Outputs (166)

Neural Network Approximation of Fuzzy Logic Operators (2000)
Journal Article
Andras, P., Kaban, A., & Bossanyi, R. (2000). Neural Network Approximation of Fuzzy Logic Operators. Annales universitatis occidentalis timisiensis series philosophia, XII, 147-159

We investigate in this paper how to use neural networks to help the development of efficient fuzzy decision systems. First we review the basic theories of fuzzy logic and neural networks, and we look at the main applications of the artificial neural... Read More about Neural Network Approximation of Fuzzy Logic Operators.

Approximation of chaotic shapes with tree-structured neural networks (1999)
Presentation / Conference Contribution
Andras, P. (1999). Approximation of chaotic shapes with tree-structured neural networks. In IJCNN'99: International Joint Conference on Neural Networks, Proceedings (817-820). https://doi.org/10.1109/IJCNN.1999.831056

The approximation of highly irregular decision regions is a challenging problem in pattern recognition and classification. Existing neural networks require many neurons for approximating irregular decision regions. A new tree-structured neural networ... Read More about Approximation of chaotic shapes with tree-structured neural networks.

Efficient selection of the node parameters in RBF neural networks (1999)
Presentation / Conference Contribution
Andras, P. (1999). Efficient selection of the node parameters in RBF neural networks. In Seminar of Numerical and Statistical Calculus (9-22)

Orthogonal RBF neural network approximation (1999)
Journal Article
Andras, P. (1999). Orthogonal RBF neural network approximation. Neural Processing Letters, 9, 141-151. https://doi.org/10.1023/A%3A1018621308457

The approximation properties of the RBF neural networks are investigated in this paper. A new approach is proposed, which is based on approximations with orthogonal combinations of functions. An orthogonalization framework is presented for the Gaussi... Read More about Orthogonal RBF neural network approximation.

Amnesia: Neuropsychological Interpretation and Artificial Neural Network Simulation (1998)
Journal Article
Opre, A., & Andras, P. (1998). Amnesia: Neuropsychological Interpretation and Artificial Neural Network Simulation. Cognition, Brain, Behavior: An Interdisciplinary Journal, 2(3-4), 315-335

The amnesia syndrome is characterized by normal perceptual, linguistic and intellectual functioning together with an inability to remember explicitly recent events and new information. Amnesic patients generally exhibit spared priming effects on impl... Read More about Amnesia: Neuropsychological Interpretation and Artificial Neural Network Simulation.

A genetic solution for the cutting stock problem (1996)
Presentation / Conference Contribution
András, P., András, A., & Szabό, Z. (1996). A genetic solution for the cutting stock problem. In Proceedings of the First Online Workshop on Soft Computing (WSC1) (87-92)

The cutting stock problem it is of great interest in relation with several real world problems. Basically it means that there are some smaller pieces that have to be cut from a greater stock piece, in such a way, that the remaining part of the stock... Read More about A genetic solution for the cutting stock problem.