降噪
混乱的
信号(编程语言)
计算机科学
语音识别
算法
模式识别(心理学)
编码器
视频去噪
人工智能
对象(语法)
视频跟踪
多视点视频编码
程序设计语言
操作系统
作者
Shuting Lou,Jiarui Deng,Shanxiang Lyu
出处
期刊:Social Science Research Network
[Social Science Electronic Publishing]
日期:2022-01-01
摘要
Chaos is a ubiquitous phenomenon in nature, but the observed chaotic signals are often contaminated by noises. In this work, we consider chaotic signal denoising from the perspective of deep learning, and propose a chaotic signal denoising method referred to as Simplified Convolutional Denoising Auto-Encoder (SCDAE). The method consists of an encoder and a decoder with $13$ layers in total, and requires minimal preprocessing steps. Our simulation results show that the proposed method can achieve smaller root mean square errors and better proliferation exponents than conventional denoising techniques.
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