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In recent years there has been rapid progress in the development of
signal processing in general, and more specifically in the
application of signal processing and pattern analysis to biological
signals. Techniques, such as parametric and nonparametric spectral
estimation, higher order spectral estimation, time-frequency
methods, wavelet transform, and identifi cation of nonlinear
systems using chaos theory, have been successfully used to
elucidate basic mechanisms of physiological and mental processes.
Similarly, biological signals recorded during daily medical
practice for clinical diagnostic procedures, such as electroen
cephalograms (EEG), evoked potentials (EP), electromyograms (EMG)
and electrocardio grams (ECG), have greatly benefitted from
advances in signal processing. In order to update researchers,
graduate students, and clinicians, on the latest developments in
the field, an International Symposium on Processing and Pattern
Analysis of Biological Signals was held at the Technion-Israel
Institute of Technology, during March 1995. This book contains 27
papers delivered during the symposium. The book follows the five
sessions of the symposium. The first section, Processing and
Pattern Analysis of Normal and Pathological EEG, accounts for some
of the latest developments in the area of EEG processing, namely:
time varying parametric modeling; non-linear dynamic modeling of
the EEG using chaos theory; Markov analysis; delay estimation using
adaptive least-squares filtering; and applications to the analysis
of epileptic EEG, EEG recorded from psychiatric patients, and sleep
EEG."
In recent years there has been rapid progress in the development of
signal processing in general, and more specifically in the
application of signal processing and pattern analysis to biological
signals. Techniques, such as parametric and nonparametric spectral
estimation, higher order spectral estimation, time-frequency
methods, wavelet transform, and identifi cation of nonlinear
systems using chaos theory, have been successfully used to
elucidate basic mechanisms of physiological and mental processes.
Similarly, biological signals recorded during daily medical
practice for clinical diagnostic procedures, such as electroen
cephalograms (EEG), evoked potentials (EP), electromyograms (EMG)
and electrocardio grams (ECG), have greatly benefitted from
advances in signal processing. In order to update researchers,
graduate students, and clinicians, on the latest developments in
the field, an International Symposium on Processing and Pattern
Analysis of Biological Signals was held at the Technion-Israel
Institute of Technology, during March 1995. This book contains 27
papers delivered during the symposium. The book follows the five
sessions of the symposium. The first section, Processing and
Pattern Analysis of Normal and Pathological EEG, accounts for some
of the latest developments in the area of EEG processing, namely:
time varying parametric modeling; non-linear dynamic modeling of
the EEG using chaos theory; Markov analysis; delay estimation using
adaptive least-squares filtering; and applications to the analysis
of epileptic EEG, EEG recorded from psychiatric patients, and sleep
EEG."
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