摘要：
This paper implements a deep learning-based modulation pattern recognition algorithm for communication signals using a convolutional neural network architecture as a modulation recognizer. In this paper, a multiple-parallel complex convolutional neural network architecture is proposed to meet the demand of complex baseband processing of all-digital communication signals. The architecture learns the structured features of the real and imaginary parts of the baseband signal through parallel branches and fuses them at the output according to certain rules to obtain the final output, which realizes the fitting process to the complex numerical mapping. By comparing and analyzing several commonly used time-frequency analysis methods, a time-frequency analysis method that can well highlight the differences between different signal modulation patterns is selected to convert the time-frequency map into a digital image that can be processed by a deep network. In order to fully extract the spatial and temporal characteristics of the signal, the CLP algorithm of the CNN network and LSTM network in parallel is proposed. The CNN network and LSTM network are used to extract the spatial features and temporal features of the signal, respectively, and the fusion of the two features as well as the classification is performed. Finally, the optimal model and parameters are obtained through the design of the modulation recognizer based on the convolutional neural network and the performance analysis of the convolutional neural network model. The simulation experimental results show that the improved convolutional neural network can produce certain performance gains in radio signal modulation style recognition. This promotes the application of machine learning algorithms in the field of radio signal modulation pattern recognition.
摘要：
We report the evolution of crystal structural, magnetic, and electrical transport properties in the iridates Eu2Ir2−xRuxO7 (x = 0.0, 0.1, 0.3, and 0.5). Powder X-ray diffraction measurement indicates the prepared polycrystalline samples retain the cubic pyrochlore-type structure. The evolution of magnetism has been studied using dc magnetic susceptibilities. Although the magnetic irreversibility temperature changes marginally, the magnetic moment increases with progressive Ru doping. A distinct metal-insulator transition is observed for Eu2Ir2−xRuxO7 series. The nature of electronic conduction in the low temperature insulating state has been found to follow a power law behavior. Interestingly, we found the resistivity increases with Ru doping in Eu2Ir2−xRuxO7. The results may be ascribed to increased electronic correlation and Ir/Ru substitutional disorder, which interrupt direct Ir–Ir hopping in the samples.
通讯机构：
[Zhao-Yu Sun] S;School of Electrical and Electronic Engineering, Wuhan Polytechnic University, Wuhan, China
关键词：
The European Physical Journal B;Condensed Matter;Complex Systems;journal;EPJ
摘要：
Multipartite nonlocality, a measure of multipartite quantum correlations, is used to characterize topological quantum phase transitions (QPTs) in an infinite-size spin-1/2 two-leg Kitaev ladder model. First of all, the nonlocality measure
$${\mathcal {S}}$$
is singular at the critical points, thus these topological QPTs are accompanied by dramatic changes of multipartite quantum correlations. The influence of the inter-chain coupling upon multipartite nonlocality is also investigated. Furthermore, we carry out scaling analysis and find that the logarithm measure scales linearly as
$$\log _2{\mathcal {S}}_n \sim {\mathcal {K}} n +b$$
, with n the length of the concerned subchain. It is clear that the slope
$${\mathcal {K}}$$
plays a central role in the large-n behavior of the nonlocality in the ladder. Especially, as n increases, we find the finite-size slope
$${\mathcal {K}}_n$$
converges slowly in the
$$\varDelta _{x,y}$$
phases which present non-local string orders, and quite rapidly in the
$$\varDelta _0$$
phase which does not present any string order. We figure out a clear picture to explain these different behaviors.
关键词：
Photoelectric Sensor;RFID Tag;Ant Colony Algorithm;Network Life Cycle;Network Load
摘要：
In this study, RFID technology and wireless photoelectric sensor (WOSN) technology were combined in the acquisition of traffic information. RFID tag and photoelectric sensor were used as a node to build a traffic information collection network. To improve the life cycle and load performance of the network, and achieve the optimal distribution among nodes, the ant colony optimization (ACO) algorithm was taken as the research object, and the network node distribution routing algorithm of multiple RFID tags-photoelectric sensor nodes was designed. The improved ACO based on energy and distance was selected for self-organizing distribution, so that the nodes distributed locally could be regarded as a whole. Then, each local head node transmitted information based on the route generated by the improved ACO, so that the traffic information obtained by each head node was sent to the aggregation node at the lowest cost. In the experiment, the multi RFID tag-photoelectric sensor node distribution based on the improved ACO can extend the network life cycle, and achieve a balanced network load.
关键词：
Logical stochastic resonance;Logical vibrational resonance;Bistable system;Switching time
摘要：
Various external driving forces can induce logical stochastic or vibrational resonance, such as noise, harmonics, and the combination of noise and harmonics. In engineering, using harmonics as driving force is more conducive to the control of logic operations, while a wider optimal parameter region and a shorter switching time are expected in practice to improve the robustness and response speed of system. Here, we report the logical vibrational resonance in a two-well potential system subjected to biharmonics. Our results show that the variable frequency (VF) (one harmonic) could broaden the optimal parameter region when an appropriate weak long-period signal is chosen as the fundamental frequency (FF) (the other harmonic). An intuitive interpretation for LVR is given by means of bifurcation and potential well diagrams. In addition, according to dynamic potential wells varying with input signal, four different kinds of switching modes are presented, and the switching time presents differences for different switching modes. There may be a trade-off between fast response and the robustness of system. Noise obviously affects the optimal parameter region of VF and the switching time. Finally, some results are further verified by circuit simulation. (c) 2020 Elsevier Ltd. All rights reserved.
摘要：
Variation-based methods with different priors have been proven their ability in preserving edges for image restoration. Blind image decomposition is an inverse problem that is much harder to be solved than non-blind image decomposition from noisy images, commonly producing staircase effects in flat regions and smoothing fine structures. In this paper, we have tried to use spatially adaptive sparse representation (SASR) prior to restore a clean result from a blurred and noised image. In order to fastly and efficiently solve the SASR model, the alternating direction method of multipliers (ADMM) is firstly exploited to separate it into two subproblems. Then the final solution is alternatively optimized with the employment of fast Fourier transformation (FFT) and generalized soft-threshold formula. The experiments on both synthesized images and practical polluted images show that the proposed algorithm is effectiveness in quantitation and qualification, and is even better than state-of-the-arts.
关键词：
Magnetic nanoparticles;Petroleum industry;Magnetic separation;Reservoir sensing and imaging;Oil recovery
摘要：
Due to the exclusive size effect, magnetic nanoparticles (MNPs) exhibit unique chemical, mechanical and considerably different magnetic properties compared with conventional micro and macro materials. Therefore, MNPs are of great significance and interest in biology, medicine and engineering. Recently, MNPs are also found to show great potential in petroleum industry applications, such as targeted adsorption, remote detection, directional transport and local heating. For these specific applications, the dispersity and stability of the MNPs in suspension are of great importance. Although some works have overviewed the use of nanotechnology for oil production, there is no review focusing on the application of MNPs in petroleum industry to date. Thus, recent progress and future developments in this field require for a work to summarize. This review provides an overview on the applications of the MNPs in petroleum industry, including drilling and completion improvement, magnetic separation, reservoir sensing and imaging, enhanced oil recovery, heavy oil recovery, flow assurance and conformance control. The physiochemical properties of MNPs, such as size, surface and magnetic properties, are also introduced. Finally, the main challenges and opportunities regarding the application of the MNPs in this research field are discussed.
关键词：
Logical stochastic resonance;Logical vibrational resonance;Set-Reset latch;Triple-well potential system
摘要：
We demonstrate additive driving force can induce logic and Set-Reset latch operation in a triple-well potential system and find the optimal parameter region with contour maps. The logic input signal plays the role of system bias. To be specific, the external driving force makes the system jump from high potential well to low potential well without jumping back, and thus can induce correct logic output. The problem that the optimal parameter region is too narrow can be solved in two ways: one is to increase the amplitude of the logic input signal, and the other is to introduce of logical vibration resonance. In addition, the logic input itself can be directly acted as the driving force to make the system in the correct potential well, that is, to achieve the correct logic and Set-Reset latch operation without other external driving force.
摘要：
It was demonstrated recently that there are optimal windows of noise intensity or frequency and amplitude of the periodic driving force, which let a bistable system operate reliably as logic gates. These phenomena are called logical stochastic resonance (LSR). Given that the driving force is not always perfect regular, there may be phase disturbance in driving force; therefore, the Wiener process is used here to model phase disturbance of driving force, and then the effects of phase disturbance on reliability and agility of logic gates are explored in detail. Comparing with the periodic force, the aperiodic force with appropriate intensity phase disturbance can drive a bistable system to yield phenomena similar to LSR in a wider reliable region and can reduce mean switching time to obtain a faster response of logic devices to the input signal. On the other hand, depending on the amplitude and average angular frequency, moderate-intensity phase disturbance may also reduce success probability and increase mean switching time and thus lead to the instability and the slower response of logic devices.
摘要：
Permeability estimation plays an important role in reservoir evaluation and hydrocarbon development, etc. Traditional physical model-based methods have problems with being time consuming and high cost. The applications of machine learning are currently becoming more and more extensive, however, there are still several limitations to previous machine learning-based permeability estimation methods, such as a limited number of samples, a requirement of prior knowledge, and some parameters needing to be calculated indirectly. In this paper, a hybrid reservoir permeability prediction approach, which is based on a certain scale of permeability dataset, embedded feature selection (EFS) and a light gradient boosting machine (LightGBM), is proposed. First, EFS is used to select features from the raw dataset. Then a LightGBM is adopted to predict the permeability. The influence of feature selection threshold, the base learners' number and dataset size on prediction results is also investigated. In addition, different feature selections and prediction models are compared. The proposed hybrid approach is also verified on other datasets. The experimental results show that the proposed approach can effectively predict the reservoir permeability based on limited direct logging data.
摘要：
Lipkin-Meshkov-Glick (LMG) models describe a set of N qubits which are located at the corners of an N-dimensional simplex and embedded in an external magnetic field. Because of its high coordinate number, quantum correlations in the models are quite nontrivial. For instance, in the large- N limit, two-site entanglement concurrence vanishes for any magnetic field. Multisite global entanglement and generalized global entanglement also tend to vanish in some quantum regions. We characterize the quantum correlations in the LMG model with multipartite nonlocality. In LMG models with anisotropy in the x−y plane, for any fixed magnetic field, the ground-state nonlocality (denoted by S) is found to scale as log10S∼aN+b, with a and b the fitting parameters. For LMG models which are isotropic in the x−y plane, nevertheless, the nonlocality for each Dicke state scales as log10S∼a1N+b, with b>0. Signals for the quantum phase transitions of the models will also be discussed. These results indicate that multipartite nonlocality captures some key ingredient of the ground-state quantum correlations in the models. In addition to the ground states, we also study multipartite nonlocality in the LMG models at finite temperatures. In the anisotropic models, the thermal stability of the nonlocality at low temperatures is determined by the energy gap. For the isotropic models, nevertheless, as the temperature increases, the nonlocality presents a sharp valley which is followed by a round peak. The behavior is far beyond the above-mentioned “thermal stability vs energy gap” picture. The underlying mechanics is the “contribution inversion” of low-lying energy states in the thermal-state nonlocality S(ρ̂T); that is, in a low-temperature region, the first-excited state “defeats” the ground state and plays a dominant role in thermal-state nonlocality.
关键词：
Microbolometer;Bias optimization;Focal plane array;Signal-to-noise ratio
摘要：
To increase the output signal-to-noise ratio of microbolometric focal plane array, the microbolometric bias optimization is crucial. The bias influence on the microbolometric responsivity is theoretically analyzed and numerically calculated, and the microbolometric responsivity can be optimized according to these theoretical analysis and calculated results. Some kinds of microbolometric noises are also theoretically discussed, from which the microbolometric noise can be theoretically derived to be related to the microbolometric bias parameter through numerical calculation. The bias optimization for microbolometric focal plane array can be obtained through the integrative effect of the microbolometric responsivity and current noise. These analysis and numerical calculation for the microbolometric bias optimization are theoretically strict and algorithmically reasonable, which has been experimentally verified in our laboratory. The bias parameter optimization method in this paper has guidable significance for high signal-to-noise ratio microbolometric focal plane array to detect low infrared radiation target.
作者：
Fang, Chao;Zhang, Juanjuan;Chen, Xiqu;Weng, George J.*
期刊：
Nanomaterials,2020年10(6) ISSN：2079-4991
通讯作者：
Weng, George J.
作者机构：
[Fang, Chao; Chen, Xiqu] Wuhan Polytech Univ, Dept Elect & Elect Engn, Wuhan 430023, Peoples R China.;[Zhang, Juanjuan] Lanzhou Univ, Minist Educ China, Key Lab Mech Environm & Disaster Western China, Lanzhou 730000, Peoples R China.;[Zhang, Juanjuan] Lanzhou Univ, Coll Civil Engn & Mech, Dept Mech & Engn Sci, Lanzhou 730000, Peoples R China.;[Weng, George J.] Rutgers State Univ, Dept Mech & Aerosp Engn, New Brunswick, NJ 08903 USA.
通讯机构：
[Weng, George J.] R;Rutgers State Univ, Dept Mech & Aerosp Engn, New Brunswick, NJ 08903 USA.
关键词：
Monte Carlo simulations;electrical conductivity;graphene polymer nanocomposites
摘要：
Electrical conductivity is one of several outstanding features of graphene-polymer nanocomposites, but calculations of this property require the intricate features of the underlying conduction processes to be accounted for. To this end, a novel Monte Carlo method was developed. We first established a randomly distributed graphene nanoplatelet (GNP) network. Then, based on the tunneling effect, the contact conductance between the GNPs was calculated. Coated surfaces (CSs) were next set up to calculate the current flow from the GNPs to the polymer. Using the equipotential approximation, the potentials of the GNPs and CSs met Kirchhoff's current law, and, based on Laplace equation, the potential of the CSs was obtained from the potential of the GNP by the walk-on-spheres (WoS) method. As such, the potentials of all GNPs were obtained, and the electrical conductivity of the GNP polymer composites was calculated. The barrier heights, polymer conductivity, diameter and thickness of the GNP determining the electrical conductivity of composites were studied in this model. The calculated conductivity and percolation threshold were shown to agree with experimental data.
摘要：
Some noisy nonlinear system can be used to realize reliable logic operation based on the mechanism of logical stochastic resonance (LSR). However, most previous studies focus mainly on Gaussian noise-driven system. In this paper, the effect of non-Gaussian sine-Wiener (SW) bounded noise on the reliability and agility of logic system is explored based on a SW noise-driven two-potential well system. The success probability P of obtaining desired reliable logic operation increases quickly, reaches a maximum of P = 1, and then decrease with the increase of noise intensity or self-correlation time of SW noise, showing the occurrence of LSR. Furthermore, with increasing self-correlation time of SW noise, the optimal window of noise intensity moves toward left and becomes narrower. For too long self-correlation time, SW noise cannot induce LSR. The optimal parameter regions of SW noise are strongly dependent on bias b of logic system. Therefore, adjusting bias b can realize the control of noise and let noise produce constructive effect. Additionally, the agility of reliable logic gate can be improved by properly increasing noise intensity. Taken together, the results presented here are beneficial to the design of new logic devices based on LSR. (C) 2019 Elsevier Ltd. All rights reserved.
