For pattern recognition: use a 3-layer artificial neural network (ANN), with linear activation function for the input layer units and logistic activation function for the hidden layer units (as for the output layer units, you could use any of the two).
For regression: I'm no expert on this, and I thus even wonder why you'd use an ANN to make a regression, so the only interest I can see here is for carrying a nonlinear regression. In this case, you must use a linear activation function for both the input layer and the output layer units and a logistic activation function for the hidden layer.
