Results 61 to 70 of about 25,760 (169)

Backpropagation in matrix notation

CoRR, 2017
7 pages, Remark 6 ...
openaire   +2 more sources

Spike-based computation using classical recurrent neural networks

Neuromorphic Computing and Engineering
Spiking neural networks (SNNs) are a type of artificial neural networks in which communication between neurons is only made of events, also called spikes.
Florent De Geeter, Damien Ernst, Guillaume Drion   +2 more
doaj   +1 more source

IMPROVEMENTS TO THE BACKPROPAGATION ALGORITHM [PDF]

Annals of the University of Petrosani: Economics, 2012
This paper presents some simple techniques to improve the backpropagation algorithm. Since learning in neural networks is an NP-complete problem and since traditional gradient descent methods are rather slow, many alternatives have been tried in order to accelerate convergence.
openaire   +1 more source

Practical Boolean Backpropagation

CoRR
11 ...
openaire   +2 more sources

Progressive Training of Hybrid Clipped Rectified Linear Unit for Resilient Convolution Neural Networks

IEEE Access
Convolutional neural networks used in safety-critical systems must remain reliable under hardware-induced faults. Activation clipping is an effective fault-mitigation technique, yet existing approaches face a fundamental trade-off: layer-wise clipping ...
Seyedhamidreza Mousavi, Mohammad Hasan Ahmadilivani, Jaan Raik, Maksim Jenihhin, Masoud Daneshtalab   +4 more
doaj   +1 more source

Analysis and Prediction of Vertical Office Network Bandwidth Using a Backpropagation-Based Neural Network

Ilkom Jurnal Ilmiah
The digitalization of business and operational processes in vertical offices has transformed work behaviour, creating a critical need for stable internet connectivity to ensure smooth operations.
Muhammad Jamil Asshiddiq, Iffatul Mardhiyah   +1 more
doaj   +1 more source

Design and Implementation of a Three-Layer Backpropagation Neural Network for Multi-Output Regression in Citizen-Science Impact Assessment

AI
Measuring the impact of citizen-science projects is hard because inputs are heterogeneous, mostly categorical, and sparse. We present Alquimics, a compact supervised neural network trained on one-hot project descriptors to predict impacts across five ...
Luigi Ceccaroni, Lyle Visa, Iain Visa
doaj   +1 more source

A direct normal irradiation forecasting model based on artificial neural networks

Revue des Énergies Renouvelables, 2016
We investigate the forecasting of the hourly Direct Normal Irradiation (DNI) using Artificial Neural Networks (ANN). The data used are hourly satellite data for the region of Ouarzazate in the South West Mediterranean basin region.
I. Belhaj, O. El Fatni, S. Barhmi, E.H. Saidi   +3 more
doaj  

DETERMINATION OF THE NEXT STOPPING FLOOR IN ELEVATOR TRAFFIC CONTROL BY MEANS OF NEURAL NETWORKS

Electrica, 2005
When a group of lifts serve together it is important coordinate the movements of the individual lifts in such a way that the lift group should operate efficiently.
C.Erdem İMRAK, Mustafa ÖZKIRIM
doaj  

High-Fidelity Backpropagation through Primate Foveal Cones. [PDF]

J Neurosci
Wienbar SR, Bryman GS, Do MTH.
europepmc   +1 more source