Nonlinear Autoregression With Convergent Dynamics on Novel Computational Platforms
Jiayin Chen, Hendra I. Nurdin · IEEE Transactions on Control Systems Technology · 2021
Nonlinear stochastic modeling is useful for describing complex engineering systems. Meanwhile, neuromorphic (brain-inspired) computing paradigms are being developed to tackle tasks that are challenging and resource-intensive on digital computers. An emerging scheme is reservoir computing, which exploits nonlinear dynamical systems for temporal information processing. This brief introduces reservoir computers with output feedback as stationary and ergodic infinite-order nonlinear autoregressive models. We highlight the versatility of this approach by employing classical and quantum reservoir computers to model synthetic and real datasets, further exploring their potential for control applications.