Analyze the Efficiency of Blind Signal Extraction Algorithms in a Background of Impulse Noise Based on the Maximization of the Absolute Value of the Kurtosis.

 في هذا البحث، تم تحليل كفاءة خوارزميات استخلاص إشارة النبض العمياء في خلفية ضوضاء النبض على أساس تعظيم القيمة المطلقة للتفرطح. توليف خوارزميات الاستخلاص العمياء مع نقطة ثابتة وتدرس في تركيبة مع التدرج. ويظهر التقارب بين هذه الخوارزميات للشروط الاولية الصفرية وغير الصفرية .يتم صياغة برهان  ليمي ومبرهنتين للسماح باثبات تخصيص أعمى للإشارة وتحديد عدد القرارات فيما يتعلق باستخلاص الاإشارة. وقد أثبتت النمذجة أن خوارزمية النقطة الثابتة القائمة على تعظيم قيمة التفرطح المطلق هي أكثر كفاءة وتسمح بفصل إشارة النبضية المطلوبه بحيث ان نسبة الإشارة إلى الضوضاء تبلغ30 ديسيبل أكثر من خوارزمية التدرج التي لها نفس الوظيفة والهدف. ان المحاكاة لخوارزمية تعظيم قيمة التفرطح المطلق و خوارزمية النقطه الثابتة القائمة على تعظيم قيمة التفرطح المطلق تم تننفيذها باساخدام برنامج ماتلاب.In this paper, analyzed the efficiency of algorithms of blind pulse signal extraction in a background of impulse noise based on the maximization of the absolute value of the kurtosis. Synthesized blind separation algorithms with fixed point and it is considered in combination with the gradient. The convergence of these algorithms is shown for zero and nonzero initial conditions. A lemma and two theorems are formulated Allowing to prove the blind allocation of the signal and to determine the number of decisions with regard to signal extraction. Modeling established that the fixed point algorithm based on the maximization of the absolute kurtosis value is more efficient and allows to separate the pulse desire signal with the signal-to-noise ratio of 30 dB more than the gradient algorithm with the same objective function. Computer modeling of AbsoKurt and AbsoKurtFP algorithms Carried out in Simulink using Matlab programing

Semi-blind source extraction algorithm for fetal electrocardiogram based on generalized autocorrelations and reference signals

AbstractBlind source extraction (BSE) has become one of the promising methods in the field of signal processing and analysis, which only desires to extract “interesting” source signals with specific stochastic property or features so as to save lots of computing time and resources. This paper addresses BSE problem, in which desired source signals have some available reference signals. Based on this prior information, we develop an objective function for extraction of temporally correlated sources. Maximizing this objective function, a semi-blind source extraction fixed-point algorithm is proposed. Simulations on artificial electrocardiograph (ECG) signals and the real-world ECG data demonstrate the better performance of the new algorithm. Moreover, comparisons with existing algorithms further indicate the validity of our new algorithm, and also show its robustness to the estimated error of time delay

Non Invasive Foetal Monitoring with a Combined ECG - PCG System

Although modern ultrasound provides remarkable images and biophysical measures, the technology is expensive and the observations are only available over a short time. Longer term monitoring is achieved in a clinical setting using ultrasonic Doppler cardiotocography (CTG) but this has a number of limitations. Some pathologies and some anomalies of cardiac functioning are not detectable with CTG. Moreover, although frequent and/or long-term foetal heart rate (FHR) monitoring is recommended, mainly in high risk pregnancies, there is a lack of established evidence for safe ultrasound irradiation exposure to the foetus for extended periods (Ang et al., 2006). Finally, high quality ultrasound devices are too expensive and not approved for home care use. In fact, there is a remarkable mismatch between ability to examine a foetus in a clinical setting, and the almost complete absence of technology that permits longer term monitoring of a foetus at home. Therefore, in the last years, many efforts (Hany et al., 1989; Jimenez et al., 1999; Kovacs et al., 2000; Mittra et al., 2008; Moghavvemi et al., 2003; Nagal, 1986; Ruffo et al., 2010; Talbert et al., 1986; Varady et al., 2003) have been attempted by the scientific community to find a suitable alternative

Методы слепого подавления помех при обработке полезных сигналов : учебное пособие

Изложены методы подавления помех с использованием биспектральной обработки, алгоритмов слепого выделения (разделения) сигналов, алгоритмов на основе статистик высших порядков, адаптивных моделей, вейвлет- и векторно-матричного преобразования случайных процессов. Приводится классификация указанных методов и формулируется термин «слепые условия». Большинство изложенных методов реализованы в лабораторных работах на платформе Simulink. Предназначено для студентов, изучающих дисциплины, связанные с приемом и обработкой сигналов. Будет полезна аспирантам и научным работникам, занимающимся вопросами преодоления широкой априорной непараметрической неопределенности

Z.: Robust Extraction of Specific Signals with Temporal Structure. Neurocomputing

structur