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APPINF
2003
13 years 9 months ago
Preventing Computational Chaos in Asynchronous Neural Networks
One of the primary advantages of artificial neural networks is their inherent ability to perform massively parallel, nonlinear signal processing. However, the asynchronous dynamics...
Jacob Barhen, Vladimir Protopopescu
NIPS
2003
13 years 9 months ago
Training a Quantum Neural Network
Most proposals for quantum neural networks have skipped over the problem of how to train the networks. The mechanics of quantum computing are different enough from classical compu...
Bob Ricks, Dan Ventura
ICONIP
1998
13 years 9 months ago
Statistical Methods for Construction of Neural Networks
Despite all the progress in neural networks the technology is still brittle and sometimes difficult to apply. Automatic construction of networks and proper initialization of their...
Wlodzislaw Duch, Rafal Adamczak
IJON
2006
138views more  IJON 2006»
13 years 7 months ago
Time-series prediction using a local linear wavelet neural network
A local linear wavelet neural network (LLWNN) is presented in this paper. The difference of the network with conventional wavelet neural network (WNN) is that the connection weigh...
Yuehui Chen, Bo Yang, Jiwen Dong
IDA
2003
Springer
14 years 1 months ago
Similarity-Based Neural Networks for Applications in Computational Molecular Biology
This paper presents an alternative to distance-based neural networks. A distance measure is the underlying property on which many neural models rely, for example self-organizing ma...
Igor Fischer