Noise Immunity Research Articles

Optimizing the ordering of the Hadamard masks of ghost imaging suitable for the efficient face reconstruction using the max-projection method

One crucial component of ghost imaging (GI) is the encoded mask. Higher-quality reconstruction at lower sampling rates is still a major challenge for GI. Inspired by deep learning, max-projection method is proposed in the paper to reorder the Hadamard masks for its efficient and rapid reconstruction. The simulations demonstrated that max-projection ordering with only 20 face training images yielded excellent reconstruction outcomes. In noise-free simulations, at an ultralow sampling rate of 5%, the PSNR of the max-projection ordering was 1.1 dB higher than that of the cake-cutting ordering with the best performance in the reference group. In noisy simulations, at ultralow sampling rates, the retrieved images remained almost identical to their noise-free counterparts. Irrespective of the presence or absence of noise, the max-projection ordering guaranteed the highest fidelity of image reconstruction at ultralow sampling rates. The reconstruction time was reduced to mere milliseconds, thereby enabling swift visualization of dynamic phenomena. Accordingly, the max-projection ordering Hadamard matrix offers a promising solution for real-time GI due to its higher reconstruction quality, stronger noise immunity and millisecond reconstruction time.

Adaptive Space–Location-Weighting Function Method for High-Precision Density Inversion of Gravity Data

Underground 3D density variation can be obtained via the inversion of gravity data, which is a very important basis for structural division, oil and gas structure definition, and mineral resource evaluation. A depth-weighting function is usually introduced as a structural constraint in density inversion to solve the skin effect. We propose an adaptive space–location-weighting (ASW) function for gravity field data to improve the resolution of the inversion, which adds the position and depth information provided by the DEXP method to form a new weighting function. The weighting function is partitioned according to the horizontal distribution of the source and can effectively improve the resolution of field sources with different positions and different depths. The results of model tests have shown that the ASW function method can significantly improve the precision and resolution of density inversion results and has good noise immunity. The ASW method was applied to interpret the real gravity data of a mining area in Shandong, and we speculated potential mineralization based on the inversion results, which corresponded well with the logging results.

Use of a spatially distributed in-phase antenna to increase the noise immunity of signal reception

Objectives. Radio-technical information transmission systems are widely used in various sectors of our life, not only for telecommunications and associated domestic needs, but also for the functioning of various special services, such as emergency response units, which increasingly use robotic complexes in the course of their work. In the event of an emergency, robot devices can be used to get in under rubble, in concrete pipes or other municipal facilities, which typically result in a sharp deterioration of the necessary conditions for the propagation of radio waves. In this regard, the problem of ensuring reliable communication with the robotic complex becomes rather acute. The aim of the present work is to reduce the effect of multipath propagation of radio waves in the communication channel under complex interference conditions.Methods. The methods of statistical radio engineering and mathematical modeling are used according to optimal signal reception theory.Results. The presented model for a multi-element, spatially-distributed, in-phase receiving antenna of various configurations, featuring an electronically adjustable radiation pattern, is designed to ameliorate the multipath nature of signal propagation. A simulation of a multipath communication channel was carried out in the presence of one main and three reflected beams of radio wave propagation, as well as with harmonic interference at two angles of its arrival and different frequency detuning relative to the frequency of the useful signal. The probability of a bit error when receiving discrete information using the proposed antenna is estimated.Conclusions. The proposed signal processing algorithm on the receiving side can be used to partially compensate for the influence of the multipath effect. As a result, the noise immunity of information reception in comparison with reception on an omnidirectional antenna with one antenna element increases: for a bit error probability of 10−3, the energy gain ranges from 2 dB for two beams to 7–10 dB for three or four beams. In the presence of concentrated harmonic interference in the radio channel, its simultaneous spatial (by the antenna) and spectral (by the demodulator) filtering is also observed, the effectiveness of which depends on the direction of arrival and the frequency detuning of the interference, which also leads to a significant decrease in the error probability.

Multi-master event waveform stacking microseismic location method based on time-frequency transformation

Waveform stacking is frequently employed in the analysis of microseismic data due to its adaptability, effectiveness, and noise immunity. However, the low signal-to-noise ratio and inaccurate velocity model have a considerable negative impact on the waveform stacking location method's performance. A time-frequency transform-based characteristic function and the addition of a multi-master event method to waveform stacking location are presented as solutions to the aforementioned issues. In this paper, non-smooth statistical features of characteristic function are extracted and enhanced using time-frequency transform. Based on the two-pair double-difference method, multi-master events are introduced and a reference criterion for selecting the master events is proposed. Experiments with simulated and actual microseismic data show that the conversion of time-domain signals into time-frequency signals by wavelet transform can enhance the peak capacity of the signal and reduce the background noise, enhancing the imaging resolution. The introduction of multi-master events not only reduces the sensitivity of the waveform stacking method to velocity error but also improves the clustering effect of the master event method.

Noise immunity of signals with phase and amplitude-phase modulation taking into account the phase noise of the heterodyne

Noise immunity of signals with phase and amplitude-phase modulation taking into account the phase noise of the heterodyne

A METHOD OF PROTECTING INFORMATION IN CYBER-PHYSICAL SPACE

The subject of the study is the processes of ensuring the reliability and security of information in cyber-physical space. The objective is to develop recommendations for the implementation of a method of information security in cyber-physical space. The development is based on the technology of ultra-wideband signals circulating in wireless communication channels. The task is to ensure the stable and reliable operation of the airborne wireless mobile communication network, which is the main component of cyberspace and its most vulnerable link to destructive influences. Methods used: methods of analytical modelling and time-position pulse coding. The following results were obtained. It is shown that in order to ensure high quality of wireless network operation, it is necessary to expand its bandwidth, which is limited by the physical resource of the radio frequency spectrum. It is proposed to overcome this contradiction by applying the technology of ultra-wideband signals, the base of which is much larger than one. In this case, the information signal is emitted without a carrier frequency simultaneously in the entire frequency band, provided that the signal level is lower than the noise level. The method of positional-time coding is used, in which each information bit is encoded by hundreds of ultra-short chip pulses arriving in a certain sequence. In such wireless communication systems, the use of autocorrelation reception of modulated ultra-wideband signals is proposed. A comparative analysis has shown that the wireless network with the best reliability and noise immunity is the one where the time separation of the reference and information signals is applied. During the first half of the bit interval, the switch closes the transmitter output directly to the ultra-wideband signal generator, forming a reference signal. In the middle of the bit interval, the switcher switches the output to one of two possible positions depending on the signal "zero" or "one", forming the information part of the signal. Conclusions. Systems with autocorrelation reception and separate transmission of reference and information signals provide a high level of structural

Study of the Noise Immunity of the Iterative Symbol-by-Symbol Decoding Algorithm for Decoding Signal Constructions Based on OFDM Signals

Study of the Noise Immunity of the Iterative Symbol-by-Symbol Decoding Algorithm for Decoding Signal Constructions Based on OFDM Signals

Интервально-импульсная модуляция сверхширокополосных хаотических радиоимпульсов: теория и эксперимент

An approach to reduce the negative impact of multipath signal propagation (interpulse interference) in a wireless communication channel has been proposed. Pulse-interval modulation of chaotic radio pulses allows to increase the time interval between pulses without reducing the average bitrate. The possibility of using this method in ultra-wideband microwave channels with multipath propagation is demonstrated. The noise immunity of the AWGN channel has been studied. An experimental implementation of the method is described.

Autofocusing in off-axis digital Fresnel holography using S-th power weighted neighborhood correlation coefficient

Accurately determining the focus plane of the reconstructed image is crucial for obtaining high-quality reconstructed images in the process of digital hologram reconstruction. In this paper, a focusing evaluation function based on S-th power weighted neighborhood correlation coefficient (SPWNCC) is proposed to realize automatic focusing of the reconstructed image in off-axis digital Fresnel holography. The Fresnel transform method is utilized as the off-axis digital holographic reconstruction algorithm. Both the numerical simulation and optical experiment results are given to verify the validity of the proposed autofocusing method. The obtained focusing curve can maintain good unimodality and noise immunity performance over a large search range (approximately 800 mm). The proposed SPWNCC based focusing evaluation function has a certain guiding significance on the automatic focusing of off axis digital holographic reconstructed images of long distance recorded objects.

Статистическая модель высоконаправленной цифровой антенной решетки пространственно-корреляционным методом обработки сигналов

The article presents a statistical model of a digital antenna array with a spatial correlation method of signal processing. The model is obtained on the basis of the Neumann-Pearson criterion for the conditions of a stationary Gaussian distribution of the output process in spatial correlation signal processing. This model makes it possible to numerically evaluate the probabilistic characteristics of radar signal detection for various orders of nonlinear processing under the influence of natural radio interference and can be recommended for the study and optimization of the construction of the antenna array aperture with spatial correlation signal processing, providing a given spatial noise immunity of radio engineering systems.

Reflection-type surface lattice resonances in all-metal metasurfaces for refractive index sensing

Surface lattice resonance (SLR) is a pretty effective mechanism to realize ultranarrow linewidths in the spectrum. Herein, we propose and demonstrate reflection-type SLRs in all-metal metasurfaces experimentally, compared with the traditional transmission-type SLR, which can avoid the refractive index (RI) mismatch problem and are more suitable for high-efficiency RI sensing due to direct contact and strong light–matter interaction. The measured SLR linewidth is 13.5 nm influenced by the meta-atom size, which needs a compromise design to keep a balance between the narrow linewidth and noise immunity. Notably, the SLR sensitivity is determined by the lattice period along the polarization direction with regularity, which establishes an intuitive link between structures and optical responses and provides a theoretical guide for metasurface designs. Additionally, incident angle multiplexing will make the resonance wavelength red shift or blue shift in the case of orthogonal polarization. The rectangular array metasurface can realize dual SLRs with different sensing performances. Flexibly, the SLR can also be formed by the different meta-atoms and arrays. This research supports SLR multifarious applications involving not only RI sensing but also nonlinear optics, nano-lasers, etc.

Estimating Optimal Synchronization Parameters for Coherent Chaotic Communication Systems in Noisy Conditions

It is known, that coherent chaotic communication systems are more vulnerable to noise in the transmission channel than conventional communications. Among the methods of noise impact reduction, such as extended symbol length and various digital filtering algorithms, the optimization of the synchronization coefficient may appear as a very efficient and simple straightforward approach. However, finding the optimal coefficient for the synchronization of two chaotic oscillators is a challenging task due to the high sensitivity of chaos to any disturbances. In this paper, we propose an algorithm for finding the optimal synchronization parameter K_opt for a coherent chaos-based communication system affected by various noises with different signal-to-noise ratios (SNR). It is shown, that under certain conditions, optimal $K$ provides the lowest possible bit error rate (BER) during the transmission. In addition, we show that various metrics applied to the message demodulation task propose different noise immunity to the overall system. For the experimental part of the study, we simulated and physically prototyped two chaotic communication systems based on well-known Rossler and Lorenz chaotic oscillators. The microcontroller-based prototype of a chaotic communication system was developed to investigate the influence of noise in the real transmission channel. The experimental results obtained using the designed hardware testbench are in good correspondence with the theoretical propositions of the study and simulation results. The suggested evaluation metrics and optimization algorithms can be used in the design of advanced chaos-based communication systems with increased performance.

Turbine fault diagnosis of the oscillating water column wave energy converter based on multi-lead residual neural networks

Turbine fault diagnosis of the oscillating water column (OWC) wave energy converter has been a critical engineering challenge. This paper proposes a new approach for diagnosing turbine faults which is based on a correlation analysis of ensemble empirical modal decomposition (EEMDCA) and the fusion of multi-lead residual neural (MLRN) networks. The correlation coefficient between the intrinsic modal function (IMF) components and the original sample data is used to determine the number of lead branches in the MLRN structure. The numerical simulations were conducted for 14 cases (one intact and 13 faulty cases). Based on the data processed by EEMDCA, the diagnostic accuracies of MLRN, single-lead residual neural (SLRN) networks, and CNN are compared. Additionally, the noise immunity of the different methods (MLRN, SLRN, CNN, EEMDCA-MLRN, EEMDCA-SLRN and EEMDCA-CNN) is studied considering four different noise levels. Furthermore, experimental research of the OWC model in a wave flume is conducted under three wave conditions to validate the effectiveness of the proposed EEMDCA-MLRN approach for turbine fault diagnosis. Results indicate that the proposed method can provide references for real-time operation and maintenance monitoring of OWC in practical engineering.

Ice Identification with Error-Accumulation Enhanced Neural Dynamics in Optical Remote Sensing Images

Arctic sea ice plays an important role in Arctic-related research. Therefore, how to identify Arctic sea ice from remote sensing images with high quality in an unavoidable noise environment is an urgent challenge to be solved. In this paper, a constrained energy minimization (CEM) method is applied for Arctic sea ice identification, which only requires the target spectrum. Moreover, an error-accumulation enhanced neural dynamics (EAEND) model with strong noise immunity and high computing accuracy is proposed to aid with the CEM method for Arctic sea ice identification. With the theoretical analysis, the proposed EAEND model possesses a small steady-state error in noisy environments. Finally, compared with other existing models, the proposed EAEND model can not only complete sea ice identification in excellent fashion, but also has the advantages of high efficiency and noise immunity.

Identification of time-varying inertia tensor parameters of a space solar power satellite based on a robust weighted recursive algorithm under impulsive disturbance

Considering changes in the structural size and mass caused by the on-orbit assembly process in a planar space solar power satellite, this study proposes an improved robust recursive algorithm to identify the time-varying inertia tensor parameters of the system. In this algorithm, to decrease the effect of impulsive disturbance on inertial parameter identification during the on-orbit assembly and improve computational accuracy, robust weighted factor and multi-innovation theory are involved. Then, the time-varying inertia tensor parameters of this large flexible structure are identified based on the distributed measurement results of multiple attitude sensors. The simulation results indicate that the proposed algorithm improves the identification accuracy and has better robustness than the original method under the impulsive disturbance. The relative values of the average relative error caused by the impulsive disturbance under the proposed algorithm are approximately 27.8–73.0% less than those under the original method. Additionally, the results also demonstrate that the proposed algorithm has higher noise immunity than the classical recursive least-squares method in a time-varying system. When the impulsive disturbance and zero-mean Gaussian white noise are applied to the system, compared with the conventional recursive least-squares method, the proposed algorithm yields lower absolute and relative values of the average relative error by approximately 4.2% and 44.9%, respectively.

Damage detection of CFRP laminates based on Adamax-INN model for EIT

Carbon fiber reinforced polymer (CFRP) is electrically conductive, making it possible to detect structural damage of CFRP laminates with electrical impedance tomography (EIT). However, the inverse problem of EIT is severely non-linear, ill-posed, and underdetermined, thus limiting the resolution and accuracy of images reconstructed with EIT. This paper solves the inverse problem of EIT based on invertible neural networks (INN) and optimizes INN with Adamax gradient descent algorithm. Simulation and experimental results demonstrated that, compared with traditional EIT image reconstruction algorithms and radial basis function (RBF) neural network algorithm, the Adamax-INN model largely reduced the artifacts in reconstructed images, improved the damage recognition accuracy and edge clarity, and displayed good noise immunity.

Analysis of noise immunity of satellite communications under small-scale ionospheric disturbances and time-selective fading of received signals

The article develops a methodology for analyzing the noise immunity of satellite communication systems under small-scale disturbances of the ionosphere, taking into account the possibility of general and time-selective fading of received signals Differential Phase Shift Keying. The refined dependences of the intervals of time and space correlation of fading in the transionospheric radio channel on the parameters of transmitted signals and the state of the ionosphere are obtained. The analytical dependence of the probability of erroneous reception of signals with Differential Phase Shift Keying on the average signal-to-noise ratio at the receiver input, the frequency-time parameters of the signals and the characteristics of small-scale ionospheric inhomogeneities was obtained.

Effects of the Training Data Condition on Arterial Spin Labeling Parameter Estimation Using a Simulation-Based Supervised Deep Neural Network.

A simulation-based supervised deep neural network (DNN) can accurately estimate cerebral blood flow (CBF) and arterial transit time (ATT) from multidelay arterial spin labeling signals. However, the performance of deep learning depends on the characteristics of the training data set. We aimed to investigate the effects of the ground truth (GT) ranges of CBF and ATT on the performance of the DNN when training data were prepared using arterial spin labeling signal simulation. Deep neural networks were individually trained using 36 patterns of the training data sets. Simulation test data (1,000,000 points), 17 healthy volunteers, and 1 patient with moyamoya disease were included. The simulation test data were used to evaluate accuracy, precision, and noise immunity of the DNN. The best-performing DNN was determined by the normalized mean absolute error (NMAE), normalized root mean squared error (NRMSE), and normalized coefficient of variation over repeated training (CV Net ). Cerebral blood flow and ATT values and their histograms were compared between the GT and predicted values. For the in vivo data, the dependency of the predicted values on the GT ranges was visually evaluated by comparing CBF and ATT maps between the best-performing DNN and the other DNNs. Moreover, using the synthesized noisy images, noise immunity was compared between the best-performing DNN based on the simulation study and a conventional method. The simulation study showed that a network trained by the GT of CBF and ATT in the ranges of 0 to 120 mL/100 g/min and 0 to 4500 milliseconds, respectively, had the highest performance (NMAE CBF , 0.150; NRMSE CBF , 0.231; CV NET CBF , 0.028; NMAE ATT , 0.158; NRMSE ATT , 0.257; and CV NET ATT , 0.028). Although the predicted CBF and ATT varied with the GT range of the training data sets, the appropriate settings preserved the accuracy, precision, and noise immunity of the DNN. In addition, the same results were observed in in vivo studies. The GT ranges to prepare the training data affected the performance of the simulation-based supervised DNNs. The predicted CBF and ATT values depended on the GT range; inappropriate settings degraded the accuracy, whereas appropriate settings of the GT range provided accurate and precise estimates.

Frequency modulated signal standing out by stochastic resonance effect

In this paper, the phenomenon which is known as stochastic resonance is considered to the signal processing application. Signal standing out with the presence of noise is considered to be one of the basic problems of telecommunication and radioengineering. The stochastic resonance effect is shown to provide significant improvement of some characteristics of the information signal, such as power gain, and noise dispersion at the system output at a certain optimal noise level. In the present article, Minimum Shift Keying signal mixed with Gaussian white noise has been studied using stochastic resonance effect. Noise coefficient, which is one of the quantitative characteristics of noise immunity is calculated and investigated.

Lower bound on operation time of composite quantum gates robust against pulse length error

Precise control of quantum systems is a cornerstone for realizing high-quality quantum technology such as quantum computing and quantum communication. The performance of control of systems often deteriorates due to systematic errors. In one-qubit control, the pulse length error (PLE) is a typical systematic error, which is often caused by deviation of the strength of the control field. A composite quantum gate (CQG) is a method for suppressing effects of such systematic errors at the cost of a long operation time. A longer operation time implies stronger decoherence, and thus a shorter CQG is preferable from the viewpoint of noise immunity. However, it has not been clear how short CQG can be implemented. This problem can be regarded as an optimization problem under constraints: optimizing the operation time while requiring the error robustness. In this paper, we find a lower bound on operation time of all CQGs with first-order robustness against the PLE, in which effects of the error are eliminated up to its first order. The derivation of this bound is based on a geometric property of robustness against the PLE. This can be used for search after high-performance CQGs.