View Full Version : Re: Data filtering

06-19-1997, 03:23 AM
> Priority: NORMAL
> Date sent: Thu, 19 Jun 1997 12:24:36 +0100
> Send reply to: G.Giakas@staffs.ac.uk
> From: Giannis Giakas
> Subject: Data filtering

Good stuff, GG.

Agree with you entirely.

On another matter, could you contact Calvin URGENTLY to discuss the
use of your extrapolation method on our European Championships data.



> Dear biomch-l subscribers
> Although I agree with most points of the recent postings by Prof.
> Hatze, I would like to address the issue of "fundamental flaws". As
> it was pointed out, there was an inaccurate DESCRIPTION in one of our
> recent publications of the fact that the derivatives are considered
> for the determination of the optimally filtered series in ORFOS
> algorithm. This however does not affect the results of the comparison
> study, as the original algorithms presented in the literature were
> used, and not algorithms were developed specifically for this study.
> As such, this inaccurate description in the INTRODUCTION of the paper
> does not present a "fundamental flaw" in our view.
> Furthermore there are more "fundamental flaws" when some of these so
> called "automatic" filtering methods are accepted and published on
> the basis of subjective choices of factors that determine the
> behaviour of the methods validation using a limited number of test
> signals and not clear explanation of the required assumptions and
> limitations of the method. In such cases readers led to believe that
> any "automatic" method can be applied to any set of data without
> examining in detail the assumptions and limitations of the method.
> For this reason comparison studies using a wide range of signals are
> useful.
> Another problem is that when a researcher is not allowed to use an
> algorithm for a single research study for evaluation-comparison
> purposes and he/she is expected to purchase a whole software package
> or even a whole hardware system to access a particular method.
> There is also agreement that there is already a large number of
> "automatic" or "semi-automatic" filtering methods and there is
> certainly "re-invention of the wheel" when single and subjective
> methods for the determination of the cut-off frequency are used. The
> important thing, as it was pointed out before, is to ensure that the
> assumptions of a particular method are satisfied when applied to a
> specific set of data.
> Personally, I prefer to use a "semi-automatic" method so I have some
> freedom to alter the parameters of the method than to use the
> black-box approach of a "full-automatic" method.
> Thank you very much for your time.
> Giannis
> --
> Giannis Giakas
> Division of SHE
> Staffordshire University
> Stoke-on-Trent ST4 2DF
> Tel : +44 1782 294292
> Fax : +44 1782 747167
> Email: g.giakas@staffs.ac.uk
> http://www.staffs.ac.uk/sands/scis/sport/giannis/gian1.htm
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