Application spike sparsity and AHaH node count.

The applications and benchmarks presented in this paper to demonstrate various machine learning tasks using AHaH plasticity require different AHaH node configurations depending on the type of data being processed and what the desired result is. The sparsity is a function of the incoming data and is defined as the number of coactive spikes divided by the total spike space.