Frequency Domains

Transmission/reflection coefficients measurement technique for determining materials complex permittivity at microwave (MW) frequencies with a modified inexpensive arrangement setup is examined in this paper. The general consideration is to use only the amplitudes of the transmission and reflection coefficients in presence of material sample to do permittivity determination. According to the analysis, the permittivity can be uniquely determined by measuring these two amplitudes when sample is prepared with large enough attenuation that multiple reflections between the two surfaces of the sample can be neglected. The validity of the method was proven by experiments, and numerical solutions of the measured data where achieved with the assistance of MathCAD™.

This paper discusses six most frequent methods used to extract different features in Electrocardiograph (ECG) signals namely Autoregressive (AR), Wavelet Transform (WT), Eigenvector, Fast Fourier Transform (FFT), Linear Prediction (LP), and Independent Component Analysis (ICA). The study reveals that Eigenvector method gives better performance in frequency domain for the ECG feature extraction. © 2012 IEEE.

ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6169708

ABSTRACT In this paper, we address the problem of reestablishing the network connectivity in post-disaster scenarios, where the original wireless infrastructure has been partitioned into multiple network fragments (called islands), operating on different frequencies. To this purpose, we propose the utilization of swarms of dedicated repairing units, called Stem-Nodes (SNs). SNs are provided with Cognitive Radio (CR) and self-positioning capabilities, in order to offer maximum reconfigurability in terms of mobility and wireless technologies supported. Moreover, swarms of SNs can self-organize into STEM-Mesh structure, that works as a dynamic backbone to connect heterogeneous islands using different technologies (e.g. Wi-Fi, Wi-MAX, etc). In this paper, we present three contributions pertaining to STEM-Mesh: (i) we describe a distributed motion control scheme (based on virtual springs approach) that enables SNs to self-organize into dynamic STEM-Mesh structures, (ii) we introduce a discovery scheme, through which SNs can explore the scenario in both spatial and frequency domains, and possibly connect the islands to the STEM-Mesh backbone and (iii) we validate the correctness of the proposed scheme, by verifying the optimal placements of the SNs composing the STEM-Mesh on a simplified scenario (e.g. chain topology). Finally, we evaluate through Omnet++ simulations the ability of STEM-Mesh to maximally re-establish connectivity on partitioned network scenarios.

Results are presented of wavelet analysis as applied to loop-back phase measurements of a high precision NIST-developed modem used for satellite two-way time transfer. It is also applied to phase measurements between a high-performance Cs and H-maser clock

Transmission/reflection coefficients measurement technique for determining materials complex permittivity at microwave (MW) frequencies with a modified inexpensive arrangement setup is examined in this paper. The general consideration is to use only the amplitudes of the transmission and reflection coefficients in presence of material sample to do permittivity determination. According to the analysis, the permittivity can be uniquely determined by measuring these two amplitudes when sample is prepared with large enough attenuation that multiple reflections between the two surfaces of the sample can be neglected. The validity of the method was proven by experiments, and numerical solutions of the measured data where achieved with the assistance of MathCAD™.

ABSTRACT This research separately obtained biological ages(BA) of cardiac and vascular systems from ten patients individually and in groups using two inference engines(IE). Electrocardiogram (ECG) and Arterial diameter variation (ADV) signals in radial artery were obtained from 157 patients for ten minutes, and from ECG, heart rate variability (HRV) values were obtained. Both signals were divided into three age groups: 36 young people from 14 to 30 years, 100 adults from 31 to 69 years and 21 seniors 70 to 81 years. Seven HRV variables were used in the time and frequency domains and seven variables for ADV signals in order to develop inference engines. The De Luca and Termini entropy function was applied to the results of the two inference engines, and the differences between them were shown. The sum(d) of the amount of changes in linguistic terms (LT), for the second age decade was calculated and this amount was related to biological changes with age: most changes in LT of HRV and ADV equals dmax=14. Biological age ranges from 20-40 years where 2 ≤ d ≤ 7, 40-77 years 9 ≤ d ≤ 12 for HRV signal, and 20-40 years where 4 ≤ d ≤ 5 and 40-74 years, 6 ≤ d ≤ 10 for the ADV signal. In some patients there was a big difference between their chronological and biological ages with potential risk in their cardiovascular systems. The state of the cardiovascular system was determined from the biological age.

This paper discusses six most frequent methods used to extract different features in Electrocardiograph (ECG) signals namely Autoregressive (AR), Wavelet Transform (WT), Eigenvector, Fast Fourier Transform (FFT), Linear Prediction (LP), and Independent Component Analysis (ICA). The study reveals that Eigenvector method gives better performance in frequency domain for the ECG feature extraction. © 2012 IEEE.

ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6169708