Results 151 to 160 of about 11,306 (311)

Scalable Platform Enabling Reservoir Computing With Nanoporous Oxide Memristors for Image Recognition and Time Series Prediction

open access: yesAdvanced Intelligent Systems, EarlyView.
The approach of physical in materia computing incorporates parallel computing within the medium itself. A scalable and energy‐efficient, oxide‐based computational platform is realized in form of a nanoporous network of volatile niobium oxide memristors sandwiched between top and bottom metallic electrodes, and then tested for prediction and ...
Joshua Donald   +7 more
wiley   +1 more source

Biomarker‐Agnostic Detection of Ovarian Cancer from Blood Plasma Using a Machine Learning‐Driven Electronic Nose

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a biomarker‐agnostic diagnostic strategy for ovarian cancer, utilizing a machine learning‐enhanced electronic nose to analyze volatile organic compound signatures from blood plasma. By overcoming the dependence on specific biomarkers, this approach enables accurate detection, staging, and cancer type differentiation, offering a ...
Ivan Shtepliuk   +4 more
wiley   +1 more source

Stochastic Volatility Models

open access: yes, 2023
I denne avhandlingen ble effektiviteten av Stokastiske Volatilitetsmodeller, med ARMA(p, q) log-volatilitet, undersøkt i forhold til GARCH(p, q) i å forutsi volatiliteten til finansielle tidsserier. Videre var målet å vurdere evnen til SVMer i å fange opp atferden til underliggende finansielle tidsserier.
openaire   +1 more source

Device‐Level Implementation of Reservoir Computing With Memristors

open access: yesAdvanced Intelligent Systems, EarlyView.
Reservoir computing (RC) is an emerging computing scheme that employs a reservoir and a single readout layer, which can be actualized in the nanoscale with memristors. As a comprehensive overview, the principles of RC and the switching mechanisms of memristors are discussed, followed by actual demonstrations of memristor‐based RC and the remaining ...
Sunbeom Park, Hyojung Kim, Ho Won Jang
wiley   +1 more source

Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions

open access: yesAdvanced Intelligent Systems, EarlyView.
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li   +15 more
wiley   +1 more source

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