Dielectrically loaded antennas meet growing interest in wireless and satellite communication due to small dimensions, controllable properties and perfect protection from damages even in the case of explosions. Real construction can be computed using time domain finite difference methods, but those methods meet big difficulties in dynamic problems. The generalized eigenfunction method applied earlier to diffraction problems and in laser theory can help to find within the reasonably limited amount of calculation not only static but dynamic characteristics of antennas. The importance of the dynamic analysis is easily seen from the presented figures, which show big changes in antenna parameters in the case of transmission (or reception) of short pulses. For high bit rate communication systems the detailed analysis of such changes is of vital importance.

A 3-D model for the His Purkinje System (HPS) of the heart is used to solve the direct problem and simulate the HPS surface electrogram. The same model is also used to solve the inverse problem. Results from normal and pathological models are described.

In this paper, a method for classifying material types is proposed where wavelets and neural networks are applied on laser speckle images. Multiresolution wavelet analysis was used for feature extraction while neural networks were used for classification. To improve the classifier performance, a reduced set of wavelet coefficients was obtained from all levels of transform resolutions. The effect of the laser angle of incidence on classification sensitivity was investigated. It was found that maximum sensitivity was achieved at an angle of 45 degrees. Results obtained showed that the proposed method was capable of classifying eight different materials from similar and different brands.

Some applications of geometrical modeling for biomedical signal processing are discussed. A new model of the heart nervous conductive system, used previously for the direct electrogram problem, is used now to solve the inverse problem. Geometrical modeling can give an approximate estimation of the source position and strength, even if the available amount of data is not sufficient for a correct mathematical solution. It can be useful in ECG and EEG inverse problems as well as in creating a model of human torso with non-uniform conductivity.

The generalized eigenfunction method applied earlier to diffraction problems and in laser theory can be useful in antenna design. It can help to find within the reasonably limited amount of calculation not only static but dynamic characteristics of the antenna. The importance of the dynamic analysis is discussed, demonstrating big changes in antenna parameters in the case of transmission ( or reception) of short pulses. For high bit rate communication systems the detailed analysis of such changes is of vital importance

A safe and simple system for the detection of sudden infant death syndrome (SIDS) is proposed. The system consists of an optoelectronic transceiver and electronic circuits capable of detecting infant breath, heart beating and any other infant movement. The system also includes an active alarm circuit. In case of absence of body activity or breathing, the active alarm will give the infant a mild push in order to awaken him or her. If there is no reaction, an audiovisual alarm is activated. Results obtained from six university students and three new born infants show that the system is capable of detecting apnea and SIDS.

In this paper, simulation of the His-Purkinje system (HPS) electrogram based on a three-dimensional model is proposed. The simulation is based on transformation of a two-dimensional HPS into a three-dimensional curvilinear system. Furthermore, the proposed HPS takes into consideration not just the left bundle branch but also the right bundle branch. Results obtained from normal and abnormal HPS electrograms show great similarity with those obtained experimentally.