Results 71 to 80 of about 7,314,717 (264)

3D-integrated multilayered physical reservoir array for learning and forecasting time-series information

Nature Communications
A wide reservoir computing system is an advanced architecture composed of multiple reservoir layers in parallel, which enables more complex and diverse internal dynamics for multiple time-series information processing.
Sanghyeon Choi, Jaeho Shin, Gwanyeong Park, Jung Sun Eo, Jingon Jang, J. Joshua Yang, Gunuk Wang   +6 more
doaj   +1 more source

Disentangling Bulk and Surface Contributions to Charge and Discharge Fading in High‐Voltage LiCoO2

Advanced Functional Materials, EarlyView.
High‐voltage operation of LiCoO2 accelerates capacity fading through bulk and surface degradation. By introducing a LiTaO3 coating to selectively suppress surface degradation, bulk and surface contributions to charge and discharge fading are decoupled.
Hyungjoon Moon, Sangbin Park, Jaewoo Jung, Seongeun Lee, Chanwoo Jung, Min‐Sik Park, Won‐Sub Yoon   +6 more
wiley   +1 more source

Gesture recognition with Brownian reservoir computing using geometrically confined skyrmion dynamics

Nature Communications
Physical reservoir computing leverages the dynamical properties of complex physical systems to process information efficiently, significantly reducing training efforts and energy consumption.
Grischa Beneke, Thomas Brian Winkler, Klaus Raab, Maarten A. Brems, Fabian Kammerbauer, Pascal Gerhards, Klaus Knobloch, Sachin Krishnia, Johan H. Mentink, Mathias Kläui   +9 more
doaj   +1 more source

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

Advanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin, Eunjoo Yoo, Ki‐Hoon Son, Hyun‐Sik Kim, Dae‐Hee Han, Jeong Hyeon Son, Seung Hwan Lee, Hong‐Sub Lee   +7 more
wiley   +1 more source

Reservoir characterization using support vector machines [PDF]

, 2005
Reservoir characterization especially well log data analysis plays an important role in petroleum exploration. This is the process used to identify the potential for oil production at a given source.
Wong, K.W., Fung, C.C., Gedeon, T., Ong, Y.S.   +3 more
core  

Neuromorphic overparameterisation and few-shot learning in multilayer physical neural networks

Nature Communications
Physical neuromorphic computing, exploiting the complex dynamics of physical systems, has seen rapid advancements in sophistication and performance. Physical reservoir computing, a subset of neuromorphic computing, faces limitations due to its reliance ...
Kilian D. Stenning, Jack C. Gartside, Luca Manneschi, Christopher T. S. Cheung, Tony Chen, Alex Vanstone, Jake Love, Holly Holder, Francesco Caravelli, Hidekazu Kurebayashi, Karin Everschor-Sitte, Eleni Vasilaki, Will R. Branford   +12 more
doaj   +1 more source

Substrate-voltage-controlled temporal nonlinearity in ferroelectric FET-based reservoir computing [PDF]

APL Machine Learning
Physical reservoir computing exploits inherent nonlinearity and short-term memory of physical dynamics to achieve efficient processing of time-series data with extremely-low training cost.
Eishin Nako, Ryosho Nakane, Mitsuru Takenaka, Kasidit Toprasertpong, Shinichi Takagi   +4 more
doaj   +1 more source

Balancing Hydrophobicity and Hydrophilicity: Dual Filler‐Engineered Proton Exchange Membranes for Durable, High‐Power Fuel Cells

Advanced Functional Materials, EarlyView.
Polarity‐matched Zr–MOFs program Nafion's nanoscale morphology during solution casting. Hydrophilic UiO‐66 preserves hydrated pathways, while hydrophobic UiO‐67 increases the proton hopping sites by densifying ionic clusters. Combining both fillers yields a membrane that delivers 176 mS cm−1 conductivity, reaches 1.46 W cm−2 under 200 kPa, and triples ...
Yonghwi Cho, Yunseong Ji, Minkyu Choi, Junsu Kim, Yejin Kim, Su Jeong Lee, Wooyoung Choi, Choong Hoo Lee, Ju Yeon Kim, Ohchan Kwon, Hanim Kim, Du Yeol Ryu, Ki Chul Kim, Dae Woo Kim   +13 more
wiley   +1 more source

Theoretical simulations of dynamical systems for advanced reservoir computing applications [Elektronisk resurs]

, 2020
There are computational problems that are simply too complex and cannot be handled by traditional CMOS technologies due to practical engineering limitations related to either fundamental physical behavior of devices at small scales, or various energy ...
Athanasiou, Vasileios,
core  

Restrictions on physical stochastic reservoir computers

Physical Review Applied
Reservoir computation is a recurrent framework for learning and predicting time series data, that benefits from extremely simple training and interpretability, often as the the dynamics of a physical system. In this paper, we will study the impact of noise on the learning capabilities of analog reservoir computers.
openaire   +2 more sources