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Vestibular reservoir computing

arXiv 2604.09943 ↗First posted 10 Apr 2026cs.LG nlin.CD physics.data-ancited by 0

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Abstract (arXiv)

Reservoir computing (RC) is a computational framework known for its training efficiency, making it ideal for physical hardware implementations. However, realizing the complex interconnectivity of traditional reservoirs in physical systems remains a significant challenge. This paper proposes a physical RC scheme inspired by the biological vestibular system. To overcome hardware complexity, we introduce a designed uncoupled topology and demonstrate that it achieves performance comparable to fully coupled networks. We theoretically analyze the difference between these topologies by deriving a memory capacity formula for linear reservoirs, identifying specific conditions where both configurations yield equivalent memory. These analytical results are demonstrated to approximately hold for nonlinear reservoir systems. Furthermore, we systematically examine the impact of reservoir size on predictive statistics and memory capacity. Our findings suggest that uncoupled reservoir architectures offer a mathematically sound and practically feasible pathway for efficient physical reservoir computing.

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References · 17

  1. 2021Next Generation Reservoir Computingcited by 160
  2. 2019Backpropagation Algorithms and Reservoir Computing in Recurrent Neural Networks for the Forecasting of Complex Spatiotemporal Dynamicscited by 134
  3. 2020Physical reservoir computing -- An introductory perspectivecited by 58
  4. 2020Machine learning prediction of critical transition and system collapsecited by 54
  5. 2019Forecasting Chaotic Systems with Very Low Connectivity Reservoir Computerscited by 43
  6. 2019Model-free prediction of spatiotemporal dynamical systems with recurrent neural networks: Role of network spectral radiuscited by 34
  7. 2023A Survey on Reservoir Computing and its Interdisciplinary Applications Beyond Traditional Machine Learningcited by 22
  8. 2019Dynamical learning of dynamicscited by 16
  9. 2022Optimizing Memory in Reservoir Computerscited by 13
  10. 2020Higher-Order Quantum Reservoir Computingcited by 10
  11. 2024Classical and Quantum Physical Reservoir Computing for Onboard Artificial Intelligence Systems: A Perspectivecited by 9
  12. 2013DNA Reservoir Computing: A Novel Molecular Computing Approachcited by 7
5 more
  1. 2023Infinite-dimensional reservoir computingcited by 7
  2. 2024Chaotic attractor reconstruction using small reservoirs -- the influence of topologycited by 7
  3. 2014A General Stochastic Algorithmic Framework for Minimizing Expensive Black Box Objective Functions Based on Surrogate Models and Sensitivity Analysiscited by 5
  4. 2023Deep Photonic Reservoir Computer for Speech Recognitioncited by 5
  5. 2023Harnessing Synthetic Active Particles for Physical Reservoir Computingcited by 3

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