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Storage capacity as for retrieval of sequences of binary patterns is investigated for a fully connected neural network with Q (> 2)-states. By using a generating-function method of path-integral representation, we find that the network with Q-states monotonic transfer function retrieves more sequences of the stored patterns than that with a binary monotonic transfer function at zero temperature, if the control parameter is chosen optimally. We compare the results obtained by the analytic method with those by numerical simulations.

Sequence Processing Neural Network withQ-States Monotonic Transfer Function