Intensive development of modern wirelesscommunications such as the systems of wireless access toInternet and local network systems operating in indoorenvironment provoked interest in study the features andmodels of wireless communication channels. The presence ofthe walls; partitions; furniture; radio electronic equipment;people and other objects inside the building create intricateenvironment for the propagation of radio waves. The maineffects observed in the propagation of radio waves inside thepremises are multipath due to multiple reflections of radiowaves from walls and other objects; diffraction on thenumerous sharp edges of objects located inside the room; andscattering of radio waves. These effects create intricateinterference structure of the electromagnetic field; whichvaries greatly when people and other objects move.UWB communication systems are characterized by highdata rates; low cost; multipath immunity; and large toleranceto interfering legacy systems. In recent years; UWBtechnologies have been rapidly developingPerformance of all known communication systems usingenergy-based receivers largely depends on the transmittedsignal energy; i.e. decision making is carried out at thematched filter output by estimation of signal energy. Due tothis principal peculiarity; deep fading attenuating of receivedsignal magnitude provokes considerable decreasing of signalenergy and; as consequence; performance provided bycommon energy-based decision making strategy is worsen.Suggested strategy exploiting for building novel UWBcommunication systems is based on the features of higher-order spectra. Performance provided by exploitingsuggested bispectrum-organized triplet-signals andbispectrum-based decision making for detection anddiscrimination the triplets depends on given phase couplingrelationships contained in triplet-signals. Because of this;despite considerable attenuating of triplet-signal amplitude;phase coupling information remains to be preserved for truetriplet-signals discrimination and correct decision making fordata passed through the fading wireless channel

The subject of the article is to analyze the effectiveness of a new method for detecting heterogeneities in a digital image by estimating the bimagnitude maximum of the pixel intensities. The aim is to evaluate the effectiveness of the new method of detecting heterogeneities in the image using the maximum of the bimagnitude compared to the known method based on the estimation of the local root mean square deviation (LRMSD) of pixel intensity values. The objectives of the paper are the following: to formalize the procedure for computing the bimagnitude maximum of the pixels in the local segment; create a test image with different contrast values on the borders; to develop a mathematical model for calculating in the Matlab system the efficiency of detecting heterogeneities in the image in the presence of additive Gaussian noise with different values of noise RMS; provide for analysis and comparison of the graphs the receiver operating characteristic (ROC) contained the number of correctly classified non-homogeneous areas versus the number of incorrectly classified areas. The used methods are the following: bispectral data analysis method; methods of probability theory and mathematical statistics; methods of digital image processing. The following results were obtained. A boundary map for the test image without distortion and the presence of additive Gaussian noise with a variance equal to 0.2 is constructed for two types of detectors: the first one is based on the maximum amplitude and the second one is based on the estimation of the local RMS. The results of computer simulations show that both detectors fine-tune the boundary for the images in the absence of noise. But in the presence of additive noise, the detector based on the biamplitude maximum provides a significant advantage. Graphs of the dependence of the number of correctly classified inhomogeneous sections on the number of incorrectly classified areas for the proposed and known reference detection methods are represented. The area under the curve (AUC) values that characterize the efficiency of detecting heterogeneities in the image are calculated. The scientific novelty of the obtained results is the following: a new approach of detecting inhomogeneities in the image is proposed with the help of a new informative feature estimated in the form of the local biamplitude maximum. To analyze the effectiveness of the proposed method, a test image was formed with different border contrast values. Using the proposed technique and the known method, boundary maps were constructed for the test image without distortion and in the presence of additive Gaussian noise. To evaluate the effectiveness of two methods, the graphs were plotted against the number of correctly classified inhomogeneous sites by the number of incorrectly classified (ROC) for both proposed and known detection methods. A detector based on the local RMS value is more effective at small Gaussian noise variance values, but as the noise variance increases, detector based on the biamplitude maximum estimation is more effective. The calculated AUC values for studied methods based on local RMS estimation and maximum biamplitude estimation are equal to 0. 678 and 0. 8468, respectively. Even though the proposed method loses efficiency, the bispectrum-based method is more effective at large values of noise variance, in particular, when the noise RMS is 0.6, AUC = 0.8748.

Предложен метод восстановления сигналов неизвестной формы по биспектральной плотности. Изложен новый подход, основанный на использовании гладких функций косинус и синус вместо традиционно используемой в фазовых измерениях разрывной функции арктангенс аргумента биспектра. С помощью моделирования оценена эффективность предложенного метода восстановления сигналов с разрывами первого рода при различных интервалах дискретизации.

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