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Physical reservoir computing with emerging electronics
Physical reservoir computing is a form of neuromorphic computing that harvests the dynamic properties of materials for high-efficiency computing. A...
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Brain organoid reservoir computing for artificial intelligence
Brain-inspired computing hardware aims to emulate the structure and working principles of the brain and could be used to address current limitations...
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Nonmasking-based reservoir computing with a single dynamic memristor for image recognition
Reservoir computing has been widely used in temporal information processing, and the presentation of time-delayed reservoir computing systems...
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ReLiCADA: Reservoir Computing Using Linear Cellular Automata design algorithm
In this paper, we present a novel algorithm to optimize the design of Reservoir Computing using Cellular Automata models for time series...
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MEMS reservoir computing system with stiffness modulation for multi-scene data processing at the edge
Reservoir computing (RC) is a bio-inspired neural network structure which can be implemented in hardware with ease. It has been applied across...
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Nanophotonic reservoir computing for COVID-19 pandemic forecasting
The coronavirus disease 2019 (COVID-19) has spread worldwide in unprecedented speed, and diverse negative impacts have seriously endangered human...
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Reservoir computing on a silicon platform with a ferroelectric field-effect transistor
Reservoir computing offers efficient processing of time-series data with exceptionally low training cost for real-time computing in edge devices...
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A memristor-based analogue reservoir computing system for real-time and power-efficient signal processing
Reservoir computing offers a powerful neuromorphic computing architecture for spatiotemporal signal processing. To boost the power efficiency of the...
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A high-performance computing applied to composition reservoir simulation using distributed memory and 3D hybrid unstructured grids
Reservoir models have become more complex over time, and accurate models also require refined grids for obtaining accurate results. The memory...
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An evaluation method for optical chaos synchronization based on reservoir computing
A metric is proposed for evaluation of optical chaos synchronization performance, whether the disturbance is linear or nonlinear. The chaos...
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Noise resistance of next-generation reservoir computing: a comparative study with high-order correlation computation
Reservoir computing (RC) methods have received more and more attention and applications in chaotic time series prediction with their simple structure...
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Image encryption based on actual chaotic map** using optical reservoir computing
Driven by the growing significance of information security, the field of image encryption is attracting increasing interest. This work solves an...
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Chain-structure time-delay reservoir computing for synchronizing chaotic signal and an application to secure communication
In this work, a chain-structure time-delay reservoir (CSTDR) computing, as a new kind of machine learning-based recurrent neural network, is proposed...
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A high-performance deep reservoir computer experimentally demonstrated with ion-gating reservoirs
While physical reservoir computing is a promising way to achieve low power consumption neuromorphic computing, its computational performance is still...
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An optoelectronic synapse based on α-In2Se3 with controllable temporal dynamics for multimode and multiscale reservoir computing
Neuromorphic computing based on emerging devices could overcome the von Neumann bottleneck—the restriction created by having to transfer data between...
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Re-visiting Reservoir Computing Architectures Optimized by Evolutionary Algorithms
For many years, Evolutionary Algorithms (EAs) have been applied to improve Neural Networks (NNs) architectures. They have been used for solving...