neural network and fuzzy logic question

P3.1 Given a two-input neuron with the following parameters: b = 1.4, w=[5 3] and p=[-7; 3], calculate the neuron output for the following transfer functions: i. A symmetrical hard limit transfer function ii. A saturating linear transfer function iii. A hyperbolic tangent sigmoid (tansig) transfer function P3.2 A single-layer neural network is to have six inputs and two outputs. The outputs are to be limited to and continuous over the range 0 to 1. What can you tell about the network architecture? Specifically: i. How many neurons are required? ii. What are the dimensions of the weight matrix? iii. What kind of transfer functions could be used? iv. Is a bias required? P3.1 Given a two-input neuron with the following parameters: b = 1.4, w=[5 3] and p=[-7; 3], calculate the neuron output for the following transfer functions: i. A symmetrical hard limit transfer function ii. A saturating linear transfer function iii. A hyperbolic tangent sigmoid (tansig) transfer function P3.2 A single-layer neural network is to have six inputs and two outputs. The outputs are to be limited to and continuous over the range 0 to 1. What can you tell about the network architecture? Specifically: i. How many neurons are required? ii. What are the dimensions of the weight matrix? iii. What kind of transfer functions could be used? iv. Is a bias required