Discriminating geoelectrical signals measured in seismic and aseismic areas by using Ito models

Geoelectrical signals can be considered as the end-product of complex and collective interactions among system elements. Their dynamical behavior could be different if they are measured in seismic or aseismic areas. Using the Ito equations, which represent a good macroscopic model of phenomena in which microscopic interactions are adequately averaged, we show that geoelectrical data recorded in seismic areas are well discriminated by those measured in aseismic areas. Our findings contribute to a better dynamical characterization of geoelectrical signals.     

N-Soliton-like Solution of Ito Equation

By using the extended Hirota‘s method, the N-soliton-like solution of the Ito equation is obtained. Furthermore, we also investigate the soliton-like solution interaction and find singularity.     

The optimum bandwidth of chirp signals in ultrasonic applications

A new formula for the pulse-compression ratio achievable with linear FM pulses (chirp signals) in ultrasonic applications is derived. The calculations take into account the frequently omitted effects of the transfer function of an ultrasonic transducer. For a squared-cosine type transducer spectrum, the optimum chirp signal bandwidth is 1.14 times the 6 dB bandwidth of the transducer. The pulse-compression ratio is 2.24 dB lower than in the case of an ideal broadband transducer. Measurements show a close agreement with the presented theory.     

A novel timing synchronization for CO-OFDM systems using chirp signals

A fast and efficient timing offset correction is an essential function in the coherent optical orthogonal frequency division multiplexing (CO-OFDM) system. The timing synchronization schemes for OFDM systems in wireless communications can be used for CO-OFDM systems. However, the performance of these schemes is reduced due to the chromatic dispersion. To fulfill the requirement of the CO-OFDM systems, a novel symbol timing synchronization scheme based on chirp signals has been proposed. The simulation results show that the proposed method is robust in CO-OFDM systems which is suffering from noise.     

Analysis of cross-correlations in electroencephalogram signals as an approach to proactive diagnosis of schizophrenia

We apply flicker-noise spectroscopy (FNS), a time series analysis method operating on structure functions and power spectrum estimates, to study the clinical electroencephalogram (EEG) signals recorded in children/adolescents (11 to 14 years of age) with diagnosed schizophrenia-spectrum symptoms at the National Center for Psychiatric Health (NCPH) of the Russian Academy of Medical Sciences. The EEG signals for these subjects were compared with the signals for a control sample of chronically depressed children/adolescents. The purpose of the study is to look for diagnostic signs of subjects’ susceptibility to schizophrenia in the FNS parameters for specific electrodes and cross-correlations between the signals simultaneously measured at different points on the scalp. Our analysis of EEG signals from scalp-mounted electrodes at locations F₃ and F₄, which are symmetrically positioned in the left and right frontal areas of cerebral cortex, respectively, demonstrates an essential role of frequency-phase synchronization, a phenomenon representing specific correlations between the characteristic frequencies and phases of excitations in the brain. We introduce quantitative measures of frequency-phase synchronization and systematize the values of FNS parameters for the EEG data. The comparison of our results with the medical diagnoses for 84 subjects performed at NCPH makes it possible to group the EEG signals into 4 categories corresponding to different risk levels of subjects’ susceptibility to schizophrenia. We suggest that the introduced quantitative characteristics and classification of cross-correlations may be used for the diagnosis of schizophrenia at the early stages of its development.     

Intensity analysis methods for transient signals

Conventionally, the Fourier transform is applied for sound intensity analysis of stationary signals, but this method can be applied for analyzing non-stationary transient signals. Instead of the Fourier transform analysis, instantaneous spectrum analysis methods such as the Wigner-Ville distribution and the wavelet transform are proposed. By using the mathematical example as a transient signal, advantages and disadvantages of these methods including the short-time Fourier transform are compared. From calculation results, it is considered that the STFT method is the most suitable for the accurate measurement of sound intensity levels, but the WT method is also recommended from its higher resolution of transient signals.     

Detection of B-FSK signals using schmidt trigger

Possibility to record B-FSK signals with use of stochastic resonance is studied. A Schmidt trigger is employed as bistable stochastic resonator. A digital model of the detector is proposed and quantitative results are obtained by means of simulations. Dependence of the probability of correctly detected bits on the added noise power and on the low-pass filter cutoff frequency is studied. Also the stability of the detector with respect to channel-introduced phase shifts is revealed.     

Medium effect on the characteristics of the coupled seismic and electromagnetic signals

Recently developed numerical simulation technique can simulate the coupled seismic and electromagnetic signals for a double couple point source or a finite fault planar source. Besides the source effect, the simulation results showed that both medium structure and medium property could affect the coupled seismic and electromagnetic signals. The waveform of coupled signals for a layered structure is more complicated than that for a simple uniform structure. Different from the seismic signals, the electromagnetic signals are sensitive to the medium properties such as fluid salinity and fluid viscosity. Therefore, the co-seismic electromagnetic signals may be more informative than seismic signals.     

Multichannel sampling theorem for bandpass signals in the linear canonical transform domain

The linear canonical transform (LCT) describes the effect of first-order quadratic phase optical system on a wave field. The classical multichannel sampling theorem for common bandlimited signals has been extended differently to bandlimited signals associated with LCT. However, a practical issue associated with the reconstruction of the original bandpass signal from multichannel samples in LCT domain still remains unresolved. The purpose of this paper is to introduce a practical multichannel sampling theorem for bandpass signals in LCT domain. The sampling expansion which is constructed by the ordinary convolution in the time domain can reduce the effect of spectral leakage and is easy to implement. The classical multichannel sampling theorem and the well-known sampling theorems for the LCT are shown to be special cases of it. Some potential applications of the multichannel sampling are also presented to show the advantage of the theory.     

A model for domain and domain wall NMR signals in magnetic materials

Spin echo NMR signals in magnetic materials (simple metals, alloys or intermetallic compounds) generally result from mixed contributions of distinct magnetic regions of the sample, the magnetic domains and the domain walls. The amplitude of the signal is proportional to the so-called enhancement factor which in most of the cases greatly differs in these two regions, depending upon the wall mobility, the magnetic anisotropy, etc. The experimental access to domain and domain walls is possible, in principle, by a careful control of the RF power applied to the sample. In this paper a simple superposition model is proposed which includes both contributions to the NMR signal. We calculate the amplitude of the spin echo in magnetic powder samples and compare it with experimental situations where it has been possible to separate different contributions to the signal. This has been done in some RCo₂ magnetic rare-earth intermetallic compounds by analyzing the spectral line widths and the curve of the spin echo amplitude versus the applied RF field. Despite its simplicity, the present model allows the understanding of the main features of the NMR spectra and the dependence of the echo amplitude with the RF power in these compounds.     

单向耦合洛伦兹混沌遮掩保密数字通信电路

给出了一种可高质量传送数字信号的保密通信系统,该系统利用耦合同步洛伦兹混沌电路系统进行数字信号的混沌遮掩传送.模拟实验表明,传送信息保密性好,在接收端用同步的混沌信号将信息信号检出并整形后可无失真的恢复所传送的数字信号.     

A simulation algorithm for ultrasound liver backscattered signals

In this study, we present a simulation algorithm for the backscattered ultrasound signal from liver tissue. The algorithm simulates backscattered signals from normal liver and three different liver abnormalities. The performance of the algorithm has been tested by statistically comparing the simulated signals with corresponding signals obtained from a previous in vivo study. To verify that the simulated signals can be classified correctly we have applied a classification technique based on an artificial neural network. The acoustic features extracted from the spectrum over a 2.5 MHz bandwidth are the attenuation coefficient and the change of speed of sound with frequency (dispersion). Our results show that the algorithm performs satisfactorily. Further testing of the algorithm is conducted by the use of a data acquisition and analysis system designed by the authors, where several simulated signals are stored in memory chips and classified according to their abnormalities.     

基于临界慢化现象的气候突变前兆信号的初步研究

近年来,临界慢化现象在揭示复杂动力系统是否趋于临界性灾变方面展示了重要潜力.基于临界慢化的理念,研究了气候突变的早期预警信号.针对20世纪70年代末80年代初的气候突变,对全国月平均温度资料和太平洋年代际振荡(PDO)指数进行分析,分别计算了表征临界慢化现象的方差和自相关系数.结果表明,气候发生突变前,全国月平均温度和PDO指数都存在明显的临界慢化现象,这表明临界慢化现象可能是气候突变发生前的一个早期信号.将临界慢化理论用于气候突变前兆信号的研究,对深入认识气候突变和捕捉气候突变前兆信号都具有重要的现实意义和科学价值.     

An investigation of quantum-chaotic signals generation using a fiber ring resonator and an add/drop multiplexer

We successfully generate the double security using a fiber ring resonator incorporating an add/drop device, whereas the quantum-chaotic encoding of light in a single fiber ring resonator is constructed. In the experiment, the nonlinear Kerr effects in the fiber ring resonator induced the chaotic wave form within the fiber ring resonator, which could be used to scramble or encode into the original signals. The laser input power used was 15 mW, with a fiber ring radius of 50 cm. We found that the double security can be formed, where the randomly polarized photons could be controlled by using the polarization controller and observed.     

Determination of surface reflectivity using radio signals of opportunity

Use of a bistatic reflectometry technique which employs signals of the Global Navigation Satellite System (GNSS) scattered off the Earth surface opened new opportunities in the environmental remote sensing. At the same time, similar approach can be implemented with non-GNSS signals. Recently, it was demonstrated that other signals of opportunity can be used, such as produced by communication satellites in K-, X-, S- at VHF bands and even by the Sun. This paper presents a theoretical analysis of a possible use of a noise-like broadband radio signal emitted by a point source for measuring reflectivity properties of Earth’s surface.     

The density of states for an antiferromagnetic Ising model on a triangular lattice

The Wang-Landau algorithm is an efficient Monte Carlo approach to the density of states of a statistical mechanics system. The estimation of state density would allow the computation of thermodynamic properties of the system over the whole temperature range. We apply this sampling method to study the phase transitions in a triangular Ising model. The entropy of the lattice at zero temperature as well as other thermodynamic properties is computed. The calculated thermodynamic properties are explained in the context of the magnetic phase transition.      

Towards a model for discrimination of broadband signals

The conventional model for broadband discrimination assumes that resolution is limited by peripheral internal noise that is statistically independent across channels. In this paper, we extend this model in a number of directions. In particular, we compute, compare, and discuss the effects of interchannel correlation and central noise on the sensitivity index d', for discrimination of overall level and discrimination of spectral shape.     

Limit probability distributions for an infinite-order phase transition model

The limiting probability distributions for the one-dimensional inhomogeneous spin system considered in a previous paper, which exhibits an infinite-order phase transition, are computed. It turns out that below the critical temperature or in the presence of an external magnetic field, the spins are completely polarized.     

Detection of multi-frequency weak signals with adaptive stochastic resonance system

Aiming at the poor detection rate of multi-frequency weak signals under a strong background of noise, a novel method based on adaptive stochastic resonance (SR) theory is proposed in this paper. The optimal parameters can be obtained automatically via measurement by establishing an adaptive SR system model and using the reverse location method. After passing through the adaptive SR system, the spectrum values of all eight signals greatly improve, the largest spectrum value gain increases from 12.41 to 2033 when the frequency is 0.01?Hz, which is an improvement of a factor of 162.8, and the signal-to-noise ratio (SNR) gain of the whole system is 10.3134?dB. Under the condition of different input noise intensities and signal amplitudes, the mean SNR of the system increases from –13.1136 to –2.7614?dB, which is a 78.9% increase, and the largest SNR gain is 13.4702?dB when the noise intensity D?=?1.2 and signal amplitude A?=?0.11. Compared to the single optimal spectrum value, when defining multiple optimum spectrum values as the SNR criterion, the detection sensitivity is less than 0.35 when the input noise intensity is between 0.5 and 2.5, and the sensitivity value is 6.29 times higher when D?=?2.5. The system successfully realizes the adaptive detection of twelve weak signals, and the SNR gain is 7.9743?dB, which improves the channel capacity of signal detection. The experimental results demonstrate the high efficiency and strong applicability of the system, improving the signal processing efficiency and speed of signal transmission.