Advances in Processing and Pattern Analysis of Biological by Will Gersch (auth.), Isak Gath, Gideon F. Inbar (eds.)

By Will Gersch (auth.), Isak Gath, Gideon F. Inbar (eds.)

In fresh years there was speedy growth within the improvement of sign processing mostly, and extra particularly within the software of sign processing and trend research to organic signs. recommendations, similar to parametric and nonparametric spectral estimation, better order spectral estimation, time-frequency equipment, wavelet rework, and identifi­ cation of nonlinear platforms utilizing chaos thought, were effectively used to clarify simple mechanisms of physiological and psychological methods. equally, organic signs recorded in the course of day-by-day clinical perform for medical diagnostic strategies, akin to electroen­ cephalograms (EEG), evoked potentials (EP), electromyograms (EMG) and electrocardio­ grams (ECG), have drastically benefitted from advances in sign processing. in an effort to replace researchers, graduate scholars, and clinicians, at the most modern advancements within the box, a global Symposium on Processing and development research of organic indications was once held on the Technion-Israel Institute of expertise, in the course of March 1995. This e-book comprises 27 papers brought throughout the symposium. The ebook follows the 5 periods of the symposium. the 1st part, Processing and development research of ordinary and Pathological EEG, bills for a number of the newest advancements within the quarter of EEG processing, specifically: time various parametric modeling; non-linear dynamic modeling of the EEG utilizing chaos idea; Markov research; hold up estimation utilizing adaptive least-squares filtering; and purposes to the research of epileptic EEG, EEG recorded from psychiatric sufferers, and sleep EEG.

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1. P.. Van Neerven. , Noest, A .. and Lopes da Silva. F. H .. 1991, Chaos or noise in EEG signals; dependence on state and brain stte. Electroenceph. c/in. Neurophysiol. 79:371-381. Racine. R . I .. 1972, Modification of seizure activity by electncal stimulation. II. Motor seizure, Electroenceph. c/in. Neurophrsiol. 32:281-294. , Labech. 1.. Bak. C. K .. and Sabers, A .. 1990, Magnetoencephalography and attractor dimension: normal subjects and epileptic patients. , and Bullock, H. ), Brain Dynamics, Springer-Verlag:Berlin, pp.

All patients were diagnosed as meeting DSM-IIIR criteria for obsessive-compulsive disorder by their referring psychiatrist, and each had been suffering from severe and intractable OCD for at least one year. Since the data came from a retrospective study, symptom severity rating scale data was not available. Healthy normal subjects were recruited and also underwent routine neurological examinations. Any patients or control subjects with a neurological history were excluded from the study, leaving study populations of 13 patients with severe OCD and 11 normal control subjects.

I for the case of the Duffing equation. A comparison of the plots of 0 2 for the real (Fig. I C) and surrogate signals (Fig. 1D) shows the clear difference between what one expects from a chaotic attractor and an epoch of random noise. In the same figure, we see that in the case of the limit cycle, the value of 0 2 is one, as theoretically expected. We should note that there are other types of dimensions being used to characterize the properties of attractors, besides the correlation dimension, such as the Hausdorff dimension, the Kolmogorov entropy, the Lyapunov exponents, and the information dimen- 26 F.

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