzzy rule set, neural networks, truth-value restriction (TVR).  ...  to the original CMAC; and third, it provides an intuitive fuzzy logic reasoning and has clear semantic meanings.  ...  This feature is particularly important in some areas such as financial analysis and medical diagnosis when the domain expert must be involved to analyze the causality.  ... 
doi:10.1109/tsmcb.2006.874691 pmid:17036822 fatcat:doymgrvhebgjvddjnvym7u2nqm

Synchrony and Composition: Toward a Cognitive Architecture between Classicism and Connectionism [chapter]

Markus Werning
2003 Foundations of the Formal Sciences II  
They combine the virtues and avoid the vices of classical and connectionist architectures.  ...  of neurons, (ii) that the isomorphism, in a strong sense, preserves the constituent relations of the conceptual algebra, and (iii) that the isomorphism transfers semantic compositionality.  ...  Integrated connectionist/ symbolic architectures only realize trees. Oscillatory networks, however, realize both trees and the principle of constituency, but not the principle of order.  ... 
doi:10.1007/978-94-017-0395-6_19 fatcat:cq3yvlljbfh4jksf7sd4zm2tf4

Gesture Recognition: A Survey

Sushmita Mitra, Tinku Acharya
2007 IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews)  
Applications involving hidden Markov models, particle filtering and condensation, finite-state machines, optical flow, skin color, and connectionist models are discussed in detail.  ...  Existing challenges and future research possibilities are also highlighted.  ...  Connectionist Approach To Facial Gesture Recognition Soft computing tools broadly encompass ANN, fuzzy sets and GAs.  ... 
doi:10.1109/tsmcc.2007.893280 fatcat:iywyfj465zgfnp4n2o7usgcsne
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