  A delayed feedback reservoir (DFR) is a type of reservoir computing system
well-suited for hardware implementations owing to its simple structure. Most
existing DFR implementations use analog circuits that require both
digital-to-analog and analog-to-digital converters for interfacing. However,
digital DFRs emulate analog nonlinear components in the digital domain,
resulting in a lack of design flexibility and higher power consumption. In this
paper, we propose a novel modular DFR model that is suitable for fully digital
implementations. The proposed model reduces the number of hyperparameters and
allows flexibility in the selection of the nonlinear function, which improves
the accuracy while reducing the power consumption. We further present two DFR
realizations with different nonlinear functions, achieving 10x power reduction
and 5.3x throughput improvement while maintaining equal or better accuracy.
