Vibration Spectrum Analysis

Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test  eBooks & eLearning

Posted by hill0 at Sept. 16, 2021
Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test

Non-Gaussian Random Vibration Fatigue Analysis and Accelerated Test
English | 2022 | ISBN: 9811636931 | 287 Pages | PDF EPUB | 35 MB
Rotating Machinery Vibration: From Analysis to Troubleshooting, Second Edition (repost)

Rotating Machinery Vibration: From Analysis to Troubleshooting, Second Edition by Maurice L. Adams
English | 2009 | ISBN: 1439807175 | 476 pages | PDF | 7,9 MB

Learn How To Detect Dominant Cycles With Spectrum Analysis  eBooks & eLearning

Posted by ELK1nG at Sept. 28, 2022
Learn How To Detect Dominant Cycles With Spectrum Analysis

Learn How To Detect Dominant Cycles With Spectrum Analysis
Published 9/2022
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz
Language: English | Size: 673.75 MB | Duration: 0h 44m

Using the Fast Fourier Transform and the DFT-Goertzel algorithm to detect cycles in noisy data sets (financial markets)

Rotating Machinery Vibration: From Analysis to Troubleshooting  eBooks & eLearning

Posted by insetes at April 21, 2021
Rotating Machinery Vibration: From Analysis to Troubleshooting

Rotating Machinery Vibration: From Analysis to Troubleshooting By Maurice L. Adams
2000 | 371 Pages | ISBN: 0824702581 | PDF | 63 MB

Singular Spectrum Analysis for Time Series Ed 2  eBooks & eLearning

Posted by roxul at Nov. 23, 2020
Singular Spectrum Analysis for Time Series  Ed 2

Nina Golyandina, "Singular Spectrum Analysis for Time Series Ed 2"
English | ISBN: 3662624354 | 2020 | 155 pages | PDF | 4 MB

Singular Spectrum Analysis with R  eBooks & eLearning

Posted by AvaxGenius at June 15, 2018
Singular Spectrum Analysis with R

Singular Spectrum Analysis with R by Nina Golyandina
English | PDF,EPUB | 2018 | 284 Pages | ISBN : 3662573784 | 48.53 MB

This comprehensive and richly illustrated volume provides up-to-date material on Singular Spectrum Analysis (SSA). SSA is a well-known methodology for the analysis and forecasting of time series. Since quite recently, SSA is also being used to analyze digital images and other objects that are not necessarily of planar or rectangular form and may contain gaps. SSA is multi-purpose and naturally combines both model-free and parametric techniques, which makes it a very special and attractive methodology for solving a wide range of problems arising in diverse areas, most notably those associated with time series and digital images. An effective, comfortable and accessible implementation of SSA is provided by the R-package Rssa, which is available from CRAN and reviewed in this book.

Speech Spectrum Analysis  eBooks & eLearning

Posted by insetes at May 31, 2019
Speech Spectrum Analysis

Speech Spectrum Analysis By Sean A. Fulop (auth.)
2011 | 206 Pages | ISBN: 3642174779 | PDF | 6 MB

Singular Spectrum Analysis for Time Series  eBooks & eLearning

Posted by hill0 at Nov. 28, 2020
Singular Spectrum Analysis for Time Series

Singular Spectrum Analysis for Time Series
by Nina Golyandina

English | 2020 | ISBN: 3662624354 | 155 Pages | EPUB | 16 MB

Singular Spectrum Analysis: Using R  eBooks & eLearning

Posted by AvaxGenius at June 26, 2018
Singular Spectrum Analysis: Using R

Singular Spectrum Analysis: Using R by Hossein Hassani
English | PDF,EPUB | 2018 | 158 Pages | ISBN : N/A | 7.05 MB

This book provides a broad introduction to computational aspects of Singular Spectrum Analysis (SSA) which is a non-parametric technique and requires no prior assumptions such as stationarity, normality or linearity of the series. This book is unique as it not only details the theoretical aspects underlying SSA, but also provides a comprehensive guide enabling the user to apply the theory in practice using the R software.

Fundamentals of Spectrum Analysis  eBooks & eLearning

Posted by step778 at May 10, 2022
Fundamentals of Spectrum Analysis

Christoph Rauscher, "Fundamentals of Spectrum Analysis"
English | 2007 | pages: 208 | ISBN: 3939837016 | PDF | 5,9 mb