Search Results - "GEDEON, Tamas D"

Using the Change Manager Model for the Hippocampal System to Predict Connectivity and Neurophysiological Parameters in the Perirhinal Cortex by Coward, L. Andrew, Gedeon, Tamas D.

“…Theoretical arguments demonstrate that practical considerations, including the needs to limit physiological resources and to learn without interference with…”
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Use of noise to augment training data: A neural network method of mineral-potential mapping in regions of limited known deposit examples by BROWN, Warick M, GEDEON, Tamas D, GROVES, David I

“…One of the main factors that affects the performance of MLP neural networks trained using the backpropagation algorithm in mineral-potential mapping isthe…”
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Conservation of relative fuzziness: Retrospective and triangular extension by Gedeon, Tamas D.

“…Fuzzy rule interpolation is one of the tools for reducing computational complexity of fuzzy systems, and can be used when there are gaps in the knowledge base…”
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Pattern Trees Induction: A New Machine Learning Method by Zhiheng Huang, Gedeon, T.D., Nikravesh, M.

“…Fuzzy classification is one of the most important applications in fuzzy set and fuzzy-logic-related research. Its goal is to find a set of fuzzy rules that…”
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Stability of interpolative fuzzy KH controllers by Tikk, Domonkos, Joó, István, Kóczy, László ., Várlaki, Péter, Moser, Bernhard, Gedeon, Tamás D.

“…The classical approaches in fuzzy control (Zadeh and Mamdani) deal with dense rule bases. When this is not the case, i.e. in sparse rule bases, one has to…”
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Eye Gaze Assistance for a Game-Like Interactive Task by Gedeon, Tamás (Tom) D., Zhu, Dingyun, Mendis, B. Sumudu U.

“…Human beings communicate in abbreviated ways dependent on prior interactions and shared knowledge. Furthermore, humans share information about intentions and…”
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Optimal Size Fuzzy Models by Gedeon, Tamás D., Kóczy, László T., Zorat, Alessandro

“…Approximate models using fuzzy rule bases can be made more precise by suitably increasing the size of the rule base and decreasing uncertainty in the rules. A…”
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Simulated annealing and weight decay in adaptive learning: the SARPROP algorithm by Treadgold, N.K., Gedeon, T.D.

“…A problem with gradient descent algorithms is that they can converge to poorly performing local minima. Global optimization algorithms address this problem,…”
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Confidence bounds of petrophysical predictions from conventional neural networks by Wong, P.M., Bruce, A.G., Gedeon, T.D.

“…Neural networks are powerful tools for solving the complex regression problems which abound in geosciences. Estimation of prediction confidence from neural…”
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Fuzzy tolerance relations and relational maps applied to information retrieval: Theme: Applications by KOCZY, Laszlo T, GEDEON, Tamas D, KOCZY, Judit A

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A generalized concept for fuzzy rule interpolation by Baranyi, P., Koczy, L.T., Gedeon, T.D.

“…The concept of fuzzy rule interpolation in sparse rule bases was introduced in 1993. It has become a widely researched topic in recent years because of its…”
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Fuzzy rule interpolation for multidimensional input spaces with applications: a case study by Kok Wai Wong, Tikk, D., Gedeon, T.D., Koczy, L.T.

“…Fuzzy rule based systems have been very popular in many engineering applications. However, when generating fuzzy rules from the available information, this may…”
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A survey on universal approximation and its limits in soft computing techniques by Tikk, Domonkos, Kóczy, László T., Gedeon, Tamás D.

“…This paper deals with the approximation behaviour of soft computing techniques. First, we give a survey of the results of universal approximation theorems…”
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Motion control and communication of cooperating intelligent robots by fuzzy signatures by Ballagi, A., Koczy, L.T., Gedeon, T.D.

“…This paper presents two examples of usage of fuzzy signatures in the field of mobile robotics. The first shows a complex lateral drift control method base on…”
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Pattern Trees by Zhiheng Huang, Gedeon, T.D.

“…This paper proposes a new type of tree termed pattern trees. Like decision trees, pattern trees are an effective tool for classification applications. This…”
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Efficient Fuzzy Cognitive Modeling for Unstructured Information by Kok Wai Wong, Gedeon, T.D., Koczy, L.T.

“…This paper presents an efficient fuzzy cognitive modeling which can handle granulation, organisation and causation. This cognitive modeling technique consists…”
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Exploring constructive cascade networks by Treadgold, N.K., Gedeon, T.D.

“…Constructive algorithms have proved to be powerful methods for training feedforward neural networks. An important property of these algorithms is…”
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Learning complex combinations of operations in a hybrid architecture by Coward, L.A., Gedeon, T.D., Ratnayake, U.

“…The reasons why machine learning appears limited to the relatively simple control problems are analyzed. A primary issue is that, any condition detected by a…”
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Context Dependent Reconstructive Communication by Koczy, L.T., Gedeon, T.D.

“…Fuzzy communication contains vague or imprecise components and it might lack of abundant information. If two entities (man or machine) are communicating by a…”
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Data mining of inputs: analysing magnitude and functional measures by Gedeon, T D

“…The problem of data encoding and feature selection for training back-propagation neural networks is well known. The basic principles are to avoid encrypting…”
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