Results 281 to 290 of about 274,716 (313)

Artificial neural network for steganography

Neural Computing and Applications, 2014
The digital information revolution has brought about changes in our society and our lives. The many advantages of digital information have also generated new challenges and new opportunities for innovation. The strength of the information hiding science is due to the nonexistence of standard algorithms to be used in hiding secret message.
Sabah Husien, Haitham Sabah Badi
openaire   +1 more source

Artificial neural networks: a tutorial

Computer, 1996
Artificial neural nets (ANNs) are massively parallel systems with large numbers of interconnected simple processors. The article discusses the motivations behind the development of ANNs and describes the basic biological neuron and the artificial computational model.
Anil K. Jain 0001, Jianchang Mao, K. Moidin Mohiuddin   +2 more
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Artificial Astrocyte Networks, as Components in Artificial Neural Networks

2014
Recent findings in neurophysiology provided evidence that not only neurons but also networks of glia-astrocytes are responsible for processing information in the human brain. Based on these new findings, information processing in the brain is defined as communication between neurons-neurons, neurons-astrocytes and astrocytes-astrocytes.
openaire   +1 more source

Evolving artificial neural network ensembles

IEEE Computational Intelligence Magazine, 2008
Using a coordinated group of simple solvers to tackle a complex problem is not an entirely new idea. Its root could be traced back hundreds of years ago when ancient Chinese suggested a team approach to problem solving. For a long time, engineers have used the divide-and-conquer strategy to decompose a complex problem into simpler sub-problems and then
Xin Yao 0001, Md. Monirul Islam
openaire   +1 more source

Artificial Neural Networks: An Overview

Network: Computation in Neural Systems, 2008
Neural networks have been a much publicized topic of research in recent years and are now beginning to be used in a wide range of subject areas.
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Artificial neural networks

The Lancet, 1997
M, Buyse, P, Piedbois
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String Matching Artificial Neural Networks

International Journal of Neural Systems, 2001
Three artificial neural networks (ANNs) are proposed for solving a variety of on- and off-line string matching problems. The ANN structure employed as the building block of these ANNs is derived from the harmony theory (HT) ANN, whereby the resulting string matching ANNs are characterized by fast match-mismatch decisions, low computational complexity,
openaire   +2 more sources

Uncertainty in the Output of Artificial Neural Networks

2007 International Joint Conference on Neural Networks, 2003
Analysis of the performance of artificial neural networks (ANNs) is usually based on aggregate results on a population of cases. In this paper, we analyze ANN output corresponding to the individual case. We show variability in the outputs of multiple ANNs that are trained and "optimized" from a common set of training cases.
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An artificial neural network representation for artificial organisms

2006
We introduce an artificial neural network (ANN) representation that supports the evolution of complex behaviors in artificial organisms. The strength and location of each connection in the network is specified by a connection descriptor. The connection descriptors are mapped directly into a bit-string to which a genetic algorithm is applied.
Robert J. Collins, David R. Jefferson
openaire   +1 more source

Artificial neural networks

Journal of Systems Architecture, 1998
Vincenzo Piuri, Cesare Alippi
openaire   +1 more source