Gravity inversion using the frequency characteristics of the density distribution

Three-dimensional gravity inversion based on the mass property model is very popular in recent years. The time and efficiency of inversion algorithms is relative to the magnitude of the target mesh. One approach is to search over the entire solution space for a more refined result. However, the inversion will be difficult with the increased parameters in the large search space and the number of computations increases exponentially. ｜n this paper, we propose a novel approach based on the frequency characteristics of the density distribution over the mesh. The purposes of our study are to reduce the parameters of three- dimensional gravity inversion and to lighten the image quality of the inversion result. The results show that the new method can expedite the inversion processing and get a better geological interpretation than tradition methods.

Optimization in Machine Learning:a Distribution-Space Approach

We present the viewpoint that optimization problems encountered in machine learning can often be interpreted as minimizing a convex functional over a function space,but with a non-convex constraint set introduced by model parameterization.This observation allows us to repose such problems via a suitable relaxation as convex optimization problems in the space of distributions over the training parameters.We derive some simple relationships between the distribution-space problem and the original problem,e.g.,a distribution-space solution is at least as good as a solution in the original space.Moreover,we develop a numerical algorithm based on mixture distributions to perform approximate optimization directly in the distribution space.Consistency of this approximation is established and the numerical efficacy of the proposed algorithm is illustrated in simple examples.In both theory and practice,this formulation provides an alternative approach to large-scale optimization in machine learning.

Frequency and Distribution of Microsatellites in the Genome of Filamentous Fungus,Neurospora crassa

A total of 38.0 Mb of publicly available DNA sequence in Neurospora crassa was researched for mono- to hexanucleotide simple sequence repeats (SSR or microsatellite) to determine the type, size and frequency. A total of 14 788 SSRs were observed in the whole genomic DNA sequence, about one every 2.57 kb, with the criteria of SSR length >15 bp and 80% matches. The most abundant microsatellite was trinucleotide repeat, the number was 4 729, followed by hexanucleotide and mononucleotide repeats, the numbers were 2 940 and 2 489 respectively, and the least abundance was dinucleotide repeat, only 691 were found. Among the 10 082 ORFs, 4 094 SSRs were harbored in 2 373 ORF (no intron) of the organism. One thousand and fifty six ORFs harbored only one SSR. Similar with other organisms, tri- and hexanucleotide repeats were predominant in ORFs, 54.1 and 48.8% of tri- and hexanucleotide repeats were distributed in ORF region. The density of these two motifs was overpresented in coding regions, because ORF region and coding region constitutes only 46 and 38.3% of genomic sequence, respectively. Upstream and downstream 300 bp of regulatory regions were high density regions of SSRs, particularly density of pentanucleotide SSR in upstream region was as high as five times of average density in genomic DNA, density of di- and tetranucleotide SSR was also more than two times of average density. The density of penta-, tetra-, di- and mononucleotide SSRs was relatively higher than average density. There were 47 SSRs in mitochondria 64 840 bp DNA sequence, their distribution is similar with genomic DNA sequence. These results suggested that SSRs were clustered in regulatory regions of genomic DNA.

Adaptive Time Frequency Distribution Based on Linear Chirp Modulated Gaussian Functions

We propose a method that uses linear chirp modulated Gaussian functions as the elementary functions, by adaptively adjusting variances, time frequency centers and sweep rates, to decompose signals. By taking WVD, an improved adaptive time frequency distribution is developed, which is non negative, free of cross term interference, and of better time frequency resolution. The paper presents an effective numerical algorithm to estimate the optimal parameters of the basis. Simulations indicate that the proposed approach is effective in analyzing signal's time frequency behavior.

Carrier frequency disturbance distributions on GPS during equatorial ionospheric scintillation

In the equatorial region,deep amplitude fading in global positioning system(GPS)signals frequently occurs during the strong ionospheric scintillation,it can lead to the loss of lock in GPS carrier tracking loops,and result in increased positioning error and even navigation interruption.The relationships between amplitude scintillation indices and detrended carrier frequency are investigated,based on GPS L1 C/A signals during the last peak of the solar cycle at the low latitude site of São Josédos Campos,Brazil(23.2S,45.9W)from 2013 to 2015.Corresponding mathematic model of the probability distribution function is built for the first time to provide statistical analysis on the above relationships.The results show that the standard carrier frequencies reveal an almost linear relation with the amplitude scintillation indices.Moreover,the frequency widths of detrended frequency are proportional to levels of amplitude scintillation when the value of the peak probability is lower than the corresponding boundary.A conclusion can be drawn that different levels of amplitude scintillation will influence the fluctuation of the carrier frequency.The analysis will provide useful guidance to set the receiver’s bandwidth with respect to the different scintillation levels and design the advanced tracking algorithms to improve the robustness and precision of the GPS receiver.

A VERIFICATION ON DIVISION OF HYDROCLIMATIC AREA IN CHINA SEAS USING DIGITAL CHARACTERISTIC OF FREQUENCY DISTRIBUTION

oceanographic data files on the China Seas prepared by the National Marine Data and Information Service, SOA, China and the '30-year (1953-1982) Reports of Sea Surface Monthly Mean Temperature in the East China Sea by the Meteorological Agency, Japan,' were used to calculate the digital characteristics of frequency distribution of sea and air temperature in 153 areas in the China Seas. Principal factor analysis and fuzzy cluster ISODATA were used to divide the China hydroclimatic area into three climatic zones including ten climatic regions. It is concluded that the characteristic values derived by this method may completely show the characteristics of frequency distribution of sea and air temperature in the studied area and the final division of hydroclimatic area is fully coincident with the author's former result [2].

The Effects of Mutual Coupling and Transformer Connection Type on Frequency Response of Unbalanced Three Phase Electrical Distribution System

In this paper, a novel harmonic modeling technique by utilizing the concept of multi-terminal components is presented and applied to frequency scan analysis in multiphase distribution system. The proposed modeling technique is based on gathering the same phase busses and elements as a separate group (phase grouping technique, PGT) and uses multi-terminal components to model three-phase distribution system. Using multi- terminal component and PGT, distribution system elements, particularly, lines and transformers can effectively be modeled even in harmonic domain. The proposed modeling technique is applied to a test system for frequency scan analysis in order to show the frequency response of the test system in single and three-phase conditions. Consequently, the effects of mutual coupling and transformer connection types on three-phase frequency scan responses are analyzed for symmetrical and asymmetrical line configurations.

Low Frequency Oscillations of the Heat Distribution in the Global Upper Ocean Layers

The heat distributions in the upper layers of the ocean have been studied and some important low frequency oscillations （LFOs） are already found and quantified by using various characteristic factors. In this paper, the ‘heat center＇ of a sea area is defined with a simple method. Then the temperature data set of the upper layer of the global ocean （from surface down to 400 m, 1955-2003） is analyzed to detect the possible LFOs. Not only some zonal LFOs, which were reported early, but also some strong LFOs of the vertical and meridional heat distribution, which might imply some physical sense, are detected. It should be noted that the similar vertical oscillation pattern can be found in the Pacific Ocean, Atlantic Ocean and Indian Ocean. Results from some preliminary studies show that the vertical LFO might be caused by the solar irradiance anomalies. This study may help reveal some unknown dynamical processes in the global oceans and may also benefit other related studies.

Dependence of Switching Current Distribution of a Current-Biased Josephson Junction on Microwave Frequency

We investigate the distribution of the switching current of a current-biased Josephson junction （CBJJ） and its dependence on the microwave frequency using two theoretical methods, one of which is the quantum trajectory method and the other is the master equation method. Both the methods show that the distribution of the switching current of CBJJ will exhibit double peaks in a certain range of microwave frequency if proper microwave power is given, and the gap between the two peaks will increase with the microwave frequency. The obtained results can be used to identify the energy difference of the ground and first excited states in a Josephson junction for any bias current.

THE CHARACTERISTICS OF THUNDERSTORM FREQUENCY VARIATION AND THEIR POSSIBLE RELATION WITH THE ADJUSTMENT OF CROP DISTRIBUTION IN THE LEIZHOU PENINSULA

In order to research possible influences of the adjustment of plant distribution on the development frequency of thunderstorms over the Leizhou Peninsula, mathematic statistic methods, including correlation analyses, 11 kinds of fitting models and all-variable regression methods, were used for analyses and research. The results show that the average trend of the number of annual thunderstorm days is descending obviously, and there are thunderstorms in all seasons, in which warm post-midday thunderstorms have taken up the most part, and high frequency is found from May to September, and the starting and ending dates of thunderstorms have a great annual discrepancy. The vegetation structure has been improved along with the reduction of rice fields and the area increment of sugarcane and fruits planting, which results in the decrease of the number of thunderstorm days; the change in the characteristics of winter spare fields, which is caused by the planting of vegetables, limits the formation of thunderstorms in early winter and late spring. Meanwhile, the area adjustment of peanut planting has little influence on the variation of thunderstorm days. The adjustment of principal crop distribution, such as rice, sugarcane, fruits and vegetables, may have obvious influence on the formation of thunderstorms, and sugarcane has the largest effect, followed in turn by rice, vegetables and fruits, and the adjustment of crop distribution has little influence on the starting and ending dates of thunderstorms.

LOCALIZED RADON-WIGNER TRANSFORM AND GENERALIZED-MARGINAL TIME-FREQUENCY DISTRIBUTIONS

This paper introduces the localized Radon transform (LRT) into time-frequency distributions and presents the localized Radon-Wigner transform (LRWT). The definition of LRWT and a fast algorithm is derived, the properties of LRWT and its relationship with Radon-Wigner transform, Wigner distribution (WD), ambiguity function (AF), and generalized-marginal time-frequency distributions are analyzed.

A NEW QUADRATIC TIME-FREQUENCY DISTRIBUTIONAND A COMPARATIVE STUDY OF SEVERAL POPULARQUADRATIC TIME-FREQUENCY DISTRIBUTIONS

A new quadratic time-frequency distribution (TFD) with a compound kernel is proposed and a comparative study of several popular quadratic TFD is carried out. It is shown that the new TFD with compound kernel has stronger ability than the exponential distribution (ED) and the cone-shaped kernel distribution (CKD) in reducing cross terms, meanwhile almost not decreasing the time-frequency resolution of ED or CKD.

ESMD Method for Frequency Distribution of Tank Surface Temperature under Wind Effect

Due to the poor understanding of the small-scale processes at the air-water interface, some lab experiments are done in a water tank by infrared techniques. With the help of ESMD method, the stochastic temperature sequences extracted from the infrared photographs are decomposed into several empirical modes of general periodic forms. The corresponding analyses on the modes reveal that, within certain limits, both spatial and temporal frequencies increase along the wind speed. As for the amplitudes, the existence of wind may result in fold increasing of their values. In addition, when the wind speed is added from 4 m/s to 5 m/s, both frequency and amplitude of the surface temperature decrease and it implies an enhanced mixing and a weakened temperature gradient under the force of wind blowing.

TVAR Time-frequency Analysis for Non-stationary Vibration Signals of Spacecraft

Predicting the time-varying auto-spectral density of a spacecraft in high-altitude orbits requires an accurate model for the non-stationary random vibration signals with densely spaced modal frequency. The traditional time-varying algorithm limits prediction accuracy, thus affecting a number of operational decisions. To solve this problem, a time-varying auto regressive （TVAR） model based on the process neural network （PNN） and the empirical mode decomposition （EMD） is proposed. The time-varying system is tracked on-line by establishing a time-varying parameter model, and then the relevant parameter spectrum is obtained. Firstly, the EMD method is utilized to decompose the signal into several intrinsic mode functions （IMFs）. Then for each IMF, the PNN is established and the time-varying auto-spectral density is obtained. Finally, the time-frequency distribution of the signals can be reconstructed by linear superposition. The simulation and the analytical results from an example demonstrate that this approach possesses simplicity, effectiveness, and feasibility, as well as higher frequency resolution.

Adaptive Time-Frequency Distribution Based on Time-Varying Autoregressive and Its Application to Machine Fault Diagnosis

The time-varying autoregressive （TVAR） modeling of a non-stationary signal is studied. In the proposed method, time-varying parametric identification of a non-stationary signal can be translated into a linear time-invariant problem by introducing a set of basic functions. Then, the parameters are estimated by using a recursive least square algorithm with a forgetting factor and an adaptive time-frequency distribution is achieved. The simulation results show that the proposed approach is superior to the short-time Fourier transform and Wigner distribution. And finally, the proposed method is applied to the fault diagnosis of a bearing , and the experiment result shows that the proposed method is effective in feature extraction.

High-Precision Doppler Frequency Estimation Based Positioning Using OTFS Modulations by Red and Blue Frequency Shift Discriminator

Orthogonal Time Frequency and Space(OTFS) modulation is expected to provide high-speed and ultra-reliable communications for emerging mobile applications, including low-orbit satellite communications. Using the Doppler frequency for positioning is a promising research direction on communication and navigation integration. To tackle the high Doppler frequency and low signal-to-noise ratio(SNR) in satellite communication, this paper proposes a Red and Blue Frequency Shift Discriminator(RBFSD) based on the pseudo-noise(PN) sequence.The paper derives that the cross-correlation function on the Doppler domain exhibits the characteristic of a Sinc function. Therefore, it applies modulation onto the Delay-Doppler domain using PN sequence and adjusts Doppler frequency estimation by red-shifting or blue-shifting. Simulation results show that the performance of Doppler frequency estimation is close to the Cramér-Rao Lower Bound when the SNR is greater than -15dB. The proposed algorithm is about 1/D times less complex than the existing PN pilot sequence algorithm, where D is the resolution of the fractional Doppler.

Distributed antenna wireless communication system coverage design and field trial over higher frequency band

This paper aims to examine the architecture design of a distributed antenna based Gbps wireless communication system using the high frequency band.In order to analyze the feasibility of the higher frequency band applications,the cumulative distribution of simulated user throughput in a cellular is investigated firstly.It shows that capacity improvement can be obtained using higher operating frequency band,especially in hotspot scenarios.Secondly,the architecture of the distributed antenna system(DAS) is introduced to overcome the disadvantages of weak coverage and rank deficient for the traditional multiple-input multiple-output(MIMO) systems using higher frequency bands in line-of-sight(LOS)environments.In addition,a software-defined-radio(SDR) based Gbps wireless transmission system with scalable hardware architecture is designed and implemented.Finally,a demo of outdoor DAS coverage for high data throughput application is given.Field trials show that 1 Gbps data rate and a large coverage in outdoor environments can be achieved over 6.05 GHz.It is proved that the Gbps DAS system at a higher frequency band can be a successful model for future wireless broadband coverage in hotspot scenarios.

Analysis of temporal and spatial distribution characteristics of ammonium chloride smoke particles in confined spaces

In response to the demand for short-range detection of anti-smoke environment interference by laser fuzes,this study proposes a smoke environment simulation of non-uniform continuous point source diffusion and investigates an experimental laboratory smoke environment using an ammonium chloride smoke agent.The particle size distribution,composition,and mass flow distribution of the smoke were studied.Based on a discrete phase model and a kεturbulence model,a numerical simulation was developed to model the smoke generation and diffusion processes of the smoke agent in a confined space.The temporal and spatial distribution characteristics of the smoke mass concentration,velocity,and temperature in the space after smoke generation were analyzed,and the motion law governing the smoke diffusion throughout the entire space was summarized.Combined with the experimental verification of the smoke environment laboratory,the results showed that the smoke plume changed from fan-shaped to umbrella-shaped during smoke generation,and then continued to spread around.Meanwhile,the mass concentration of smoke in the space decreased from the middle outward;the changes in temperature and velocity were small and stable.In the diffusion stage(after 900 s),the mass concentration of smoke above 0.8 m was relatively uniform across an area of smoke that was 12 m thick.The concentration decreased over time,following a consistent decreasing trend,and the attenuation was negligible in a very short time.Therefore,this system was suitable for conducting experimental research on laser fuzes in a smoke environment.Owing to the stability of the equipment and facilities,the setup could reproduce the same experimental smoke environment by artificially controlling the smoke emission of the smoke agent.Overall,this work provides a theoretical reference for subsequent research efforts regarding the construction of uniform smoke environments and evaluating laser transmission characteristics in smoky environments.

Boosting Adversarial Training with Learnable Distribution

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural networks.Adversarial training is one of the most potent methods to defend against adversarial attacks.However,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial training.This paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture model.The distribution centroid is built to classify samples and constrain the distribution of the sample features.The natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the model.The proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial training.This algorithm gradually increases the accuracy and robustness of the model by scaling perturbation.Finally,the proposed method outputs the predicted labels and the distance between the sample and the distribution centroid.The distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model defense.The effectiveness of the proposed method is demonstrated through comprehensive experiments.

Two-dimensional distributed strain sensing with an Archimedean spiral arrangement in optical frequency domain reflectometry

We demonstrate a distributed two-dimensional(2D)strain-sensing system in optical frequency domain reflectometry(OFDR)with an Archimedean spiral arrangement of the sensing fiber.The Archimedean spiral describes a simple relationship between the radial radius and polar angle,such that each circle(the polar angle from0 to 2π)can sense the 2D strain in all directions.The strain between two adjacent circles can also be easily obtained because an Archimedean spiral facilitates sensing of every angle covering the full 2D range.Based on the mathematical relation of Archimedean spirals,we deduce the relationship between the one-dimensional position of the sensing fiber and 2D distribution in polar coordinates.The results of the experiment show that an Archimedean spiral arrangement system can achieve 2D strain sensing with different strain load angles.