Define an Artificial Neuron Network $($ANN$)$ model as; $4$ input, $2$ hidden layer with $4$ neurons each and $1$ outputs. The weight coefficients will be chosen randomly $0,1.$ Apply activation functions given below;

$($a$)$ Linear

$($b$)$ Threshold

$($c$)$ Sigmoid non$-$linear

Then curve outputs of the ANN structure.

$2.$ Explain wavelet approach and related main wavelet equation. Draw wavelet model with the level of $c{A}_4$ and $c{D}_3$ at the transmitter and related receiver block.

$3.($a$)$ For $88$ matrix input matrix with randomly chosen elements in the range of $0,1.$

$($a$)$Apply lowpass filtering then down sampling output.

$($b$)$ Apply high pass filtering then down sampling