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Fundamentals of neural networks
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The article was published on 1993-01-01 and is currently open access. It has received 1921 citations till now. The article focuses on the topics: Time delay neural network & Physical neural network.read more
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Perbandingan Algoritma Levenberg-Marquardt dengan Metoda Backpropagation pada Proses Learning Jaringan Saraf Tiruan untuk Pengenalan Pola Sinyal Elektrokardiograf
TL;DR: In this article, a system pengenalan pola EKG (Elektrokardiograf) merupakan suatu proses ying penting dalam menganalisa keaadan jantung pasien.
A Text Independent Speaker Recognition System Using a Novel Parametric Neural Network
TL;DR: This paper presents a new Speaker Recognition Technique aimed at high identification accuracy and low impostor acceptance based on a modified neural network, which is an extended and improved version of a Self-Organizing Map in multiple dimensions.
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Neural network meta‐model of fibrous materials based on discrete‐event simulation. Part 2: neural network meta‐model
TL;DR: The results of the sensitivity analysis of the neural networks have showed that the standard deviations of the fiber length and the fineness have no affect on the irregularity of the fibrous material.
Proceedings ArticleDOI
Combining multiple decision trees using fuzzy-neural inference
TL;DR: This paper presents a novel approach to combining multiple decision trees, which utilizes the power of fuzzy inference techniques and a back-propagation feed forward neural network (BP-FFNN) to improve the overall classification.
Journal ArticleDOI
A supervised committee neural network for the determination of aquifer parameters: a case study of Katasbes aquifer in Shiraz plain, Iran
Mahmoud Mohammad Rezapour Tabari,Mahmoud Mohammad Rezapour Tabari,Tahereh Azari,Vahid Dehghan +3 more
TL;DR: In this paper, a supervised committee machine with training algorithms (SCMTA) was proposed to estimate aquifer parameters by integrating artificial neural network training algorithms and the supervised committee machines concept, which combines Levenberg-Marquardt (LM), Bayesian regularization (BR), gradient descent (GD), one-step secant (OSS), and resilient back-propagation (RP) algorithms.