  A reservoir computer is a way of using a high dimensional dynamical system
for computation. One way to construct a reservoir computer is by connecting a
set of nonlinear nodes into a network. Because the network creates feedback
between nodes, the reservoir computer has memory. If the reservoir computer is
to respond to an input signal in a consistent way (a necessary condition for
computation), the memory must be fading; that is, the influence of the initial
conditions fades over time. How long this memory lasts is important for
determining how well the reservoir computer can solve a particular problem. In
this paper I describe ways to vary the length of the fading memory in reservoir
computers. Tuning the memory can be important to achieve optimal results in
some problems; too much or too little memory degrades the accuracy of the
computation.
