Computer system and computation method using recurrent neural network

A computation method using a recurrent neural network in a computer system including at least one computer, the at least one computer including a computation device and a memory connected to the computation device, the recurrent neural network including an input unit, a reservoir unit, and an output unit, the input unit including an input node that receives a plurality of time-series data, the reservoir unit including at least one nonlinear node that receives input data output by the input unit and has time delay, the output unit including an output node that receives an output from the reservoir unit, the computation method comprising:

• causing the input unit to receive a plurality of time-series data;
• causing the input unit to divide each of the plurality of time-series data by a first time width;
• causing the input unit to execute sample and hold processing on the time-series data included in the first time width and thus to calculate a first input stream for each of the plurality of time-series data;
• causing the input unit to execute mask processing that modulates the first input stream with a second time width and thus to calculate a plurality of second input streams for each of the plurality of first input streams;
• causing the input unit to execute time shift processing that gives time shift on each of the plurality of second input streams, and
• causing the input unit to calculate the input data by superimposing the plurality of second input streams subjected to the time shift processing.