Publication | Closed Access
Simple Reservoir Computing Capitalizing on the Nonlinear Response of Materials: Theory and Physical Implementations
61
Citations
20
References
2021
Year
Numerical AnalysisEngineeringSpatial MultiplexingComputational MechanicsReservoir EngineeringNonlinear ResponsePhysic Aware Machine LearningNumerical SimulationUnconventional ComputingSystems EngineeringNonlinear ProcessNeuromorphic EngineeringNeurocomputersComputer EngineeringNonlinear DynamicsReservoir ComputingNonlinear Dynamical SystemsReservoir ModelingComputational NeuroscienceMechanical SystemsBrain-like ComputingPhysical ImplementationsMultiscale Modeling
The potential of nonlinear dynamical systems serving as reservoirs has attracted much attention for the physical realization of reservoir computing (RC). Here, we propose a hardware system working as a reservoir with one simple form of nonlinearity that reflects the intrinsic characteristics of the materials. We show that insufficient dynamics in such physical systems can perform like complex dynamical systems with the assistance of external controls. Based on the idea of spatial multiplexing, this dynamical system is studied under two frameworks. The correlation between structural adjustments of the reservoir and system performance in processing various types of task is proposed. Our results are expected to enable the development of material-based devices for RC.
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