Physical Reservoir Computing Enabled by Solitary Waves and Biologically Inspired Nonlinear Transformation of Input Data
Abstract
:1. Introduction
2. State-of-the-Art
2.1. Traditional Reservoir Computing Algorithm
- 1
- Create a vector of input values;
- 2
- Use a random number generator to define an input matrix consisting of elements and a recurrent weight matrix containing elements;
- 3
- 4
- 5
- Construct the state matrix using the values of ;
- 6
- Train the output as , where is the identity matrix, is a regularisation coefficient, is the transpose of , and is a matrix composed of target outputs for each time instant ;
- 7
- Solve Equation (1) with a new set of target data , and compute the output vector as .
2.2. Next Generation Algorithmic Reservoir Computing and Adjacent Techniques
2.3. Physical Reservoir Computing Systems Based on Solitary Waves
3. Experimental Setup
4. Results
4.1. Formation of the Nonlinear Functional
4.2. Advantages for Generative Mode Operation
4.3. Free-Running Forecast of Chaotic Time Series
5. Discussion
5.1. Energy Efficiency, Power Consumption, and Cost
5.2. Potential Applications
6. Conclusions
Supplementary Materials
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
AI | artificial intelligence |
DC | direct current |
ESN | Echo State Network |
FLOPS | floating point operations per second |
KdV | Korteweg–de Vries |
LSM | Liquid State Machine |
MGTS | Mackey–Glass time series |
RC | reservoir computing |
RAM | random access memory |
SL | solitary-like |
UV | ultraviolet |
USD | United States Dollar |
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Maksymov, I.S. Physical Reservoir Computing Enabled by Solitary Waves and Biologically Inspired Nonlinear Transformation of Input Data. Dynamics 2024, 4, 119-134. https://doi.org/10.3390/dynamics4010007
Maksymov IS. Physical Reservoir Computing Enabled by Solitary Waves and Biologically Inspired Nonlinear Transformation of Input Data. Dynamics. 2024; 4(1):119-134. https://doi.org/10.3390/dynamics4010007
Chicago/Turabian StyleMaksymov, Ivan S. 2024. "Physical Reservoir Computing Enabled by Solitary Waves and Biologically Inspired Nonlinear Transformation of Input Data" Dynamics 4, no. 1: 119-134. https://doi.org/10.3390/dynamics4010007