Because of the distance between the skull and brain and their different resistivities, electroencephalographic (EEG) data collected from any point on the human scalp includes activity generated within a large brain area. This spatial smearing of EEG data by volume conduction does not involve significant time delays, however, suggesting that the Independent Component Analysis (ICA) algorithm of ...

When exploiting independent component analysis (ICA) to perform blind source separation (BSS), it is assumed that sources are mutually independent. However, in practice, the latent sources are usually dependent to some extent. Subband decomposition ICA (SDICA) is an extension of ICA to admit source dependence. It assumes that each source is represented as the sum of some independent sub-compone...

BACKGROUND Despite a high prevalence of intracranial aneurysm (ICA) in autosomal dominant polycystic kidney disease (ADPKD), rupture events are rare. The current recommendations for ICA screening are based on expert opinions and studies with low levels of evidence. OBJECTIVES The aim of our study was to describe the attitudes of practicing nephrologists in Europe towards screening for ICA usi...

Independent Component Analysis (ICA) and Blind Source Separation (BSS) have become standard tools in multivariate data analysis. ICA continues to generate a flurry of research interest, resulting in increasing numbers of papers submitted to conferences and journals. Furthermore, there are many workshops and special sessions conducted in major conferences that focus on recent research results. T...

Wang, Yong G., and Stephen L. Lipsius. Genistein elicits biphasic effects on L-type Ca21 current in feline atrial myocytes. Am. J. Physiol. 275 (Heart Circ. Physiol. 44): H204–H212, 1998.—A perforated patch recording method was used to determine the effects of genistein (Gen), a protein tyrosine kinase (PTK) inhibitor, on basal L-type Ca21 current (ICa,L) in feline atrial myocytes. Gen (50 μM) ...

Independent Component Analysis (ICA) is a popular method for extracting independent features from visual data. However, as a fundamentally linear technique, there is always nonlinear residual redundancy that is not captured by ICA. Hence there have been many attempts to try to create a hierarchical version of ICA, but so far none of the approaches have a natural way to apply them more than once...

هدف: این پژوهش با هدف آزمون مدل روابط بین سبک‌های مقابله و خودکارآمدی حرفه‌ای استرس ادراک شده ناشی از حرفه‌های سلامت در گروهی پرستاران انجام شد. روش: همبستگی، 151 نفر شاغل بخش‌های اونکولوژی دانشگاه علوم پزشکی تهران به پرسشنامه باورهای شغلی برای (پیسانتی، لامباردو، لوسیدی، لازاری برتینی، 2008)، نسخة کوتاه سیاهه موقعیت‌های استرس‌زا (کوهن، جانگ استین، 2006) (ولفگانگ، 1988) پاسخ دادند. مفروض روش آم...

Title of Dissertation LEARNING ALGORITHMS FOR AUDIO AND VIDEO PROCESSING INDEPENDENT COMPONENT ANALYSIS AND SUPPORT VECTOR MACHINE BASED APPROACHES Yuan Qi Master of Science Dissertation directed by Professor Rama Chellappa Department of Electrical and Computer Engineering In this thesis we propose two new machine learning schemes a Subband based Independent Component Analysis scheme and a hybr...

Linear independent component analysis (ICA) learns simple cell receptive fields fromnatural images.Here,we show that linear complexvalued ICA learns complex cell properties from Fourier-transformed natural images, i.e. two Gabor-like filters with quadrature-phase relationship. Conventional methods for complex-valued ICA assume that the phases of the output signals have uniform distribution. We ...