Results 71 to 80 of about 129,225 (287)
Sustainable Synaptic Device with Two‐Dimensional Ferroelectric Materials for Neuromorphic Computing
Advanced Science, EarlyView.α‐In2Se3 based FeSFETs can be utilized as sustainable devices through polarization switching governed by both out‐of‐plane and in‐plane polarizations. Upon reaching a fatigued state, current annealing enabled by conductance modulation can significantly enhance the endurance of FeSFETs.
Jaewook Yoo +12 more
wiley +1 more source
Advanced Science, EarlyView.We present an organic–inorganic heterostructure transistor array for neuromorphic computing, achieving 95.6% MNIST accuracy and 1.2 fJ per operation, with dynamic spatiotemporal encoding and precise vehicle direction detection under combined optical and electrical stimulation.
Wen‐Min Zhong +13 more
wiley +1 more source
Revista Tecnológica, 2014 La aplicación de modelos matemáticos en el manejo de cuencas hidrográficas tiene requerimientos exigentes de información y en su mayoría no han sido desarrollados para ser aplicados en regiones de montaña.
Jaime Eduardo Veintimilla +1 more
doaj
Modeling Financial Time Series with Artificial Neural Networks [PDF]
, 2009 Financial time series convey the decisions and actions of a population of human actors over time. Econometric and regressive models have been developed in the past decades for analyzing these time series.
Versace, Massimiliano, Wong, Charles
core +1 more source
Coherent 100G Nonlinear Compensation with Single-Step Digital Backpropagation
, 2015 Enhanced-SSFM digital backpropagation (DBP) is experimentally demonstrated and compared to conventional DBP. A 112 Gb/s PM-QPSK signal is transmitted over a 3200 km dispersion-unmanaged link.
Forestieri, Enrico +5 more
core +1 more source
Backdrop: Stochastic Backpropagation
CoRR, 2018 11 pages, 9 figures, 2 tables.
Siavash Golkar, Kyle Cranmer
openaire +2 more sources
Nonlinear backpropagation: doing backpropagation without derivatives of the activation function [PDF]
IEEE Transactions on Neural Networks, 1997 The conventional linear backpropagation algorithm is replaced by a nonlinear version, which avoids the necessity for calculating the derivative of the activation function. This may be exploited in hardware realizations of neural processors. In this paper we derive the nonlinear backpropagation algorithms in the framework of recurrent backpropagation ...
John A. Hertz +3 more
openaire +2 more sources
Triple‐Mode Ferroelectric Thin‐Film Transistor for Hybrid Electrical–Optical Reservoir Computing
Advanced Science, EarlyView.A triple‐mode ferroelectric thin‐film transistor is developed by integrating Si3N4/HZO/IGZO layers to realize three independent memory modes: electric long‐term, electric short‐term, and optical short‐term. This single‐device architecture functions as both a reservoir and readout layer, achieving 92.43% MNIST accuracy. It offers a fully hardware‐based,
Hyeonho Lee +9 more
wiley +1 more source
A Novel Neuro-Fuzzy Model for Multivariate Time-Series Prediction
Data, 2018 Time series forecasting can be a complicated problem when the underlying process shows high degree of complex nonlinear behavior. In some domains, such as financial data, processing related time-series jointly can have significant benefits.
Alexander Vlasenko +3 more
doaj +1 more source
High Voltage, 2021 This study presents a combined model based on the exploratory factor analysis (EFA) and the least square support vector machine (LSSVM) to predict the contamination degree of insulator surface. Firstly, EFA method is utilised to reduce numerous influence
Jiaxiang Sun +5 more
doaj +1 more source