Ward3 is a Ward Net with 3 inputs and two hidden neurons. The hidden neurons may have either the hyperbolic tangent activation function or the Gaussian activation function, depending on the setting of parameters h1 and h2. The output activation function is the hyperbolic tangent (therefore the output signal is –1 to 1).

scale – the number of past bars over which input scaling will take place. Recommended optimizer range is 10 to 200.

h1 and h2 – the parameter which determines the activation function used in the respective hidden neurons. Set to 0 for hyperbolic tangent. Set to 1 for Gaussian. Recommended optimizer range is 0 to 1.

input1 to input3  -  neural network inputs. Indicators such as Price Momentum indicators are recommended. Let the optimizer find the parameters for the indicators.

w1 to w8 – the weights in the neural network. These are similar to coefficients in regression analysis. Recommended optimizer range is –1 to 1.