A. Usikov Institute of Radio Physics and Electronics,
National Academy of Sciences of Ukraine
12, Academician Proskura Str., Kharkiv 61085, Ukraine
The Special Features of Spiral-Enhanced Slow-Surface Wave Excitation on a Plasma Column Generated in Free Space
Universidad Autonoma del Carmen, Ciudad del Carmen, Campeche, Mexico
Projection Matrixes and CFAR Detection of Signals in the Case of Unknown Covariance Hermitian Matrix of Interferences
The paper is devoted to investigation of determinate signals with a constant false alarm rate (CFAR) in the case of the unknown Hermitian interference covariance matrix, when the detection is based on the Neyman-Pearson criterion on the estimate of the clutter circulant covariance matrix. We establish the conditions a detector must fulfill in order to ensure the CFAR property with presence of the correlated clutter.
National Polytechnic of Mexico, Mexico
Institute of Radio Engineering and Electronics, Moscow, Russia
Radar Processing on Basis of Kravchenko-Rvachev’s Functions for Resolving of Numerical Targets
The signal choice in the radar system is being governed by various factors including power considerations, maximum range and resolution. Using linear FM signal in the radar it has been tested the performance of the weighting window processing technique and matched receiver filter to attenuate the side lobe levels. We have investigated novel weighting windows employing the Kravchenko-Rvachev’s functions for reduction of the side lobes. Some important characteristics like as gain, level of the side lobes, principal lobe width, etc. are calculated and compared with other classical window functions. The results show the advantages of the new Kravchenko-Rvachev’s weighting functions.
Control of Mobile Robots by Means of Internet
Fail-Safe Model of Interaction of Autonomous Systems in Global Network
Implementation of the Algorithm of Simulation Modeling for Increasing the Operation Efficiency of a Telecommunication Company
Selection of the Rational Variant for Construction of a Specialized Distributed Database in a Fuzzy Multicriterion Environment
ESIME Culhuacan, National Polytechnic Institute of Mexico, Mexico
Environmental Sounds Recognition
This paper describes an environmental sounds recognition system using LPC-Cepstral coefficients as feature vectors and an artificial neural network backpropagation as recognition method. LPC-Cepstral data are totally dependents of the sound-source from which are computed. This system is evaluated using a database containing files from four different sound-sources under a variety of recording conditions. The training patterns used in the network-training ad testing processes, are extracted from the Discrete Fourier transform magnitude of the LPC-Cepstral matrices. The global percentages of classification obtained in the network-testing process are 98.2% and 96.8%. Basically the idea here is to apply the techniques found in speech recognition systems to an environmental sounds recognition system.
Kharkov National University of Radio Engineering and Electronics,
14, Lenin Ave, Kharkov, 61166, Ukraine
Exploration into the Physical Factor of Meteor Detectibility
The comparative analysis of electron density models by Lebedinets and Kostylev was performed. The influence of the chosen model of the ionosphere meteor zone on the radio meteors noticeability was shown. Results of the MARS complex noticeability factor estimations were obtained. It was shown that the software developed can be used in future scientific investigations when obtaining real distributions of meteors’ speed.