Added routine to create layers for little net.
Completed support for training either a little or big net.
Fixed bug in the calculation of the dimensions of the random projection matrix.
Reworked the way experiments are specified and how results are save.
Generalized the creation of experiments to handle varying sizes of hidden layers.
Added a few experiments. Saving because this configuration appears to learn though it still needs to be tuned.
Reworked the models so that there is a SparseBlockModel, formerly the BigModel, and two other models generalized from LittleModel called EqualParametersModel and EqualComputationsModel derived from a base class called MLPModel. These two new models allow for direct comparision with models that have the same number of parameters and the same number of computations as the SparseBlockModel respectively.