By Panos Z. Marmarelis M.D., Ph.D., Vasilis Z. Marmarelis (auth.)
In learning physiological platforms bioscientists are always confronted with the matter of offering descriptions of cause-effect relationships. This job is generally performed throughout the functionality of stimulus-response experiments. long ago, the layout of such experiments has been advert hoc, incomplete, and definitely inefficient. Worse but, bioscientists have did not reap the benefits of advances in fields without delay concerning their difficulties (specifically, advances within the sector of platforms analysis). The raison d'etre of this publication is to rectify this deficiency by way of offering the physiologist with methodological instruments that might be important to her or him in daily labora tory encounters with physiological structures. The ebook was once written in order that it'd be functional, worthwhile, and up-to date. With this in brain, components of it provide step by step descriptions of within the laboratory. it really is was hoping that this systematic methods to be increases the usefulness of the booklet to the typical learn physiologist and, possibly, decrease the necessity for in-depth wisdom of a few of the linked arithmetic. even supposing the fabric bargains with state-of-the paintings options in platforms and sign research, the mathematical point has been stored low in order to be understandable to the common physiologist with out large education in arithmetic. To this finish, mathematical rigor is usually sacrificed without difficulty to intuitive basic arguments.
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Additional resources for Analysis of Physiological Systems: The White-Noise Approach
Therefore, it seems more reasonable, instead of giving a single value as the estimate, to give a range (interval) within which the true parameter value wi11lie with a given degree of confidence. That is, a probability statement will be made about the degree of certainty with which the true parameter value lies within a specified range. Assume that we are trying to estimate the mean value, /-t, of a signal x(t). The signal is sampled every At seconds, producing a sequence of samples where Xk =x(kM).
Pnn(t) is significant only for small values of t. For example, if aCt) is a sine wave, then its autocorrelation is also a sine wave of the same frequency. Thus, if aCt) is contaminated by broadband uncorrelated noise n (t) then the sine wave form can be easily detected by looking at Main power supply 60-Hz noise, contributions of other neighboring physiological sources such as blood vessels or muscle electrical activity, etc. If the frequency ranges of these contaminating noise sources are identified, then it is sometimes possible to design a filter (as discussed later, in Sec. 8) that reduces unwanted frequency components. For example, Fig. 13A shows an ECG (electrocardiogram) signal that is heavily contaminated by noise. The frequency spectrum of this signal is shown in the same figure.
Analysis of Physiological Systems: The White-Noise Approach by Panos Z. Marmarelis M.D., Ph.D., Vasilis Z. Marmarelis (auth.)
Main power supply 60-Hz noise, contributions of other neighboring physiological sources such as blood vessels or muscle electrical activity, etc. If the frequency ranges of these contaminating noise sources are identified, then it is sometimes possible to design a filter (as discussed later, in Sec. 8) that reduces unwanted frequency components. For example, Fig. 13A shows an ECG (electrocardiogram) signal that is heavily contaminated by noise. The frequency spectrum of this signal is shown in the same figure.