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In this paper, a novel image denoising algorithm and novel input features are proposed. The algorithm is applied to phase-resolved partial discharge (PRPD) diagrams with a single dominant partial discharge (PD) source, preparing them for automatic artificial-intelligence-based classification. It was designed to mitigate several sources of distortions often observed in PRPDs obtained from fully operational hydroelectric generators. The capabilities of the denoising algorithm are the automatic removal of sparse noise and the suppression of non-dominant discharges, including those due to crosstalk. The input features are functions of PD distributions along amplitude and phase, which are calculated in a novel way to mitigate random effects inherent to PD measurements. The impact of the proposed contributions was statistically evaluated and compared to classification performance obtained using formerly published approaches. Higher recognition rates and reduced variances were obtained using the proposed methods, statistically outperforming autonomous classification techniques seen in earlier works. The values of the algorithm’s internal parameters are also validated by comparing the recognition performance obtained with different parameter combinations. All typical PD sources described in hydro-generators PD standards are considered and can be automatically detected.

A bioinspired hybrid multiobjective optimization technique that associates a general regression neural network and a cuckoo search algorithm is proposed for microwave applications. This study is focused on the simulation, design, and synthesis of frequency selective surfaces (FSSs) with triangular ring patch elements printed on fiberglass substrates (FR4). The proposed technique aims, for example, to design FSSs with specific values for the resonance frequency and bandwidth in the frequency range from 8 to 12 GHz. For validation purpose, a bandstop FSS filter, centered at 11 GHz and with a 4 GHz bandwidth, was synthesized, fabricated, and measured. Good agreement between simulated and measured results is reported. © 2015 Wiley Periodicals, Inc. Microwave Opt Technol Lett 57:2400–2405, 2015

Recent research into radio propagation and large-scale channel modeling shows that frequencies can be used above 6 GHz for the new generation of mobile communications (5G). This paper provides a detailed account of measurement campaigns that use directional horn antennas in co-polarization (V-V and H-H) and cross-polarization (V-H) in line-of-sight (LOS) and obstructed-line-of-sight situations between the transmitter and receptor; they were carried out in a corridor and computer laboratory located at the Federal University of Para (UFPA). The measurement data were used to adjust path loss prediction models of radio propagation, through the minimum mean square error (MMSE) method, for indoor environments in the frequencies of 8-11 GHz. The parameters for the models that were determined are as follows: path loss exponent, polarization exponent (co-and cross-polarization), effects of shadowing and path loss exponent for wall losses. Standard deviation and standard deviation point by point are included as statistical metrics. The approximations with regard to the large-scale path loss models for frequencies of 8-11 GHz show a convergence with the measured data, owing to the method employed for the optimization of the MMSE to determine the parameters of the model.

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In this work is presented a hybrid bioinspired optimization technique that associates a General Regression Neural Network (GRNN) with the Multiobjective Bat Algorithm (MOBA), for the design and synthesis of the Frequency Selective Surfaces (FSS), aiming its application in data communication systems by diffusion of millimeter waves, specifically, in the IEEE 802.15.3c standard. The designed device consists of planar arrangements of metallizations (patches), diamond-shaped, arranged over a RO4003 substrate. The FSS proposed in this study presents an operation with ultra-wide band characteristics, its patch designed to cover the range of 40.0 GHz at 70.0 GHz, i.e., 30.0 GHz bandwidth and 60.0 GHz resonance. The upper and lower cutoff frequencies, referring to the transmission coefficient's scattering matrix (dB), were obtained at the cutoff threshold at-10dB, to control the bandwidth of the device.

The feasible choice of a propagation model for a given wireless system depends on environment type among other factors. Thus, it is a crucial decision on radio network planning. This current proposal is a new methodology applied for LTE systems that includes: to find optimal parameters of a propagation model that minimizes Root Mean Square Error (RMSE) and maximizes Grey Relation Grade and Mean Absolute Percentage Error, (GRG-MAPE) in a city-forest environment through the use of metaheuristic optimization such as Cuckoo Search (CS). The results, quantitatively analyzed by RMSE and GRG-MAPE, show a better accuracy of optimized model in comparison with the original version and even with Stanford University Interim (SUI) model.

A three‐dimensional convex polyhedral beam‐tracing method for modeling ultrawideband indoor radio channels is presented.The model enables a fast and unambiguous generation of all propagation paths between the transmitter and the receiver over an 850‐MHz bandwidth. To validate the model, its results are compared with measurements. © 2012 Wiley Periodicals, Inc. Microwave Opt Technol Lett 54:904–909, 2012; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26670