The number of epochs is not relevant when comparing SCG to other algorithms
like standard backpropagation. Indeed one iteration in SCG needs the
computation of two gradients, and one call to the error function, while one
iteration in standard backpropagation needs the computation of one gradient
and one call to the error function. Møller defines a complexity unit
(cu) to be equivalent to the complexity of one forward passing of all patterns
in the training set. Then computing the error costs 1 cu while computing the
gradient can be estimated to cost 3 cu. According to Møller's metric, one
iteration of SCG is as complex as around 
iterations of standard
backpropagation.
Note: As the SNNS implementation of SCG is not very well optimized, the CPU time is not necessarily a good comparison criterion.