It is routine nowadays for signal analysis to be carried out in the frequency domain. However, the decision to apply a Fourier Transform to the data is often taken without much thought. Consideration should first be given to alternative methods. There are a number of excellent analysis techniques available for investigating the characteristics of time domain data. In this concluding chapter we shall introduce correlation, which is probably the best-known time domain analysis technique. There are many others, but a detailed discussion of them all would require more space than is available in this book. The reader who needs more than an introduction to the subject should look at some of the excellent books available, references to which are given in the bibliography at the end of the book.
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Bibliography and Further Reading
- C. Chatfield, The Analysis of Time Series, 2nd edn, Chapman and Hall, 1980.Google Scholar
- K. G. Beauchamp, Signal Processing, Allen and Unwin, 1973.Google Scholar
- J. S. Bendat and A. G. Piersol, Measurement and Analysis of Random Data, Wiley, 1966.Google Scholar
- J. S. Bendat, Principles and Applications of Random Noise Theory, Wiley, 1958.Google Scholar
- J. S. Bendat and A. G Piersol, Engineering Applications of Correlation and Spectral Analysis, Wiley, 1980.Google Scholar