考虑数值不确定性的非线性模型验证

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摘要翻译：
本文提出了一种考虑数值计算误差的模型验证方法。研究了正弦映射和Duffing-Ueda电路系统的两个辨识模型。应用了RMSE和MAPE指标。我们已经表明，经过几次迭代，可能会注意到文献中提供的索引之间的一些有意义的差异。这一差异已经计算出大约34%。
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英文标题：
《Incorporating Numerical Uncertainties for Validation of Nonlinear Models》
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作者：
Igor C. Silva, Gabriel H. A. Silva, Samir A. M. Martins, Erivelton G.
  Nepomuceno
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最新提交年份：
2017
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分类信息：

一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Signal Processing        信号处理
分类描述：Theory, algorithms, performance analysis and applications of signal and data analysis, including physical modeling, processing, detection and parameter estimation, learning, mining, retrieval, and information extraction. The term "signal" includes speech, audio, sonar, radar, geophysical, physiological, (bio-) medical, image, video, and multimodal natural and man-made signals, including communication signals and data. Topics of interest include: statistical signal processing, spectral estimation and system identification; filter design, adaptive filtering / stochastic learning; (compressive) sampling, sensing, and transform-domain methods including fast algorithms; signal processing for machine learning and machine learning for signal processing applications; in-network and graph signal processing; convex and nonconvex optimization methods for signal processing applications; radar, sonar, and sensor array beamforming and direction finding; communications signal processing; low power, multi-core and system-on-chip signal processing; sensing, communication, analysis and optimization for cyber-physical systems such as power grids and the Internet of Things.
信号和数据分析的理论、算法、性能分析和应用，包括物理建模、处理、检测和参数估计、学习、挖掘、检索和信息提取。“信号”一词包括语音、音频、声纳、雷达、地球物理、生理、（生物）医学、图像、视频和多模态自然和人为信号，包括通信信号和数据。感兴趣的主题包括：统计信号处理、谱估计和系统辨识；滤波器设计；自适应滤波/随机学习；（压缩）采样、传感和变换域方法，包括快速算法；用于机器学习的信号处理和用于信号处理应用的机器学习；网络与图形信号处理；信号处理中的凸和非凸优化方法；雷达、声纳和传感器阵列波束形成和测向；通信信号处理；低功耗、多核、片上系统信号处理；信息物理系统的传感、通信、分析和优化，如电网和物联网。
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英文摘要：
  This paper proposes a model validation method that incorporates error due to numerical procedures. Two identified models for Sine Map and Duffing-Ueda Circuit systems have been investigated. The indexes RMSE and MAPE have been applied. We have shown that after some few iterates, it is possible to notice some significative difference between index provided in the literature. This difference has been computed in around 34%.
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PDF链接：
https://arxiv.org/pdf/1711.07757

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关键词：不确定性 线性模型 模型验证 非线性 不确定 辨识 方法 不确定性 Ueda 映射

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