2012/3

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Symbolical Analysis of RF-Network Problems using Mason’s Rule
(Společnost pro radioelektronické inženýrství, 2012-09) Schwerg, Nikolai
We briefly review Mason’s rule for the computation of RF-network problems and show its implementation into the software package freeMASON. This tool solves symbolically Mason’s rule for any wave quantity and allows to derive analytical expressions as well as their functional evaluation. We demonstrate our approach studying the effect of an unbalanced magictee on the RF power distribution to two accelerating cavities.
Empirical Relations for Optical Attenuation Prediction from Liquid Water Content of Fog
(Společnost pro radioelektronické inženýrství, 2012-09) Khan, M. S.; Grabner, M.; Muhammad, S. S.; Awan, M. S.; Leitgeb, E.; Kvicera, V.; Nebuloni, R.
Simultaneous measurements of the liquid water content (LWC) and optical attenuation have been analyzed to predict optical attenuation caused by fog particles. Attenuation has been measured at two different wavelengths, 830 nm and 1550 nm, across co-located links. Five months measured data have been processed to assess power-law empirical models, which estimate optical attenuation from the LWC. The proposed models are compared with other published models and are demonstrated to perform sufficiently well to predict optical attenuation if the LWC values are available.
Microstrip Cross-coupled Interdigital SIR Based Bandpass Filter
(Společnost pro radioelektronické inženýrství, 2012-09) Maharjan, Ram Krishna; Shrestha, Bhanu; Kim, Nam-Young
A simple and compact 4.9 GHz bandpass filter for C-band applications is proposed. This paper presents a novel microstrip cross-coupled interdigital half-wavelength stepped impedance resonator (SIR) based bandpass filter (BPF).The designed structure is similar to that of a combination of two parallel interdigital capacitors. The scattering parameters of the structure are measured using vector network analyzer (VNA). The self generated capacitive and inductive reactances within the interdigital resonators exhibited in a resonance frequency of 4.9 GHz. The resonant frequency and bandwidth of the capacitive cross-coupled resonator is directly optimized from the physical arrangement of the resonators. The measured insertion loss (S21) and return loss (S11) were 0.3 dB and 28 dB, respectively, at resonance frequency which were almost close to the simulation results.
MISO Current-mode Biquad Filter with Independent Control of Pole Frequency and Quality Factor
(Společnost pro radioelektronické inženýrství, 2012-09) Jaikla, Winai; Siripongdee, Surapong; Suwanjan, Peerawut
This article presents a three-inputs single-output biquadratic filter performing completely standard functions: low-pass, high-pass, band-pass, band-reject and all-pass functions, based on current controlled current conveyor transconductance amplifier (CCCCTA). The quality factor and pole frequency can be electronically/independently tuned via the input bias current. The proposed circuit uses 2 CCCCTAs and 2 grounded capacitors without external any resistors which is very suitable to further develop into an integrated circuit. The filter does not require double input current signal. Each function response can be selected by suitably selecting input signals with digital method. Moreover, the circuit possesses high output impedance which would be an ideal choice for current-mode cascading. The PSPICE simulation results are included to verify the workability of the proposed filter. The given results agree well with the theoretical anticipation.
Segmentation of Speech and Humming in Vocal Input
(Společnost pro radioelektronické inženýrství, 2012-09) Sporka, Adam J.; Polacek, Ondrej; Havlik, Jan
Non-verbal vocal interaction (NVVI) is an interaction method in which sounds other than speech produced by a human are used, such as humming. NVVI complements traditional speech recognition systems with continuous control. In order to combine the two approaches (e.g. "volume up, mmm") it is necessary to perform a speech/NVVI segmentation of the input sound signal. This paper presents two novel methods of speech and humming segmentation. The first method is based on classification of MFCC and RMS parameters using a neural network (MFCC method), while the other method computes volume changes in the signal (IAC method). The two methods are compared using a corpus collected from 13 speakers. The results indicate that the MFCC method outperforms IAC in terms of accuracy, precision, and recall.

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