Study of Artificial Neural Network

Sonu; Ravi Parkash Bhokal

doi:https://doi.org/10.14445/22315373/IJMTT-V47P535

International Journal of Mathematics Trends and Technology

Research Article | Open Access | Download PDF

Volume 47 | Number 4 | Year 2017 | Article Id. IJMTT-V47P535 | DOI : https://doi.org/10.14445/22315373/IJMTT-V47P535

Study of Artificial Neural Network

Sonu, Ravi Parkash Bhokal

Abstract

An Artificial Neural Network (ANN) is a mathematical model that tries to simulate the structure and functionalities of biological neural networks. Basic building block of every artificial neural network is artificial neuron, that is, a simple mathematical model (function). Such a model has three simple sets of rules: multiplication, summation and activation. At the entrance of artificial neuron the inputs are weighted what means that every input value is multiplied with individual weight. In the middle section of artificial neuron is sum function that sums all weighted inputs and bias. At the exit of artificial neuron the sum of previously weighted inputs and bias is passing trough activation function that is also called transfer function.

Keywords

An Artificial Neural Network (ANN) is a mathematical model that tries to simulate the structure and functionalities of biological neural networks.

References

1. C.Lau: “Neural Networks, Theoretical Foundations and Analysis”, 1991, IEEE Press.
2. Davies, D.W.; W.L. Price (1989). Security for computer networks. 2nd ed. John Wiley & Sons.
3. http://en.wikipedia.org/wiki/Artificial_Neural Network
4. R. Schalkoff: “Pattern Recognition: Statistical, Structural and Neural Appraoches”, New Work, John Wiley & Sons, 1992.
5. S.Y.Kung: “DIGITAL NEURAL NETWORKS”, 1993 by PTR Prentice Hall, Inc.

Citation :

Sonu, Ravi Parkash Bhokal, "Study of Artificial Neural Network," International Journal of Mathematics Trends and Technology (IJMTT), vol. 47, no. 4, pp. 253-259, 2017. Crossref, https://doi.org/10.14445/22315373/IJMTT-V47P535