Chaotic signal denoising based on simplified convolutional denoising auto-encoder

DOI10.1016/j.chaos.2022.112333zbMath1504.94054OpenAlexW4283369224MaRDI QIDQ2112926

Shanxiang Lyu, Jiarui Deng, Shuting Lou

Publication date: 12 January 2023

Published in: Chaos, Solitons and Fractals (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.chaos.2022.112333

zbMATH Keywords

chaosdenoisingdeep learningconvolutional denoising auto-encoder

Mathematics Subject Classification ID

Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Analytic circuit theory (94C05)

Uses Software

• Torch
• Theano
• TensorFlow
• Caffe
• MXNet
• Adam

Cites Work

• Unnamed Item
• Unnamed Item
• Chaos-based digital communication systems. Operating principles, analysis methods, and performance evaluation
• Blind extraction of ECG signals based on similarity in the phase space
• Multiple dynamics analysis of Lorenz-family systems and the application in signal detection
• On the evidence of deterministic chaos in ECG: Surrogate and predictability analysis
• Theoretical Design and Circuit Implementation of Multidirectional Multi-Torus Chaotic Attractors

This page was built for publication: Chaotic signal denoising based on simplified convolutional denoising auto-encoder