自回归滑动平均模型
情态动词
系列(地层学)
谱密度估计
集合(抽象数据类型)
光谱分析
时间序列
协方差
算法
估计
数学
应用数学
计算机科学
统计
自回归模型
工程类
地质学
数学分析
傅里叶变换
光谱学
系统工程
化学
程序设计语言
量子力学
古生物学
物理
高分子化学
作者
Marta Berardengo,Giovanni Battista Rossi,Francesco Crenna
出处
期刊:Sensors
[Multidisciplinary Digital Publishing Institute]
日期:2021-06-23
卷期号:21 (13): 4280-4280
被引量:17
摘要
This paper deals with the spectral estimation of sea wave elevation time series by means of ARMA models. To start, the procedure to estimate the ARMA coefficients, based on the use of the Prony’s method applied to the auto-covariance series, is presented. Afterwards, an analysis on how the parameters involved in the ARMA reconstruction procedure—for example, the signal time length, the number of poles and data used—affect the spectral estimates is carried out, providing evidence on their effect on the accuracy of results. This allowed us to provide guidelines on how to set these parameters in order to make the ARMA model as accurate as possible. The paper focuses on mono-modal sea states. Nevertheless, examples also related to bi-modal sea states are discussed.
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