Insect-Wing Structured Microfluidic System for Reservoir Computing
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Abstract (arXiv)
As the demand for more efficient and adaptive computing grows, nature-inspired architectures offer promising alternatives to conventional electronic designs. Microfluidic platforms, drawing on biological forms and fluid dynamics, present a compelling foundation for low-power, high-resilience computing in environments where electronics are unsuitable. This study explores a hybrid reservoir computing system based on a dragonfly-wing inspired microfluidic chip, which encodes temporal input patterns as fluid interactions within the micro channel network. The system operates with three dye-based inlet channels and three camera-monitored detection areas, transforming discrete spatial patterns into dynamic color output signals. These reservoir output signals are then modified and passed to a simple and trainable readout layer for pattern classification. Using a combination of raw reservoir outputs and synthetically generated outputs, we evaluated system performance, system clarity, and data efficiency. The results demonstrate consistent classification accuracies up to 91%, even with coarse resolution and limited training data, highlighting the viability of the microfluidic reservoir computing.
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References · 11
- 2019Modeling Tabular data using Conditional GANcited by 699
- 2022PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecastingcited by 172
- 2021Next Generation Reservoir Computingcited by 160
- 2023Machine Learning for Synthetic Data Generation: A Reviewcited by 120
- 2020The Gaussian equivalence of generative models for learning with shallow neural networkscited by 113
- 2020Towards Robust Pattern Recognition: A Reviewcited by 31
- 2018Rapid Time Series Prediction with a Hardware-Based Reservoir Computercited by 14
- 2022Biological neurons act as generalization filters in reservoir computingcited by 12
- 2020Protein Structured Reservoir computing for Spike-based Pattern Recognitioncited by 2
- 2023Spintronic Physical Reservoir for Autonomous Prediction and Long-Term Household Energy Load Forecastingcited by 1
- 2025Communicating Smartly in Molecular Communication Environments: Neural Networks in the Internet of Bio-Nano Thingscited by 1
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