Review article of American Journal of Computer Sciences and Applications
An overview of Artificial neural network
Emon Md Mohaiminul Islama
aChongqing University Of Science And Technology, Shapingba, Chnongqing,China
Neural networks represent a brain metaphor for information processing. These models are biologically inspired rather than an exact replica of how the brain actually functions. Neural networks have been shown to be very promising systems in many forecasting applications and business classification applications due to their ability to learn from the data. This article aims to provide a brief overview of artificial neural network.The artificial neural network learns by updating the network architecture and connection weights so that the network can efficiently perform a task. It can learn either from available training patterns or automatically learn from examples or input-output relations.
Keywords: review, artificial neural network
How to cite this article:
Emon Md Mohaiminul Islama. An overview of Artificial neural network. American Journal of Computer Sciences and Applications, 2019; 2:16.
1. Neural Networks at Pacific Northwest National Laboratory
2. Klimasauskas, CC. (1989). The 1989 Neuro Computing Bibliography. Hammerstrom, D. (1986). A Connectionist/Neural Network Bibliography.
3. N. Murata, S. Yoshizawa, and S. Amari, ―Learning curves, model selection and complexity of neural networks,‖ in Advances in Neural Information Processing Systems 5, S. Jose Hanson, J. D. Cowan, and C. Lee Giles, ed. San Mateo, CA: Morgan Kaufmann, 1993, pp. 607-614
4. Bradshaw, J.A., Carden, K.J., Riordan, D., 1991. Ecological ―Applications Using a Novel Expert System Shell‖. Comp. Appl. Biosci. 7, 79–83
5. Lippmann, R.P., 1987. An introduction to computing with neural nets. IEEE Accost. Speech Signal Process. Mag., April: 4-22.
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