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Mass Spectrometry 2019
March 04-05, 2019
Berlin, Germany
Mass Spectrometry
9th Edition of International Conference on
International Journal of Drug Development and Research
ISSN: 0975-9344 Page 17
A novel method for the interpretation
of spectrometer signals based on delta-
modulation and similarity determination
Petra Perner
Institute of Computer Vision and Applied Computer Sciences IBaI, Germany
For the application of mass spectrometry in different
areas the automatic intelligent spectrometer signal
analysis methods are necessary. These methods
should be robust and machine learnable automatic
signal interpretation methods. These methods should
be taken into account that not so much spectrometer
data about the application are available from scratch
and that these data need to be learnt while using the
spectrometer system. We propose to represent the
spectrometer signal by a sequence of 0/1 characters
obtained from a specific delta modulator. This prevents
us from a particular symbolic description of peaks and
background. The interpretation of the spectrometer
signal is done by searching for a similar signal in a
constantly increasing data base. The comparison
betweenthetwosequencesisdonebasedonasyntactic
similarity measure. We describe in this paper how the
signal representation is obtained by delta modulation,
the similaritymeasure for the comparison of the signals
and give results for searching the data base.
Biography
Petra Perner is the Director of the Institute of Computer Vi-
sion and Applied Computer Sciences IBaI. (IAPR Fellow)
She received her Diploma Degree in Electrical Engineering
and her PhD Degree in Computer Science for the work on
Data Reduction Methods for Industrial Robots with Direct
Teach-in-Programing. Her habilitation thesis was about “A
Methodology for the Development of Knowledge-Based Im-
age-Interpretation Systems”. She has been the Principal In-
vestigator of various national and international research proj-
ects. She received several research awards for her research
work and has been awarded with three business awards for
her work on bringing intelligent image interpretation meth-
ods and dataminingmethods into business. Her research in-
terest is image analysis and interpretation, machine learning,
data mining, big data, machine learning, image mining and
case-based reasoning.
Petra Perner, Int J Drug Dev & Res 2019, Volume 11
DOI: 10.21767/0975-9344-C1-004