Reference no: EM133071067
DSC-550 Neural Networks and Deep Learning - Grand Canyon University
Project
Starting with a single neuron and with single layer of neurons, generate the transfer function of a multiple layer network.Examine the inside of the artificial neural network, devise a transfer function for each layer, briefly research how a topology can be obtained, analyze recurrent neural networks, and investigate forward propagation, cost function, and backward propagation.
Consider the following multilayer neural network with the transfer function for each layer:
![1665_Neural Networks.jpg](https://secure.expertsmind.com/CMSImages/1665_Neural Networks.jpg)
Where satlin is defined by:
![2337_Neural Networks1.jpg](https://secure.expertsmind.com/CMSImages/2337_Neural Networks1.jpg)
And purelinis defined as:
![922_Neural Networks2.jpg](https://secure.expertsmind.com/CMSImages/922_Neural Networks2.jpg)
Using Python and the correspondent libraries, sketch the following responses (plot the indicated variable versus p for (-3< p<3)).
Given that
w1,11=2, w2.11=1, b11=2, b21=-1, w1,12=1, w1,22=-1, b12=0
i. n11.
ii. a11.
iii. n12.
iv. a21.
v. n12.
vi. a12.
Attachment:- Neural Networks and Deep Learning.rar