Predicting Hyper-Chaotic Time Series Using Adaptive Higher-Order Nonlinear Filter
Author:
Publisher
IOP Publishing
Subject
General Physics and Astronomy
Reference12 articles.
1. Predicting chaotic time series
2. Forecasting a chaotic time series using an improved metric for embedding space
3. Identification of models for chaotic systems from noisy data: implications for performance and nonlinear filtering
4. On selecting models for nonlinear time series
5. Prediction using unsupervised learning
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Nonlinear point-process estimation of neural spiking activity based on variational Bayesian inference;Journal of Neural Engineering;2022-08-01
2. A Data-based Compact High-order Volterra Model for Complex Blast Furnace System;IEEE Transactions on Industrial Informatics;2021
3. WOA-Based Echo State Network for Chaotic Time Series Prediction;Journal of the Korean Physical Society;2020-03
4. Data-Driven Modeling Based on Volterra Series for Multidimensional Blast Furnace System;IEEE Transactions on Neural Networks;2011-12
5. A Model-Free Predictor Based on Predictive Tracking for Time Series;2009 WASE International Conference on Information Engineering;2009-07
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3