Optimization of neural network training for image recognition based on trigonometric polynomial approximation

DOI10.1134/S0361768821080272zbMath1485.68239OpenAlexW4200312734MaRDI QIDQ2064396

B. Pulido-Gaytan, N. Kuchukova, Andrei Tchernykh, N. Vershkov, Jorge M. Cortés-Mendoza, Viktor Kuchukov, Mikhail Babenko

Publication date: 5 January 2022

Published in: Programming and Computer Software (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1134/s0361768821080272

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Computing methodologies for image processing (68U10) Trigonometric approximation (42A10)

Uses Software

• MNIST
• PyTorch
• ADADELTA

Cites Work

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• Search for the global extremum using the correlation indicator for neural networks supervised learning
• Implementation of spectral transformations in the class of fast neural networks
• Training Products of Experts by Minimizing Contrastive Divergence
• Collected Works
• On the representation of continuous functions of many variables by superposition of continuous functions of one variable and addition
• A logical calculus of the ideas immanent in nervous activity
• Digital Signal Processing

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