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Brain-Inspired Reservoir Computing Using Memristors with Tunable Dynamics and Short-Term Plasticity
Recent advancements in reservoir computing research have created a demand for analog devices with dynamics that can facilitate the physical implementation of reservoirs, promising faster information processing while consuming less energy and occupying a smaller area footprint.
Spike-based Neuromorphic Computing for Next-Generation Computer Vision
Neuromorphic Computing promises orders of magnitude improvement in energy efficiency compared to traditional von Neumann computing paradigm.
Biomembrane-based Memcapacitive Reservoir Computing System for Energy Efficient Temporal Data Processing
Reservoir computing is a highly efficient machine learning framework for processing temporal data by extracting features from the input signal and mapping them into higher dimensional spaces.
