Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Periodic Signals Read chapter Read first chapter

2017 | OriginalPaper | Chapter

6. Signal Changes

Author : Jose Maria Giron-Sierra

Published in: Digital Signal Processing with Matlab Examples, Volume 1

Publisher: Springer Singapore

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Signal changes along time can have a meaning. There are many electronic instruments made for the monitoring of signal changes. For instance, the monitoring of heart pace and other biomedical signals, the detection of intruders by means of infrared sensors, etc. But there is not only interest from data acquisition applications; humans do use signal changes along time for communication purposes, through modulation techniques. Needless to say how important communications and data acquisition are nowadays. The chapter highlights different kinds of signal changes that could be relevant. Several visualization and analysis tools are introduced, like the spectrogram, the Hilbert transform, the chirp transform, and the cepstral analysis (interesting for voice recognition)

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
previous chapter Digital Filters
next chapter Time-Frequency Analysis
Literature
1.
2.
3.
M.L. Bedran, A comparison between the doppler and cosmological redshifts. Am. J. Phys. 70(4), 406–408 (2002)CrossRef
4.
K.J. Blinowska, J. Zygierewicz, Practical Biomedical Signal Analysis Using MATLAB (CRC Press, Boca Raton, 2012)
5.
L.I. Bluestein, A linear filter approach to the computation of the discrete Fourier transform. Northeast Electr. Res. Eng. Meet. Rec. 10, 218–219 (1968)
6.
B.P. Bogert, M.J. Healy, J.W. Tukey, The quefrency alanysis of time series for echoes: cepstrum, pseudo-autocovariance, cross-cepstrum and saphe cracking, in: Procedings of the Symposium Time Series Analysis vol. 15 (1963), pp. 209–243
7.
J. Bradbury, S. Vehrencamp, Principles of Animal Communication (Sinauer Press, Sunderland, 2011)
8.
J.J. Burred, A. Robel, T. Sikora, Dynamic spectral envelope modeling for timbre analysis of musical instrument sounds. IEEE Trans. Audio Speech Lang. Process. 18(3), 663–674 (2010)CrossRef
9.
X. Cheng, J.V. Hart, J.S. Walker, Time-frequency analysis of musical rhythm. Not. AMS 56(3), 356–372 (2009)MathSciNetMATH
10.
D.G. Childers, D.P. Skinner, R.C. Kemerait, The cepstrum: a guide to processing. Proc. IEEE 65(10), 1428–1443 (1977)CrossRef
11.
C. Clark Acoustic communication by animals, in Proceedings of the 3 \(^{rd}\) International Symposium on Acoustic Communication by Animals (2011)
12.
K. Doi, Diagnostic imaging over the last 50 years: research and development in medical imaging science and technology. Phys. Med. Biol. 51(13), 5–27 (2006)CrossRef
13.
C.E. Felder, A real-time variable resolution chirp z-transform. Master’s thesis, Rochester Institute of Technology (2007)
14.
15.
C. Gonzalez, J. Pleite, V. Valdivia, J. Sanz, An overview of the on line application of frequency response analysis (FRA), in Proceedings of the IEEE International Symposium Industrial Electronics, ISIE (2007), pp. 1294–1299
16.
S.L. Hopp, M.J. Owren, C.S. Evans, Animal Acoustic Communication (Springer, Heidelberg, 1998)CrossRef
17.
E. Jantunen, A summary of methods applied to tool condition monitoring in drilling. Int. J. Mach. Tools Manuf. 42(9), 997–1010 (2002)CrossRef
18.
M. Johansson, The Hilbert Transform. Master’s thesis, Växjö University, Sweden (1999)
19.
J. Kaffanke, T. Dierkes, S. Romanzetti, M. Halse, J. Rioux, M.O. Leach, N.J. Shah, Application of the chirp z-transform to MRI data. J. Magn. Reson. 178(1), 121–128 (2006)CrossRef
20.
21.
F.W. King, Hilbert Transforms (Cambridge University Press, Cambridge, 2015)
22.
J.A. Kisslo, D.B. Adams, Principles of Doppler Echocardiography and the Doppler Examination #1 (Ciba-Geigy, London, 1987)
23.
24.
25.
B. Logan, Mel frequency cepstral coefficients for music modeling, in Proceedings of the International Symposium on Music Information Retrieval (ISMIR), pp. 1–11 (2000)
26.
27.
D. Maulik, Doppler sonography: a brief history, in Doppler Ultrasound in Obstetrics and Gynecology (Springer, Heidelberg, 2005), pp. 1–7
28.
U. Meyer-Bäse, H. Natarajan, E. Castillo, A. García, Faster than the FFT: the chirp-z RAG-n discrete fast fourier transform. Frequenz 60, 147–151 (2006)CrossRef
29.
S. Molau, M. Pitz, R. Schluter, H. Ney, Computing mel-frequency cepstral coefficients on the power spectrum, in Proceedings of the International Conference Acoustics, Speech, and Signal Processing (ICASSP 2001), vol. 1 (2001), pp. 73–76
30.
L. Muda, M. Begam, I. Elamvazuthi, Voice recognition algorithms using mel frequency cepstral coefficient (MFCC) and dynamic time warping (DTW) techniques (2010). arXiv:​1003.​4083
31.
C.T. Nguyen, J.P. Havlicek, AM-FM models, partial Hilbert transform, and the monogenic signal, in Proceedings of the IEEE International Conference Image Processing, (ICIP) (2012), pp. 2337–2340
32.
A.V. Oppenheim, R.W. Schafer, From frequency to quefrency: a history of the cepstrum. IEEE Signal Process. Mag. 21(5), 95–106 (2004)CrossRef
33.
M.A. Quiñones, C.M. Otto, M. Stoddard, A. Waggoner, W.A. Zoghbi, Recommendations for quantification of doppler echocardiography: a report from the doppler quantification task force of the nomenclature and standards committee of the american society of echocardiography. J. Am. Soc. Echocardiogr. 15(2), 167–184 (2002)CrossRef
34.
35.
L. Rabiner, R.W. Schafer, C.M. Rader, The chirp z-transform algorithm. IEEE Trans. Audio Electroacoust. 17(2), 86–92 (1969)MathSciNetCrossRef
36.
L. Rabiner, R.W. Schafer, C.M. Rader, The chirp z-transform algorithm and its application. Bell Syst. Tech. J. 48(5), 1249–1292 (1969)MathSciNetCrossRef
37.
L. Rabiner, The chirp z-transform algorithm - a lesson in serendipity. IEEE Signal Process. Mag. 21(2), 118–119 (2004)CrossRef
38.
P. Rajmic, Z. Prusa, C. Wiesmeyr, Computational cost of chirp z-transform and generalized goertzel algorithm, in Proceedings of the IEEE 22 \(^{nd}\) European Signal Processing Conference, (EUSIPCO) (2014), pp. 1004–1008
39.
R.B. Randall, A history of cepstrum analysis and its application to mechanical problems, in International Conference on Surveillance 7, Chartres, France, October (2013), pp. 1–16
40.
R.B. Randall, B. Peeters, J. Antoni, S. Manzato, New cepstral methods of signal pre-processing for operational modal analysis, in Proceedings of ISMA (2012), pp. 755–764
41.
A.G. Rehorn, J. Jiang, P.E. Orban, State-of-the-art methods and results in tool condition monitoring: a review. Int. J. Adv. Manufact. Technol. 26(7–8), 693–710 (2005)CrossRef
42.
43.
D. Risch, N.J. Gales, J. Gedamke, L. Kindermann, D.P. Nowacek, A.J. Read, A.S. Friedlaender, Mysterious bio-duck sound attributed to the Antarctic minke whale (Balaenoptera bonaerensis). Biol. Lett. 10(4), 1–5 (2015)
44.
Y. Shao, Z. Rao, Z. Jin, Online state diagnosis of transformer windings based on time-frequency analysis. WSEAS Trans. Circ. Syst. 8(2), 227–236 (2009)
45.
S. Sigurdsson, K.B. Petersen, T. Lehn-Schiøler, Mel frequency cepstral coefficients: an evaluation of robustness of MP3 encoded music, in Proceedings of the Seventh International Conference on Music Information Retrieval, (ISMIR) (2006)
46.
L.M. Smith, A Multiresolution Time-Frequency Analysis and Interpretation of Musical Rhythm. Ph.D. thesis, University of Western Australia (2000)
47.
S.S. Stevens, J. Volkmann, E.G. Newman, A scale for the measurement of the psychological magnitude pitch. J. Acoust. Soc. Am. 8, 185–190 (1937)CrossRef
48.
P. Stoica, R. Moses, Spectral Analysis of Signals (Prentice Hall, Upper Saddle River, 2005)
49.
R. Tong, R.W. Cox, Rotation of NMR images using the 2D chirp-z transform. Magn. Reson. Med. 41(2), 253–256 (1999)CrossRef
50.
M. Wang, A.J. Vandermaar, K.D. Srivastava, Review of condition assessment of power transformers in service. IEEE Electr. Insul. Mag. 18(6), 12–25 (2002)CrossRef
51.
M.M. Wood, L.E. Romine, Y.K. Lee, K.M. Richman, M.K. O’Boyle, D.A. Paz, D.H. Pretorius, Spectral doppler signature waveforms in ultrasonography: a review of normal and abnormal waveforms. Ultrasound Q. 26(2), 83–99 (2010)CrossRef
52.
Metadata
Title
Signal Changes
Author
Jose Maria Giron-Sierra
Copyright Year
2017
Publisher
Springer Singapore
Book
Digital Signal Processing with Matlab Examples, Volume 1

Print ISBN: 978-981-10-2533-4

Electronic ISBN: 978-981-10-2534-1

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-981-10-2534-1_6