Apply the back propagation algorithm to find the weights corrections of a neural network after

applying the input$-$ output pattern $((0\mathrm{.}2,0\mathrm{.}5),1).$ Assume that the network has a single hidden layer

with $2$ neurons. All weights from the input layer to the hidden layer are initially set to $0\mathrm{.}3,$ all the

weights from hidden layer to the output layer are initially set to $0\mathrm{.}5,$ and all thresholds are $0\mathrm{.}2$ with

all input to the threshold are $0\mathrm{.}5.$ All neurons use the sigmoid activation function with a learning rate

of $0\mathrm{.}3$ respectively. You are required to