Application of ESN prediction model based on compressed sensing in stock market

DOI10.1016/J.CNSNS.2021.105857zbMath1468.91157OpenAlexW3157403163MaRDI QIDQ2038120

Yanyan Li

Publication date: 9 July 2021

Published in: Communications in Nonlinear Science and Numerical Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.cnsns.2021.105857

zbMATH Keywords

time seriescompressed sensingESNreserve pool

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Artificial neural networks and deep learning (68T07) Financial markets (91G15)

Cites Work

• A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems
• Compressed sensing with coherent and redundant dictionaries
• The restricted isometry property and its implications for compressed sensing
• Extensions of compressed sensing
• A simple proof of the restricted isometry property for random matrices
• Optimization and applications of echo state networks with leaky- integrator neurons
• Decoding by Linear Programming
• Compressed sensing

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