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Titlebook: Automatic Autocorrelation and Spectral Analysis; Piet M. T. Broersen Textbook 2006 Springer-Verlag London 2006 Analysis.Augmented Reality.

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发表于 2025-3-21 17:44:04 | 显示全部楼层 |阅读模式
期刊全称Automatic Autocorrelation and Spectral Analysis
影响因子2023Piet M. T. Broersen
视频video
发行地址Shows the reader which spectral methods (algorithms) are useful in practice.Demonstrates the clear advantages of using parametric rather than non-parametric models for spectral analysis.Provides the r
图书封面Titlebook: Automatic Autocorrelation and Spectral Analysis; Piet M. T. Broersen Textbook 2006 Springer-Verlag London 2006 Analysis.Augmented Reality.
影响因子."Automatic Autocorrelation and Spectral Analysis" gives random data a language to communicate the information they contain objectively. It takes advantage of greater computing power and robust algorithms to produce enough candidate models of a given group of data to be sure of providing a suitable one. Improved order selection guarantees that one of the best (often the best) will be selected automatically. Written for graduate signal processing students and for researchers and engineers using time series analysis for applications ranging from breakdown prevention in heavy machinery to measuring lung noise for medical diagnosis, this text offers:..- tuition in how power spectral density and the autocorrelation function of stochastic data can be estimated and interpreted in time series models;..- extensive support for the MATLAB® ARMAsel toolbox;..- applications showing the methods in action;..- appropriate mathematics for students to apply the methods with references for those who wish to develop them further..
Pindex Textbook 2006
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