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» Neural Networks and Complexity Theory
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IWANN
2009
Springer
15 years 2 months ago
Lower Bounds for Approximation of Some Classes of Lebesgue Measurable Functions by Sigmoidal Neural Networks
We propose a general method for estimating the distance between a compact subspace K of the space L1 ([0, 1]s ) of Lebesgue measurable functions defined on the hypercube [0, 1]s ,...
José Luis Montaña, Cruz E. Borges
64
Voted
IJCNN
2008
IEEE
15 years 4 months ago
Airport noise simulation using neural networks
— Aircraft noise is influenced by many complex factors and it is difficult to devise an accurate mathematical model to simulate it with respect to operations at an airport. Thi...
Yingjie Yang, Chris J. Hinde, David Gillingwater
ICANN
2011
Springer
14 years 1 months ago
Temperature Prediction in Electric Arc Furnace with Neural Network Tree
Abstract. This paper presents a neural network tree regression system with dynamic optimization of input variable transformations and post-training optimization. The decision tree ...
Miroslaw Kordos, Marcin Blachnik, Tadeusz Wieczore...
CATA
2000
14 years 11 months ago
Neocognitron for rotated pattern recognition
Ideally computer pattern recognition systems should be insensitive to scaling, translation, distortion and rotation. Many neural network models have been proposed to address this ...
Michael Tran, Siddheswar Ray, Ronald Pose
ICANN
2001
Springer
15 years 2 months ago
Online Symbolic-Sequence Prediction with Discrete-Time Recurrent Neural Networks
This paper studies the use of discrete-time recurrent neural networks for predicting the next symbol in a sequence. The focus is on online prediction, a task much harder than the c...
Juan Antonio Pérez-Ortiz, Jorge Calera-Rubi...