In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to m...In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.展开更多
Photochromic materials with multicolor upconversion reversible modulations are attractive in optical switching devices.Herein,the fabricated YNbO_(4):Er^(3+)/Tm^(3+)/Yb^(3+) materials exhibit excellent photochromism a...Photochromic materials with multicolor upconversion reversible modulations are attractive in optical switching devices.Herein,the fabricated YNbO_(4):Er^(3+)/Tm^(3+)/Yb^(3+) materials exhibit excellent photochromism and multicolor upconversion properties from green,red to near infrared(NIR) emissions with increasing Yb concentrations.Reversible multiband upconversion modulations are achieved by alternating light(365 and 405 nm) or thermal stimuli.After 365 nm irradiation,the luminescence color changes from yellow to red,the luminescent photoswitching contrast reaches up to 86.21%(green),82.12%(red) and 77.38%(NIR) in the Y_(0.83)Er_(0.01)Tm_(0.01)NbO_(4):0.15 Yb sample.Besides,the upconversion emission intensity before and after photochromic reaction shows remarkable change in a wide temperature range of 298-718 K.These results indicate that the Er^(3+)/Tm^(3+)/Yb^(3+) tri-doped YNbO_(4) materials can be a good candidate in optical switching and data storage applications.展开更多
Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this...Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this work,we investigate the collective particle emission from a Bose-Einstein condensate confined in a one-dimensional lattice with periodically modulated interparticle interactions.We give the regimes for discrete modes,and find that the emission can be distinctly suppressed.The configuration induces a broad band,but few particles are ejected due to the interference of the matter waves.We further qualitatively model the emission process and demonstrate the short-time behaviors.This engineering provides a way to manipulate the propagation of particles and the corresponding dynamics of condensates in lattices,and may find application in the dynamical excitation control of other nonequilibrium problems with time-periodic driving.展开更多
Recently,soft decision modulations become the highlight of parallel combinatory spread spectrum ( PCSS) system. Existing soft decision BPSK and APK modulations are given and compared in the thesis. In order to apply s...Recently,soft decision modulations become the highlight of parallel combinatory spread spectrum ( PCSS) system. Existing soft decision BPSK and APK modulations are given and compared in the thesis. In order to apply soft decision QPSK modulation based on PCSS system,the correlation of superposition PN sequences is discussed. A weighted summation algorithm is adopted in QPSK demodulation to recover the whole orthogonal correlation of the superposition sequences; meanwhile the bit error rate of weighting soft decision QPSK modulation is simulated. The simulation results show that the bit error rate performance of proposed soft decision QPSK modulation based on PCSS system is better than that of hard decision modulation. The method proposed can be widely adopted in engineering application.展开更多
The particle modulations to turbulence in round jets were experimentally studied by means of two-phase velocity measurements with Phase Doppler Anemometer （PDA）. Laden with very large particles, no significant atten...The particle modulations to turbulence in round jets were experimentally studied by means of two-phase velocity measurements with Phase Doppler Anemometer （PDA）. Laden with very large particles, no significant attenuations of turbulence intensities were measured in the farfields, due to small two-phase slip velocities and particle Reynolds number. The gas-phase turbulence is enhanced by particles in the near-fields, but it is significantly attenuated by the small particles in the far-fields. The smaller particles have a more profound effect on the attenuation of turbulence intensities. The enhancements or attenuations of turbulence intensities in the far-fields depends on the energy production, transport and dissipation mechanisms between the two phases, which are determined by the particle prop- erties and two-phase velocity slips. The non-dimensional parameter CTI is introduced to represent the change of turbulence intensity.展开更多
To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the cl...To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification.展开更多
The highest occupied molecular orbital（HOMO） energies of fullerenes are found by quantitative first-principles calculations to be raised by negative charging, and the rising rate rank of the fullerenes is C60 >C7...The highest occupied molecular orbital（HOMO） energies of fullerenes are found by quantitative first-principles calculations to be raised by negative charging, and the rising rate rank of the fullerenes is C60 >C70 >C80 >C90>C100 >C180. Then we compare fullerenes with carbon nanotubes（CNTs） and graphene sheets（GSs） and find that the increase of the HOMO energy of a fullerene is much faster than that of CNTs and graphene sheets with the same number of C atoms. The rising rate rank is fullerene>CNT>GS, which holds no matter what the number of C atoms is or which structure the fullerene isomer is. This work paves a new path for developing all-carbon devices with low-dimensional carbon nanomaterials as different functional elements.展开更多
To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPT...To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.展开更多
We compare the transport properties of electrons in monolayer graphene by modulating the Fermi velocity inside the barrier. A critical transmission angle is found only when the Fermi velocity in the barriers is larger...We compare the transport properties of electrons in monolayer graphene by modulating the Fermi velocity inside the barrier. A critical transmission angle is found only when the Fermi velocity in the barriers is larger than the one outside the barriers. It is shown that the transmission exhibits periodicity with the incident angle below the critical transmission angle, and attenuates exponentially in the opposite situation. For both situations, peak splitting occurs in the transmission as the number of the velocity barriers increases, and the characteristics of the transmission suggest an interesting application of an excellent band-pass filter. The dependence of the conductance on the Fermi energy through an identical velocity- modulation structure differs wildly with different Fermi velocities of the barrier. The counterpart of the peak splitting is the sharp oscillations in the conductance profile. Furthermore, some oscillations for the multiple barriers are so sharp that the structure may be used as an excellent sensor.展开更多
To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from ...To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines （SVM） in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types （i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK） at SNRS ranging from 0dB to 25dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.展开更多
Transmission electron microscopy （TEM） study of SrPt2As2 reveals two incommensurate modulations appearing in the charge-density-wave （CDW） state below TCDW ≈ 470 K. These two structural modulations can be well ex...Transmission electron microscopy （TEM） study of SrPt2As2 reveals two incommensurate modulations appearing in the charge-density-wave （CDW） state below TCDW ≈ 470 K. These two structural modulations can be well explained in terms of condensations of two-coupled phonon modes with wave vectors of q1=0.62a＊ on the a＊-b＊ plane and q2 = 0.23a＊ on the a＊-c＊ plane. The atomic displacements occur along the b-axis direction for q1 and along the c-axis direction for q2, respectively. Moreover, the correlation between ql and q2 can be generally written as q1 = （q2 ＋ a＊）/2 in the CDW state, suggesting the presence of essential coupling between q1 and q2. A small fraction of Ir doping on the Pt site in Sr（Pt1-xIrx）2As2 （x ≤ 0.06） could moderately change these CDW modulations and also affect their superconductivities.展开更多
This paper explores the potential to use accurate but outdated channel estimates for adaptive modulation. The work is novel in that the research is conditioned on block by block adaptation. First,we define a new quant...This paper explores the potential to use accurate but outdated channel estimates for adaptive modulation. The work is novel in that the research is conditioned on block by block adaptation. First,we define a new quantity,the Tolerable Average Use Delay (TAUD),which can indicate the ability of an adaptation scheme to tolerate the delay of channel estimation results. We find that for the variable-power schemes,TAUD is a constant and dependent on the target Bit Error Rate (BER),average power and Doppler frequency; while for the constant-power schemes,it depends on the ad-aptation block length as well. At last,we investigate the relation between the delay tolerating per-formance and the spectral efficiency and give the system design criterion. The delay tolerating per-formance is improved at the price of lower data rate.展开更多
The development of intrinsically stretchable organic electrochemical synaptic transistors(ISOESTs)based entirely on elastomeric materials is pivotal for advancing applications requiring neuromorphic functionality unde...The development of intrinsically stretchable organic electrochemical synaptic transistors(ISOESTs)based entirely on elastomeric materials is pivotal for advancing applications requiring neuromorphic functionality under significant mechanical deformation.This study presents ISOESTs capable of replicating a comprehensive range of synaptic behaviors,including excitatory postsynaptic currents(EPSCs),paired-pulse facilitation(PPF),and transitions from short-term memory(STM)to long-term memory(LTM).Remarkably,these synaptic characteristics were preserved even when the devices were subjected to 30%uniaxial strain,demonstrating exceptional mechanical robustness and functional stability.A pixelated 5×5 array of ISOESTs exhibited minimal device-to-device variation,underscoring the scalability and uniformity of the fabrication approach.To further illustrate their potential,a neurologically integrated electronic skin(e-skin)was fabricated,incorporating these ISOESTs to enable modulation of synaptic responses.The modulation of synaptic responses was strongly correlated with electrochemical analyses,establishing a robust operational framework for programmable neuromorphic systems.Comprehensive investigations into device fabrication,operation mechanisms,and integration strategies provide critical insights into the potential of these systems for next-generation applications in wearable electronics,soft robotics,neuro-prosthetics,and human–machine interfaces.This work represents a significant step toward realizing adaptive,biologically inspired electronic platforms capable of bridging the gap between engineered systems and living tissues.展开更多
Currently,dual atomic catalysts(DACs)with neighboring active sites for oxygen reduction reaction(ORR)still meet lots of challenges in the synthesis,especially the construction of atomic pairs of elements from differen...Currently,dual atomic catalysts(DACs)with neighboring active sites for oxygen reduction reaction(ORR)still meet lots of challenges in the synthesis,especially the construction of atomic pairs of elements from different blocks of the periodic table.Herein,a“rare earth(Ce)-metalloid(Se)”non-bonding heteronuclear diatomic electrocatalyst has been constructed for ORR by rational coordination and carbon support defect engineering.Encouraging,the optimized Ce-Se diatomic catalysts(Ce-Se DAs/NC)displayed a half-wave potential of 0.886 V vs.reversible hydrogen electrode(RHE)and excellent stability,which surpass those of separate Ce or Se single atoms and most single/dual atomic catalysts ever reported.In addition,a primary zinc-air battery constructed using Ce-Se DAs/NC delivers a higher peak power density(209.2 mW·cm^(−2))and specific capacity(786.4 mAh·gZn^(−1))than state-of-the-art noble metal catalysts Pt/C.Theoretical calculations reveal that the Ce-Se DAs/NC has improved the electroactivity of the Ce-N_(4)region due to the electron transfer towards the nearby Se specific activity(SA)sites.Meanwhile,the more electron-rich Se sites promote the adsorptions of key intermediates,which results in the optimal performances of ORR on Ce-Se DAs/NC.This work provides new perspectives on electronic structure modulations via non-bonded long-range coordination micro-environment engineering in DACs for efficient electrocatalysis.展开更多
The present research employs artificial intelligence to come up with an automatic solution for the modulation's classification of various radio signal varieties.As a result,the work we performed involved selecting...The present research employs artificial intelligence to come up with an automatic solution for the modulation's classification of various radio signal varieties.As a result,the work we performed involved selecting the database required for supervised deep learning,evaluating the performance of current techniques on unprocessed communication signals,and suggesting a deep learning networkbased method that would enable the classification of modulation types with the best possible ratio between computation time and accuracy.We started by examining the automatic classification models that are currently in usage.In light of the difficulty of forecasting in low Signal Noise Ratio(SNR)situations,we suggested an ensemble learning strategy based on adjusted Res Net and Transformer Neural Network,which is effective at extracting multi-scale features from the raw I/Q sequence data.Finally,we produced an architecture that is simple to use and apply to communication signals.The architecture of this solution is strong and optimal,enabling it to determine the type of modulation with up to 95%accuracy automatically.展开更多
In this work,polarization mode dispersion(PMD)in polarization-maintaining(PM)fibers,to the best of our knowledge,is first proposed and experimentally proved to be responsible for severe spectral modulations in ultrafa...In this work,polarization mode dispersion(PMD)in polarization-maintaining(PM)fibers,to the best of our knowledge,is first proposed and experimentally proved to be responsible for severe spectral modulations in ultrafast PM fiber amplifiers,the introduction of which can give reasonable explanation for the dense spectral ripples imposed on the spectra of amplified lasers from the commonly used all-PM-fiber or hybrid“PM-fiber+bulk crystal”amplifiers,including both high-power amplifiers with remarkable nonlinear effects(self-phase modulation,SPM)and even low-power amplifiers with negligible nonlinear effects.展开更多
Fractional-N phase-locked loops(PLLs)are widely deployed in high-speed communication systems to generate local oscillator(LO)or clock signals with precise frequency.To support sophisticated modulations for increasing ...Fractional-N phase-locked loops(PLLs)are widely deployed in high-speed communication systems to generate local oscillator(LO)or clock signals with precise frequency.To support sophisticated modulations for increasing the data rate,the PLL needs to generate low-jitter output[1].展开更多
Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the p...Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.展开更多
文摘In the field of radiocommunication, modulation type identification is one of the most important characteristics in signal processing. This study aims to implement a modulation recognition system on two approaches to machine learning techniques, the K-Nearest Neighbors (KNN) and Artificial Neural Networks (ANN). From a statistical and spectral analysis of signals, nine key differentiation features are extracted and used as input vectors for each trained model. The feature extraction is performed by using the Hilbert transform, the forward and inverse Fourier transforms. The experiments with the AMC Master dataset classify ten (10) types of analog and digital modulations. AM_DSB_FC, AM_DSB_SC, AM_USB, AM_LSB, FM, MPSK, 2PSK, MASK, 2ASK, MQAM are put forward in this article. For the simulation of the chosen model, signals are polluted by the Additive White Gaussian Noise (AWGN). The simulation results show that the best identification rate is the MLP neuronal method with 90.5% of accuracy after 10 dB signal-to-noise ratio value, with a shift of more than 15% from the k-nearest neighbors’ algorithm.
基金Project supported by the National Natural Science Foundation of China(52062042,51802164)the Natural Science Foundation of Inner Mongolia(2020MS05044)。
文摘Photochromic materials with multicolor upconversion reversible modulations are attractive in optical switching devices.Herein,the fabricated YNbO_(4):Er^(3+)/Tm^(3+)/Yb^(3+) materials exhibit excellent photochromism and multicolor upconversion properties from green,red to near infrared(NIR) emissions with increasing Yb concentrations.Reversible multiband upconversion modulations are achieved by alternating light(365 and 405 nm) or thermal stimuli.After 365 nm irradiation,the luminescence color changes from yellow to red,the luminescent photoswitching contrast reaches up to 86.21%(green),82.12%(red) and 77.38%(NIR) in the Y_(0.83)Er_(0.01)Tm_(0.01)NbO_(4):0.15 Yb sample.Besides,the upconversion emission intensity before and after photochromic reaction shows remarkable change in a wide temperature range of 298-718 K.These results indicate that the Er^(3+)/Tm^(3+)/Yb^(3+) tri-doped YNbO_(4) materials can be a good candidate in optical switching and data storage applications.
基金supported by the China Scholarship Council(Grant No.201906130092)the Natural Science Research Start-up Foundation of Recruiting Talents of Nanjing University of Posts and Telecommunications(Grant No.NY223065)the Natural Science Foundation of Sichuan Province(Grant No.2023NSFSC1330).
文摘Emission of matter-wave jets from a parametrically driven condensate has attracted significant experimental and theoretical attention due to the appealing visual effects and potential metrological applications.In this work,we investigate the collective particle emission from a Bose-Einstein condensate confined in a one-dimensional lattice with periodically modulated interparticle interactions.We give the regimes for discrete modes,and find that the emission can be distinctly suppressed.The configuration induces a broad band,but few particles are ejected due to the interference of the matter waves.We further qualitatively model the emission process and demonstrate the short-time behaviors.This engineering provides a way to manipulate the propagation of particles and the corresponding dynamics of condensates in lattices,and may find application in the dynamical excitation control of other nonequilibrium problems with time-periodic driving.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61271263)
文摘Recently,soft decision modulations become the highlight of parallel combinatory spread spectrum ( PCSS) system. Existing soft decision BPSK and APK modulations are given and compared in the thesis. In order to apply soft decision QPSK modulation based on PCSS system,the correlation of superposition PN sequences is discussed. A weighted summation algorithm is adopted in QPSK demodulation to recover the whole orthogonal correlation of the superposition sequences; meanwhile the bit error rate of weighting soft decision QPSK modulation is simulated. The simulation results show that the bit error rate performance of proposed soft decision QPSK modulation based on PCSS system is better than that of hard decision modulation. The method proposed can be widely adopted in engineering application.
基金supported by the National Natural Science Foundation of China (50876053 and 50706021).
文摘The particle modulations to turbulence in round jets were experimentally studied by means of two-phase velocity measurements with Phase Doppler Anemometer （PDA）. Laden with very large particles, no significant attenuations of turbulence intensities were measured in the farfields, due to small two-phase slip velocities and particle Reynolds number. The gas-phase turbulence is enhanced by particles in the near-fields, but it is significantly attenuated by the small particles in the far-fields. The smaller particles have a more profound effect on the attenuation of turbulence intensities. The enhancements or attenuations of turbulence intensities in the far-fields depends on the energy production, transport and dissipation mechanisms between the two phases, which are determined by the particle prop- erties and two-phase velocity slips. The non-dimensional parameter CTI is introduced to represent the change of turbulence intensity.
文摘To promote reliable and secure communications in the cognitive radio network,the automatic modulation classification algorithms have been mainly proposed to estimate a single modulation.In this paper,we address the classification of superimposed modulations dedicated to 5G multipleinput multiple-output(MIMO)two-way cognitive relay network in realistic channels modeled with Nakagami-m distribution.Our purpose consists of classifying pairs of users modulations from superimposed signals.To achieve this goal,we apply the higher-order statistics in conjunction with the Multi-BoostAB classifier.We use several efficiency metrics including the true positive(TP)rate,false positive(FP)rate,precision,recall,F-Measure and receiver operating characteristic(ROC)area in order to evaluate the performance of the proposed algorithm in terms of correct superimposed modulations classification.Computer simulations prove that our proposal allows obtaining a good probability of classification for ten superimposed modulations at a low signal-to-noise ratio,including the worst case(i.e.,m=0.5),where the fading distribution follows a one-sided Gaussian distribution.We also carry out a comparative study between our proposal usingMultiBoostAB classifier with the decision tree(J48)classifier.Simulation results show that the performance of MultiBoostAB on the superimposed modulations classifications outperforms the one of J48 classifier.In addition,we study the impact of the symbols number,path loss exponent and relay position on the performance of the proposed automatic classification superimposed modulations in terms of probability of correct classification.
基金Supported by the National Natural Science Foundation of China under Grant Nos 11374174,51390471,51527803,and 51701143the National Basic Research Program of China under Grant No 2015CB654902+4 种基金the National Key Research and Development Program under Grant No 2016YFB0700402the Foundation for the Author of National Excellent Doctoral Dissertation under Grant No 201141the National Program for Thousand Young Talents of China,the Tianjin Municipal Education Commissionthe Tianjin Municipal Science and Technology Commissionthe Fundamental Research Fund of Tianjin University of Technology
文摘The highest occupied molecular orbital（HOMO） energies of fullerenes are found by quantitative first-principles calculations to be raised by negative charging, and the rising rate rank of the fullerenes is C60 >C70 >C80 >C90>C100 >C180. Then we compare fullerenes with carbon nanotubes（CNTs） and graphene sheets（GSs） and find that the increase of the HOMO energy of a fullerene is much faster than that of CNTs and graphene sheets with the same number of C atoms. The rising rate rank is fullerene>CNT>GS, which holds no matter what the number of C atoms is or which structure the fullerene isomer is. This work paves a new path for developing all-carbon devices with low-dimensional carbon nanomaterials as different functional elements.
文摘To make the modulation classification system more suitable for signals in a wide range of signal to noise rate （SNR）, a feature extraction method based on signal wavelet packet transform modulus maxima matrix （WPTMMM） and a novel support vector machine fuzzy network （SVMFN） classifier is presented. The WPTMMM feature extraction method has less computational complexity, more stability, and has the preferable advantage of robust with the time parallel moving and white noise. Further, the SVMFN uses a new definition of fuzzy density that incorporates accuracy and uncertainty of the classifiers to improve recognition reliability to classify nine digital modulation types （i.e. 2ASK, 2FSK, 2PSK, 4ASK, 4FSK, 4PSK, 16QAM, MSK, and OQPSK）. Computer simulation shows that the proposed scheme has the advantages of high accuracy and reliability （success rates are over 98% when SNR is not lower than 0dB）, and it adapts to engineering applications.
基金Project supported by the National Natural Science Foundation of China (Grant No. 11104156)the Postdoctoral Science Foundation of China (CPSF) (Grant No. 2012M510405)+1 种基金the Independent Research and Development Fund of Tsinghua University (Grant No. 20121087948)Beijing Key Laboratory of Fine Ceramics Opening Fund (Grant No. 2012200110)
文摘We compare the transport properties of electrons in monolayer graphene by modulating the Fermi velocity inside the barrier. A critical transmission angle is found only when the Fermi velocity in the barriers is larger than the one outside the barriers. It is shown that the transmission exhibits periodicity with the incident angle below the critical transmission angle, and attenuates exponentially in the opposite situation. For both situations, peak splitting occurs in the transmission as the number of the velocity barriers increases, and the characteristics of the transmission suggest an interesting application of an excellent band-pass filter. The dependence of the conductance on the Fermi energy through an identical velocity- modulation structure differs wildly with different Fermi velocities of the barrier. The counterpart of the peak splitting is the sharp oscillations in the conductance profile. Furthermore, some oscillations for the multiple barriers are so sharp that the structure may be used as an excellent sensor.
文摘To make the modulation classification system more suitable for signals in a wide range of signal to noise ratios （SNRs）, a novel adaptive modulation classification scheme is presented in this paper. Differ-ent from traditional schemes, the proposed scheme employs a new SNR estimation algorithm for small samples before modulation classification, which makes the modulation classifier work adaptively according to estimated SNRs. Furthermore, it uses three efficient features and support vector machines （SVM） in modulation classification. Computer simulation shows that the scheme can adaptively classify ten digital modulation types （i.e. 2ASK, 4ASK, 2FSK, 4FSK, 2PSK, 4PSK, 16QAM, TFM, π/4QPSK and OQPSK） at SNRS ranging from 0dB to 25dB and success rates are over 95% when SNR is not lower than 3dB. Accuracy, efficiency and simplicity of the proposed scheme are obviously improved, which make it more adaptive to engineering applications.
基金Project supported by the National Basic Research Program of China(Grant Nos.2011CBA00101,2010CB923002,2012CB821404,and 2011CB921703)the National Natural Science Foundation of China(Grant Nos.11190022,11274368,and 51272277)the Funds from the Chinese Academy of Sciences
文摘Transmission electron microscopy （TEM） study of SrPt2As2 reveals two incommensurate modulations appearing in the charge-density-wave （CDW） state below TCDW ≈ 470 K. These two structural modulations can be well explained in terms of condensations of two-coupled phonon modes with wave vectors of q1=0.62a＊ on the a＊-b＊ plane and q2 = 0.23a＊ on the a＊-c＊ plane. The atomic displacements occur along the b-axis direction for q1 and along the c-axis direction for q2, respectively. Moreover, the correlation between ql and q2 can be generally written as q1 = （q2 ＋ a＊）/2 in the CDW state, suggesting the presence of essential coupling between q1 and q2. A small fraction of Ir doping on the Pt site in Sr（Pt1-xIrx）2As2 （x ≤ 0.06） could moderately change these CDW modulations and also affect their superconductivities.
基金Supported by the National Natural Science Foundation of China (No.60496311).
文摘This paper explores the potential to use accurate but outdated channel estimates for adaptive modulation. The work is novel in that the research is conditioned on block by block adaptation. First,we define a new quantity,the Tolerable Average Use Delay (TAUD),which can indicate the ability of an adaptation scheme to tolerate the delay of channel estimation results. We find that for the variable-power schemes,TAUD is a constant and dependent on the target Bit Error Rate (BER),average power and Doppler frequency; while for the constant-power schemes,it depends on the ad-aptation block length as well. At last,we investigate the relation between the delay tolerating per-formance and the spectral efficiency and give the system design criterion. The delay tolerating per-formance is improved at the price of lower data rate.
基金supported by a New Faculty Research Grant of Pusan National University,2023support from the National Research Foundation of Korea(NRF)(Nos.RS-2023-00222166 and RS-2025-00558955).
文摘The development of intrinsically stretchable organic electrochemical synaptic transistors(ISOESTs)based entirely on elastomeric materials is pivotal for advancing applications requiring neuromorphic functionality under significant mechanical deformation.This study presents ISOESTs capable of replicating a comprehensive range of synaptic behaviors,including excitatory postsynaptic currents(EPSCs),paired-pulse facilitation(PPF),and transitions from short-term memory(STM)to long-term memory(LTM).Remarkably,these synaptic characteristics were preserved even when the devices were subjected to 30%uniaxial strain,demonstrating exceptional mechanical robustness and functional stability.A pixelated 5×5 array of ISOESTs exhibited minimal device-to-device variation,underscoring the scalability and uniformity of the fabrication approach.To further illustrate their potential,a neurologically integrated electronic skin(e-skin)was fabricated,incorporating these ISOESTs to enable modulation of synaptic responses.The modulation of synaptic responses was strongly correlated with electrochemical analyses,establishing a robust operational framework for programmable neuromorphic systems.Comprehensive investigations into device fabrication,operation mechanisms,and integration strategies provide critical insights into the potential of these systems for next-generation applications in wearable electronics,soft robotics,neuro-prosthetics,and human–machine interfaces.This work represents a significant step toward realizing adaptive,biologically inspired electronic platforms capable of bridging the gap between engineered systems and living tissues.
基金the support from the National Key R&D Program of China(No.2021YFA1501101)the National Natural Science Foundation of China(No.21971117)+12 种基金the National Natural Science Foundation of China/Research Grant Council of Hong Kong Joint Research Scheme(No.N_PolyU502/21)the National Natural Science Foundation of China/Research Grants Council(RGC)of Hong Kong Collaborative Research Scheme(No.CRS_PolyU504/22)the Functional Research Funds for the Central Nankai University(No.63186005)the Tianjin Key Lab for Rare Earth Materials and Applications(No.ZB19500202)the Open Funds(No.RERU2019001)the State Key Laboratory of Rare Earth Resource Utilization,the 111 Project(No.B18030)from Chinathe Beijing-Tianjin-Hebei Collaborative Innovation Project(No.19YFSLQY00030)the Outstanding Youth Project of Tianjin 21 Natural Science Foundation(No.20JCJQJC00130)the Key Project of Tianjin Natural Science Foundation(No.20JCZDJC00650)the funding for Projects of Strategic Importance of The Hong Kong Polytechnic University(Project Code:1-ZE2V)the Shenzhen Fundamental Research Scheme-General Program(No.JCYJ20220531090807017)the Natural Science Foundation of Guangdong Province(No.2023A1515012219)the Departmental General Research Fund(Project Code:ZVUL)from The Hong Kong Polytechnic University.
文摘Currently,dual atomic catalysts(DACs)with neighboring active sites for oxygen reduction reaction(ORR)still meet lots of challenges in the synthesis,especially the construction of atomic pairs of elements from different blocks of the periodic table.Herein,a“rare earth(Ce)-metalloid(Se)”non-bonding heteronuclear diatomic electrocatalyst has been constructed for ORR by rational coordination and carbon support defect engineering.Encouraging,the optimized Ce-Se diatomic catalysts(Ce-Se DAs/NC)displayed a half-wave potential of 0.886 V vs.reversible hydrogen electrode(RHE)and excellent stability,which surpass those of separate Ce or Se single atoms and most single/dual atomic catalysts ever reported.In addition,a primary zinc-air battery constructed using Ce-Se DAs/NC delivers a higher peak power density(209.2 mW·cm^(−2))and specific capacity(786.4 mAh·gZn^(−1))than state-of-the-art noble metal catalysts Pt/C.Theoretical calculations reveal that the Ce-Se DAs/NC has improved the electroactivity of the Ce-N_(4)region due to the electron transfer towards the nearby Se specific activity(SA)sites.Meanwhile,the more electron-rich Se sites promote the adsorptions of key intermediates,which results in the optimal performances of ORR on Ce-Se DAs/NC.This work provides new perspectives on electronic structure modulations via non-bonded long-range coordination micro-environment engineering in DACs for efficient electrocatalysis.
文摘The present research employs artificial intelligence to come up with an automatic solution for the modulation's classification of various radio signal varieties.As a result,the work we performed involved selecting the database required for supervised deep learning,evaluating the performance of current techniques on unprocessed communication signals,and suggesting a deep learning networkbased method that would enable the classification of modulation types with the best possible ratio between computation time and accuracy.We started by examining the automatic classification models that are currently in usage.In light of the difficulty of forecasting in low Signal Noise Ratio(SNR)situations,we suggested an ensemble learning strategy based on adjusted Res Net and Transformer Neural Network,which is effective at extracting multi-scale features from the raw I/Q sequence data.Finally,we produced an architecture that is simple to use and apply to communication signals.The architecture of this solution is strong and optimal,enabling it to determine the type of modulation with up to 95%accuracy automatically.
基金supported by the National Natural Science Foundation of China(Nos.62375156,62075116,62075117)the Foundation of Qilu Young Scholar from Shandong University。
文摘In this work,polarization mode dispersion(PMD)in polarization-maintaining(PM)fibers,to the best of our knowledge,is first proposed and experimentally proved to be responsible for severe spectral modulations in ultrafast PM fiber amplifiers,the introduction of which can give reasonable explanation for the dense spectral ripples imposed on the spectra of amplified lasers from the commonly used all-PM-fiber or hybrid“PM-fiber+bulk crystal”amplifiers,including both high-power amplifiers with remarkable nonlinear effects(self-phase modulation,SPM)and even low-power amplifiers with negligible nonlinear effects.
基金supported by the University of Macao Research Fund under Grant MYRG-GRG2024-00298-IMEby the Macao Science and Technology Development Fund(FDCT)under Grant 0103/2022/AFJ.
文摘Fractional-N phase-locked loops(PLLs)are widely deployed in high-speed communication systems to generate local oscillator(LO)or clock signals with precise frequency.To support sophisticated modulations for increasing the data rate,the PLL needs to generate low-jitter output[1].
基金supported by the National Natural Science Foundation of China(51767017)the Basic Research Innovation Group Project of Gansu Province(18JR3RA133)the Industrial Support and Guidance Project of Universities in Gansu Province(2022CYZC-22).
文摘Photovoltaic (PV) modules, as essential components of solar power generation systems, significantly influence unitpower generation costs.The service life of these modules directly affects these costs. Over time, the performanceof PV modules gradually declines due to internal degradation and external environmental factors.This cumulativedegradation impacts the overall reliability of photovoltaic power generation. This study addresses the complexdegradation process of PV modules by developing a two-stage Wiener process model. This approach accountsfor the distinct phases of degradation resulting from module aging and environmental influences. A powerdegradation model based on the two-stage Wiener process is constructed to describe individual differences inmodule degradation processes. To estimate the model parameters, a combination of the Expectation-Maximization(EM) algorithm and the Bayesian method is employed. Furthermore, the Schwarz Information Criterion (SIC) isutilized to identify critical change points in PV module degradation trajectories. To validate the universality andeffectiveness of the proposed method, a comparative analysis is conducted against other established life predictiontechniques for PV modules.
