In this paper, we consider the design of interconnected H-infinity feedback control systems with quantized signals. We assume that a decentralized static output feedback has been designed for an interconnected continu...In this paper, we consider the design of interconnected H-infinity feedback control systems with quantized signals. We assume that a decentralized static output feedback has been designed for an interconnected continuous-time LTI system so that the closed-loop system is stable and a desired H-infinity disturbance attenuation level is achieved, and that the subsystems＇ measurement outputs are quantized before they are passed to the local controller. We propose a local-output-dependent strategy for updating the quantizers＇ parameters, so that the overall closed-loop system is asymptotically stable and achieves the same H-infinity disturbance attenuation level. Both the pre-designed controllers and the quantizers＇ parameters are constructed in a decentralized manner, depending on local information.展开更多
A new scheme is presented to design a rotated Barnes-Wall lattice based vector quantizer(LVQ). The construction method of the LVQ and its fast quantizing algorithm are described at first. Then gain-shape lattice vecto...A new scheme is presented to design a rotated Barnes-Wall lattice based vector quantizer(LVQ). The construction method of the LVQ and its fast quantizing algorithm are described at first. Then gain-shape lattice vector quantizer(GSLVQ) with LVQ as shape quantizer is discussed. Finally the GSLVQ is used in image-sequence coding and good experimental results are obtained.展开更多
AVQ(Adaptive Vector Quantizer)overcomes some shortcomings of traditional vectorquantizer with a fixed codebook trained and generated by the LBG or other algorithms by applyinga variab|e codebook.In this paper,we descr...AVQ(Adaptive Vector Quantizer)overcomes some shortcomings of traditional vectorquantizer with a fixed codebook trained and generated by the LBG or other algorithms by applyinga variab|e codebook.In this paper,we describe an effective and efficient implementation of AVQby modifying the CCN(Carpenter/Grossberg Net).The encoding process of AVQ is very similarto the learning process of the CGN.We study several different encoding schemes,includingwaveform AVQ,analysed parameter AVQ and so on,implemented by the CGN.And we simulatethe encoding performance of each scheme for encoding Gaussian process source,first order Gauss-Markov process source and practical speech signal.Our simulation results show that good qualityboth in subjective and objective tests can be obtained in a low or middle bit rate range.展开更多
This article presents a high speed third-order continuous-time(CT)sigma-delta analog-to-digital converter(SDADC)based on voltagecontrolled oscillator(VCO),featuring a digital programmable quantizer structure.To improv...This article presents a high speed third-order continuous-time(CT)sigma-delta analog-to-digital converter(SDADC)based on voltagecontrolled oscillator(VCO),featuring a digital programmable quantizer structure.To improve the overall performance,not only oversampling technique but also noise-shaping enhancing technique is used to suppress in-band noise.Due to the intrinsic first-order noise-shaping of the VCO quantizer,the proposed third-order SDADC can realize forth-order noise-shaping ideally.As a bright advantage,the proposed programmable VCO quantizer is digital-friendly,which can simplify the design process and improve antiinterference capability of the circuit.A 4-bit programmable VCO quantizer clocked at 2.5 GHz,which is proposed in a 40 nm complementary metaloxide semiconductor(CMOS)technology,consists of an analog VCO circuit and a digital programmable quantizer,achieving 50.7 dB signal-to-noise ratio(SNR)and 26.9 dB signal-to-noise-and-distortion ration(SNDR)for a 19 MHz−3.5 dBFS input signal in 78 MHz bandwidth(BW).The digital quantizer,which is programmed in the Verilog hardware description language(HDL),consists of two-stage D-flip-flop(DFF)based registers,XOR gates and an adder.The presented SDADC adopts the cascade of integrators with feed-forward summation(CIFF)structure with a third-order loop filter,operating at 2.5 GHz and showing behavioral simulation performance of 92.9 dB SNR over 78 MHz bandwidth.展开更多
A high-speed and high-resolution optical A/D quantizer is proposed.Its architecture is discussed.Bit circuits are built by using the phase modulators in parallel.Based on the different character of the half-wave volta...A high-speed and high-resolution optical A/D quantizer is proposed.Its architecture is discussed.Bit circuits are built by using the phase modulators in parallel.Based on the different character of the half-wave voltage for every phase modulator and the polarized bias design of incident light,the RF input signal is coled and transmitted in the form of optical digital signal.According to the principle of the architecture,the high-resolution quantizers with 8-bit and 12-bit,et al.are built,which operate at 100 GS/s.Their quantization noise is invariable almost with bit circuits increasing.The simulation result of 4-bit A/D quantizer is also given.展开更多
Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in speci...Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.展开更多
In this paper, the optimization of quantizer’s segment threshold is done. The quantizer is designed on the basis of approximative spline functions. Coefficients on which we form approximative spline functions are cal...In this paper, the optimization of quantizer’s segment threshold is done. The quantizer is designed on the basis of approximative spline functions. Coefficients on which we form approximative spline functions are calculated by minimization mean square error (MSE). For coefficients determined in this way, spline functions by which optimal compressor function is approximated are obtained. For the quantizer designed on the basis of approximative spline functions, segment threshold is numerically determined depending on maximal value of the signal to quantization noise ratio (SQNR). Thus, quantizer with optimized segment threshold is achieved. It is shown that by quantizer model designed in this way and proposed in this paper, the SQNR that is very close to SQNR of nonlinear optimal companding quantizer is achieved.展开更多
Quantization noise caused by analog-to-digital converter(ADC)gives rise to the reliability performance degradation of communication systems.In this paper,a quantized non-Hermitian symmetry(NHS)orthogonal frequency-div...Quantization noise caused by analog-to-digital converter(ADC)gives rise to the reliability performance degradation of communication systems.In this paper,a quantized non-Hermitian symmetry(NHS)orthogonal frequency-division multiplexing-based visible light communication(OFDM-VLC)system is presented.In order to analyze the effect of the resolution of ADC on NHS OFDM-VLC,a quantized mathematical model of NHS OFDM-VLC is established.Based on the proposed quantized model,a closed-form bit error rate(BER)expression is derived.The theoretical analysis and simulation results both confirm the effectiveness of the obtained BER formula in high-resolution ADC.In addition,channel coding is helpful in compensating for the BER performance loss due to the utilization of lower resolution ADC.展开更多
The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text classificati...The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text classification.However,BERT’s size and computational demands limit its practicality,especially in resource-constrained settings.This research compresses the BERT base model for Bengali emotion classification through knowledge distillation(KD),pruning,and quantization techniques.Despite Bengali being the sixth most spoken language globally,NLP research in this area is limited.Our approach addresses this gap by creating an efficient BERT-based model for Bengali text.We have explored 20 combinations for KD,quantization,and pruning,resulting in improved speedup,fewer parameters,and reduced memory size.Our best results demonstrate significant improvements in both speed and efficiency.For instance,in the case of mBERT,we achieved a 3.87×speedup and 4×compression ratio with a combination of Distil+Prune+Quant that reduced parameters from 178 to 46 M,while the memory size decreased from 711 to 178 MB.These results offer scalable solutions for NLP tasks in various languages and advance the field of model compression,making these models suitable for real-world applications in resource-limited environments.展开更多
We consider a relativistic two-fluid model of superfluidity,in which the superfluid is described by an order parameter that is a complex scalar field satisfying the nonlinear Klein-Gordon equation(NLKG).The coupling t...We consider a relativistic two-fluid model of superfluidity,in which the superfluid is described by an order parameter that is a complex scalar field satisfying the nonlinear Klein-Gordon equation(NLKG).The coupling to the normal fluid is introduced via a covariant current-current interaction,which results in the addition of an effective potential,whose imaginary part describes particle transfer between superfluid and normal fluid.Quantized vorticity arises in a class of singular solutions and the related vortex dynamics is incorporated in the modified NLKG,facilitating numerical analysis which is usually very complicated in the phenomenology of vortex filaments.The dual transformation to a string theory description(Kalb-Ramond)of quantum vorticity,the Magnus force,and the mutual friction between quantized vortices and normal fluid are also studied.展开更多
This study focuses on determining the second-order irregular wave loads in the time domain without using the Inverse Fast Fourier Transform(IFFT).Considering the substantial displacement effects that Floating Offshore...This study focuses on determining the second-order irregular wave loads in the time domain without using the Inverse Fast Fourier Transform(IFFT).Considering the substantial displacement effects that Floating Offshore Wind Turbine(FOWT)support structures undergo when subjected to wave loads,the time-domain wave method is more suitable,while the frequency-domain method requiring IFFT cannot be used for moving bodies.Nonetheless,the computational challenges posed by the considerable computer time requirements of the time-domain wave method remain a significant obstacle.Thus,the paper incorporates various numerical schemes,including parallel computing and extrapolation of wave forces during specific time steps to improve overall efficiency.Despite the effectiveness of these schemes,the computational difficulties associated with the time-domain wave method persist.This study then proposes an innovative approach utilizing different randomnumbers in distinct segments,significantly reducing the computation of second-order wave loads.This random number interpolation ensures a smooth curve transition between two segments,emphasizingminimizing errors near the end of the first segment.Numerical analyses demonstrate substantial decreases in total computer time for FOWT structural analyses while maintaining consistent steel design results.The proposed method is uncomplicated,requiring only a simple subprogram modification in a conventional wave load computer program.展开更多
This paper proposes a novel method for the automatic diagnosis of keratitis using feature vector quantization and self-attention mechanisms(ADK_FVQSAM).First,high-level features are extracted using the DenseNet121 bac...This paper proposes a novel method for the automatic diagnosis of keratitis using feature vector quantization and self-attention mechanisms(ADK_FVQSAM).First,high-level features are extracted using the DenseNet121 backbone network,followed by adaptive average pooling to scale the features to a fixed length.Subsequently,product quantization with residuals(PQR)is applied to convert continuous feature vectors into discrete features representations,preserving essential information insensitive to image quality variations.The quantized and original features are concatenated and fed into a self-attention mechanism to capture keratitis-related features.Finally,these enhanced features are classified through a fully connected layer.Experiments on clinical low-quality(LQ)images show that ADK_FVQSAM achieves accuracies of 87.7%,81.9%,and 89.3% for keratitis,other corneal abnormalities,and normal corneas,respectively.Compared to DenseNet121,Swin transformer,and InceptionResNet,ADK_FVQSAM improves average accuracy by 3.1%,11.3%,and 15.3%,respectively.These results demonstrate that ADK_FVQSAM significantly enhances the recognition performance of keratitis based on LQ slit-lamp images,offering a practical approach for clinical application.展开更多
Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and ...Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and over-determined problems in the inversion. The correlation complicates the mapping relation between the ATEM data and the earth parameters and thus increases the inversion complexity. To obviate this, we adopt principal component analysis to transform ATEM data into orthogonal principal components （PCs） to reduce the correlations and the data dimensionality and simultaneously suppress the unrelated noise. In this paper, we use an artificial neural network （ANN） to approach the PCs mapping relation with the earth model parameters, avoiding the calculation of Jacobian derivatives. The PC-based ANN algorithm is applied to synthetic data for layered models compared with data-based ANN for airborne time-domain electromagnetic inversion. The results demonstrate the PC-based ANN advantages of simpler network structure, less training steps, and better inversion results over data-based ANN, especially for contaminated data. Furthermore, the PC-based ANN algorithm effectiveness is examined by the inversion of the pseudo 2D model and comparison with data-based ANN and Zhody＇s methods. The results indicate that PC-based ANN inversion can achieve a better agreement with the true model and also proved that PC-based ANN is feasible to invert large ATEM datasets.展开更多
An electromagnetic field is generated through the accelerating movement of two equal but opposite charges of a single dipole. An electromagnetic field can also be generated by a time-varying infinitesimal point charge...An electromagnetic field is generated through the accelerating movement of two equal but opposite charges of a single dipole. An electromagnetic field can also be generated by a time-varying infinitesimal point charge. In this study, a comparison between the electromagnetic fields of an infinitesimal point charge and a dipole has been presented. First, the time-domain potential function of a point source in a 3D conductive medium is derived. Then the electric and magnetic fields in a 3D homogeneous lossless space are derived via the relation between the potential and field. The field differences between the infinitesimal point charge and the dipole in the step-off time, far-source, and near-source zones are analyzed, and the accuracy of the solutions from these sources is investigated. It is also shown that the field of the infinitesimal point charge in the near-source zone is different from that of the dipole, whereas the far-source zone fields of these two sources are identical. The comparison of real and simulated data shows that the infinitesimal point charge represents the real source better than the divole source.展开更多
To effectively minimize the electromagnetic field response in the total field solution, we propose a numerical modeling method for the two-dimensional （2D） time- domain transient electromagnetic secondary field of t...To effectively minimize the electromagnetic field response in the total field solution, we propose a numerical modeling method for the two-dimensional （2D） time- domain transient electromagnetic secondary field of the line source based on the DuFort- Frankel finite-difference method. In the proposed method, we included the treatment of the earth-air boundary conductivity, calculated the normalized partial derivative of the induced electromotive force （Emf）, and determined the forward time step. By extending upward the earth-air interface to the air grid nodes and the zero-value boundary conditions, not only we have a method that is more efficient but also simpler than the total field solution. We computed and analyzed the homogeneous half-space model and the fiat layered model with high precision--the maximum relative error is less than 0.01% between our method and the analytical method--and the solution speed is roughly three times faster than the total-field solution. Lastly, we used the model of a thin body embedded in a homogeneous half-space at different delay times to depict the downward and upward spreading characteristics of the induced eddy current, and the physical interaction processes between the electromagnetic field and the underground low-resistivity body.展开更多
In order to overcome data-quantization, networked-induced delay, network packet dropouts and wrong sequences in the nonlinear networked control system, a novel nonlinear networked control system model is built by the ...In order to overcome data-quantization, networked-induced delay, network packet dropouts and wrong sequences in the nonlinear networked control system, a novel nonlinear networked control system model is built by the T-S fuzzy method. Two time-varying quantizers are added in the model. The key analysis steps in the method are to construct an improved interval-delay-dependent Lyapunov functional and to introduce the free-weighting matrix. By making use of the parallel distributed compensation technology and the convexity of the matrix function, the improved criteria of the stabilization and stability are obtained. Simulation experiments show that the parameters of the controllers and quantizers satisfying a certain performance can be obtained by solving a set of LMIs. The application of the nonlinear mass-spring system is provided to show that the proposed method is effective.展开更多
Electrically anisotropic strata are abundant in nature, so their study can help our data interpretation and our understanding of the processes of geodynamics. However, current data processing generally assumes isotrop...Electrically anisotropic strata are abundant in nature, so their study can help our data interpretation and our understanding of the processes of geodynamics. However, current data processing generally assumes isotropic conditions when surveying anisotropic structures, which may cause discrepancies between reality and electromagnetic data interpretation. Moreover, the anisotropic interpretation of the time-domain airborne electromagnetic （TDAEM） method is still confined to one dimensional （1D） cases, and the corresponding three-dimensional （3D） numerical simulations are still in development. In this study, we expanded the 3D TDAEM modeling of arbitrarily anisotropic media. First, through coordinate rotation of isotropic conductivity, we obtained the conductivity tensor of an arbitrary anisotropic rock. Next, we incorporated this into Maxwell＇s equations, using a regular hexahedral grid of vector finite elements to subdivide the solution area. A direct solver software package provided the solution for the sparse linear equations that resulted. Analytical solutions were used to verify the accuracy and feasibility of the algorithm. The proven model was then applied to analyze the effects of arbitrary anisotropy in 3D TDAEM via the distribution of responses and amplitude changes, which revealed that different anisotropy situations strongly affected the responses of TDAEM.展开更多
基金Supported by National Natural Science Foundation of China （60674021）, Program for New Century Excellent Talents in University （NCET-04-0283）, the Funds for Creative Research Groups of China （60521003）, Program for Changjiang Scholars and Innovative Research Team in University （IRT0421）, the State Key Program of National Natural Science of China （60534010） and the Funds of Ph. D. Program of Ministry of Education, China （20060145019）
文摘使量子化的动态产量反馈 H 控制为的问题分离时间线性时间不变(LTI ) 系统在这份报纸被调查。考虑的 quantizer 动态、镇静一可调节激增参数和静态的 quantizer。静态的 quantizer 范围具有实际意义并且充分被考虑。首先，考虑量子化错误，使量子化的控制策略控制器状态依赖于不仅而且在系统测量产量上，它被建议以便使量子化的靠近环的系统是 asymptotically 稳定的，与规定 H，性能跳。根据这结果，然后，一个反复的基于 LMI 的优化算法被开发优化静态的 quantizer 范围为靠近环的系统满足 H 表演要求。一个例子被举说明建议方法的有效性。
基金supported by the Japan Ministry of Education,Sciences and Culture under Grant-in-Aid for Scientific Research(C)(No.21560471)
文摘In this paper, we consider the design of interconnected H-infinity feedback control systems with quantized signals. We assume that a decentralized static output feedback has been designed for an interconnected continuous-time LTI system so that the closed-loop system is stable and a desired H-infinity disturbance attenuation level is achieved, and that the subsystems＇ measurement outputs are quantized before they are passed to the local controller. We propose a local-output-dependent strategy for updating the quantizers＇ parameters, so that the overall closed-loop system is asymptotically stable and achieves the same H-infinity disturbance attenuation level. Both the pre-designed controllers and the quantizers＇ parameters are constructed in a decentralized manner, depending on local information.
基金Supported in part by subject 863-317 (China Communication 863 Programme)Fund of Xidian University and ISN National Key Lab
文摘A new scheme is presented to design a rotated Barnes-Wall lattice based vector quantizer(LVQ). The construction method of the LVQ and its fast quantizing algorithm are described at first. Then gain-shape lattice vector quantizer(GSLVQ) with LVQ as shape quantizer is discussed. Finally the GSLVQ is used in image-sequence coding and good experimental results are obtained.
文摘AVQ(Adaptive Vector Quantizer)overcomes some shortcomings of traditional vectorquantizer with a fixed codebook trained and generated by the LBG or other algorithms by applyinga variab|e codebook.In this paper,we describe an effective and efficient implementation of AVQby modifying the CCN(Carpenter/Grossberg Net).The encoding process of AVQ is very similarto the learning process of the CGN.We study several different encoding schemes,includingwaveform AVQ,analysed parameter AVQ and so on,implemented by the CGN.And we simulatethe encoding performance of each scheme for encoding Gaussian process source,first order Gauss-Markov process source and practical speech signal.Our simulation results show that good qualityboth in subjective and objective tests can be obtained in a low or middle bit rate range.
基金This work was supported by the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under Grant No.18KJB510045.
文摘This article presents a high speed third-order continuous-time(CT)sigma-delta analog-to-digital converter(SDADC)based on voltagecontrolled oscillator(VCO),featuring a digital programmable quantizer structure.To improve the overall performance,not only oversampling technique but also noise-shaping enhancing technique is used to suppress in-band noise.Due to the intrinsic first-order noise-shaping of the VCO quantizer,the proposed third-order SDADC can realize forth-order noise-shaping ideally.As a bright advantage,the proposed programmable VCO quantizer is digital-friendly,which can simplify the design process and improve antiinterference capability of the circuit.A 4-bit programmable VCO quantizer clocked at 2.5 GHz,which is proposed in a 40 nm complementary metaloxide semiconductor(CMOS)technology,consists of an analog VCO circuit and a digital programmable quantizer,achieving 50.7 dB signal-to-noise ratio(SNR)and 26.9 dB signal-to-noise-and-distortion ration(SNDR)for a 19 MHz−3.5 dBFS input signal in 78 MHz bandwidth(BW).The digital quantizer,which is programmed in the Verilog hardware description language(HDL),consists of two-stage D-flip-flop(DFF)based registers,XOR gates and an adder.The presented SDADC adopts the cascade of integrators with feed-forward summation(CIFF)structure with a third-order loop filter,operating at 2.5 GHz and showing behavioral simulation performance of 92.9 dB SNR over 78 MHz bandwidth.
基金Natural Science Foundation from Colleges and Universities of Jiangsu Province(04KJD140033)
文摘A high-speed and high-resolution optical A/D quantizer is proposed.Its architecture is discussed.Bit circuits are built by using the phase modulators in parallel.Based on the different character of the half-wave voltage for every phase modulator and the polarized bias design of incident light,the RF input signal is coled and transmitted in the form of optical digital signal.According to the principle of the architecture,the high-resolution quantizers with 8-bit and 12-bit,et al.are built,which operate at 100 GS/s.Their quantization noise is invariable almost with bit circuits increasing.The simulation result of 4-bit A/D quantizer is also given.
基金supported by the National Key R&D Program of China(No.2021YFB0301200)National Natural Science Foundation of China(No.62025208).
文摘Large-scale Language Models(LLMs)have achieved significant breakthroughs in Natural Language Processing(NLP),driven by the pre-training and fine-tuning paradigm.While this approach allows models to specialize in specific tasks with reduced training costs,the substantial memory requirements during fine-tuning present a barrier to broader deployment.Parameter-Efficient Fine-Tuning(PEFT)techniques,such as Low-Rank Adaptation(LoRA),and parameter quantization methods have emerged as solutions to address these challenges by optimizing memory usage and computational efficiency.Among these,QLoRA,which combines PEFT and quantization,has demonstrated notable success in reducing memory footprints during fine-tuning,prompting the development of various QLoRA variants.Despite these advancements,the quantitative impact of key variables on the fine-tuning performance of quantized LLMs remains underexplored.This study presents a comprehensive analysis of these key variables,focusing on their influence across different layer types and depths within LLM architectures.Our investigation uncovers several critical findings:(1)Larger layers,such as MLP layers,can maintain performance despite reductions in adapter rank,while smaller layers,like self-attention layers,aremore sensitive to such changes;(2)The effectiveness of balancing factors depends more on specific values rather than layer type or depth;(3)In quantization-aware fine-tuning,larger layers can effectively utilize smaller adapters,whereas smaller layers struggle to do so.These insights suggest that layer type is a more significant determinant of fine-tuning success than layer depth when optimizing quantized LLMs.Moreover,for the same discount of trainable parameters,reducing the trainable parameters in a larger layer is more effective in preserving fine-tuning accuracy than in a smaller one.This study provides valuable guidance for more efficient fine-tuning strategies and opens avenues for further research into optimizing LLM fine-tuning in resource-constrained environments.
基金Serbian Ministry of Education and Science through Mathematical Institute of Serbian Academy of Sciences and Arts(Project III44006)Serbian Ministry of Education and Science(Project TR32035)
文摘In this paper, the optimization of quantizer’s segment threshold is done. The quantizer is designed on the basis of approximative spline functions. Coefficients on which we form approximative spline functions are calculated by minimization mean square error (MSE). For coefficients determined in this way, spline functions by which optimal compressor function is approximated are obtained. For the quantizer designed on the basis of approximative spline functions, segment threshold is numerically determined depending on maximal value of the signal to quantization noise ratio (SQNR). Thus, quantizer with optimized segment threshold is achieved. It is shown that by quantizer model designed in this way and proposed in this paper, the SQNR that is very close to SQNR of nonlinear optimal companding quantizer is achieved.
基金supported by the National Natural Science Foundation of China(No.62201508)the Zhejiang Provincial Natural Science Foundation of China(Nos.LZ21F010001 and LQ23F010004)the State Key Laboratory of Millimeter Waves of Southeast University,China(No.K202212).
文摘Quantization noise caused by analog-to-digital converter(ADC)gives rise to the reliability performance degradation of communication systems.In this paper,a quantized non-Hermitian symmetry(NHS)orthogonal frequency-division multiplexing-based visible light communication(OFDM-VLC)system is presented.In order to analyze the effect of the resolution of ADC on NHS OFDM-VLC,a quantized mathematical model of NHS OFDM-VLC is established.Based on the proposed quantized model,a closed-form bit error rate(BER)expression is derived.The theoretical analysis and simulation results both confirm the effectiveness of the obtained BER formula in high-resolution ADC.In addition,channel coding is helpful in compensating for the BER performance loss due to the utilization of lower resolution ADC.
文摘The rapid growth of digital data necessitates advanced natural language processing(NLP)models like BERT(Bidi-rectional Encoder Representations from Transformers),known for its superior performance in text classification.However,BERT’s size and computational demands limit its practicality,especially in resource-constrained settings.This research compresses the BERT base model for Bengali emotion classification through knowledge distillation(KD),pruning,and quantization techniques.Despite Bengali being the sixth most spoken language globally,NLP research in this area is limited.Our approach addresses this gap by creating an efficient BERT-based model for Bengali text.We have explored 20 combinations for KD,quantization,and pruning,resulting in improved speedup,fewer parameters,and reduced memory size.Our best results demonstrate significant improvements in both speed and efficiency.For instance,in the case of mBERT,we achieved a 3.87×speedup and 4×compression ratio with a combination of Distil+Prune+Quant that reduced parameters from 178 to 46 M,while the memory size decreased from 711 to 178 MB.These results offer scalable solutions for NLP tasks in various languages and advance the field of model compression,making these models suitable for real-world applications in resource-limited environments.
文摘We consider a relativistic two-fluid model of superfluidity,in which the superfluid is described by an order parameter that is a complex scalar field satisfying the nonlinear Klein-Gordon equation(NLKG).The coupling to the normal fluid is introduced via a covariant current-current interaction,which results in the addition of an effective potential,whose imaginary part describes particle transfer between superfluid and normal fluid.Quantized vorticity arises in a class of singular solutions and the related vortex dynamics is incorporated in the modified NLKG,facilitating numerical analysis which is usually very complicated in the phenomenology of vortex filaments.The dual transformation to a string theory description(Kalb-Ramond)of quantum vorticity,the Magnus force,and the mutual friction between quantized vortices and normal fluid are also studied.
基金funded by National Science and Technology Council,grant number NSTC 113-2223-E-006-014.
文摘This study focuses on determining the second-order irregular wave loads in the time domain without using the Inverse Fast Fourier Transform(IFFT).Considering the substantial displacement effects that Floating Offshore Wind Turbine(FOWT)support structures undergo when subjected to wave loads,the time-domain wave method is more suitable,while the frequency-domain method requiring IFFT cannot be used for moving bodies.Nonetheless,the computational challenges posed by the considerable computer time requirements of the time-domain wave method remain a significant obstacle.Thus,the paper incorporates various numerical schemes,including parallel computing and extrapolation of wave forces during specific time steps to improve overall efficiency.Despite the effectiveness of these schemes,the computational difficulties associated with the time-domain wave method persist.This study then proposes an innovative approach utilizing different randomnumbers in distinct segments,significantly reducing the computation of second-order wave loads.This random number interpolation ensures a smooth curve transition between two segments,emphasizingminimizing errors near the end of the first segment.Numerical analyses demonstrate substantial decreases in total computer time for FOWT structural analyses while maintaining consistent steel design results.The proposed method is uncomplicated,requiring only a simple subprogram modification in a conventional wave load computer program.
基金supported by the National Natural Science Foundation of China(Nos.62276210,82201148 and 62376215)the Key Research and Development Project of Shaanxi Province(No.2025CY-YBXM-044)+3 种基金the Natural Science Foundation of Zhejiang Province(No.LQ22H120002)the Medical Health Science and Technology Project of Zhejiang Province(Nos.2022RC069 and 2023KY1140)the Natural Science Foundation of Ningbo(No.2023J390)the Ningbo Top Medical and Health Research Program(No.2023030716).
文摘This paper proposes a novel method for the automatic diagnosis of keratitis using feature vector quantization and self-attention mechanisms(ADK_FVQSAM).First,high-level features are extracted using the DenseNet121 backbone network,followed by adaptive average pooling to scale the features to a fixed length.Subsequently,product quantization with residuals(PQR)is applied to convert continuous feature vectors into discrete features representations,preserving essential information insensitive to image quality variations.The quantized and original features are concatenated and fed into a self-attention mechanism to capture keratitis-related features.Finally,these enhanced features are classified through a fully connected layer.Experiments on clinical low-quality(LQ)images show that ADK_FVQSAM achieves accuracies of 87.7%,81.9%,and 89.3% for keratitis,other corneal abnormalities,and normal corneas,respectively.Compared to DenseNet121,Swin transformer,and InceptionResNet,ADK_FVQSAM improves average accuracy by 3.1%,11.3%,and 15.3%,respectively.These results demonstrate that ADK_FVQSAM significantly enhances the recognition performance of keratitis based on LQ slit-lamp images,offering a practical approach for clinical application.
基金supported by the National Natural Science Foundation of China (Grant No. 40974039)High-Tech Research and Development Program of China (Grant No.2006AA06205)Leading Strategic Project of Science and Technology, Chinese Academy of Sciences (XDA08020500)
文摘Traditionally, airborne time-domain electromagnetic （ATEM） data are inverted to derive the earth model by iteration. However, the data are often highly correlated among channels and consequently cause ill-posed and over-determined problems in the inversion. The correlation complicates the mapping relation between the ATEM data and the earth parameters and thus increases the inversion complexity. To obviate this, we adopt principal component analysis to transform ATEM data into orthogonal principal components （PCs） to reduce the correlations and the data dimensionality and simultaneously suppress the unrelated noise. In this paper, we use an artificial neural network （ANN） to approach the PCs mapping relation with the earth model parameters, avoiding the calculation of Jacobian derivatives. The PC-based ANN algorithm is applied to synthetic data for layered models compared with data-based ANN for airborne time-domain electromagnetic inversion. The results demonstrate the PC-based ANN advantages of simpler network structure, less training steps, and better inversion results over data-based ANN, especially for contaminated data. Furthermore, the PC-based ANN algorithm effectiveness is examined by the inversion of the pseudo 2D model and comparison with data-based ANN and Zhody＇s methods. The results indicate that PC-based ANN inversion can achieve a better agreement with the true model and also proved that PC-based ANN is feasible to invert large ATEM datasets.
基金supported by Chinese National Programs for Fundamental Research and Development(No.2012CB416605)the National Natural Science Foundation of China(No.41174090)Development Project of National Key Scientific Equipment(No.ZDYZ2012-1-05-04)
文摘An electromagnetic field is generated through the accelerating movement of two equal but opposite charges of a single dipole. An electromagnetic field can also be generated by a time-varying infinitesimal point charge. In this study, a comparison between the electromagnetic fields of an infinitesimal point charge and a dipole has been presented. First, the time-domain potential function of a point source in a 3D conductive medium is derived. Then the electric and magnetic fields in a 3D homogeneous lossless space are derived via the relation between the potential and field. The field differences between the infinitesimal point charge and the dipole in the step-off time, far-source, and near-source zones are analyzed, and the accuracy of the solutions from these sources is investigated. It is also shown that the field of the infinitesimal point charge in the near-source zone is different from that of the dipole, whereas the far-source zone fields of these two sources are identical. The comparison of real and simulated data shows that the infinitesimal point charge represents the real source better than the divole source.
基金supported by the National High Technology Research and Development Program (863 Program)(2009AA06Z108)
文摘To effectively minimize the electromagnetic field response in the total field solution, we propose a numerical modeling method for the two-dimensional （2D） time- domain transient electromagnetic secondary field of the line source based on the DuFort- Frankel finite-difference method. In the proposed method, we included the treatment of the earth-air boundary conductivity, calculated the normalized partial derivative of the induced electromotive force （Emf）, and determined the forward time step. By extending upward the earth-air interface to the air grid nodes and the zero-value boundary conditions, not only we have a method that is more efficient but also simpler than the total field solution. We computed and analyzed the homogeneous half-space model and the fiat layered model with high precision--the maximum relative error is less than 0.01% between our method and the analytical method--and the solution speed is roughly three times faster than the total-field solution. Lastly, we used the model of a thin body embedded in a homogeneous half-space at different delay times to depict the downward and upward spreading characteristics of the induced eddy current, and the physical interaction processes between the electromagnetic field and the underground low-resistivity body.
基金The National Natural Science Foundation of China(No.60474049,60835001)Specialized Research Fund for Doctoral Program of Higher Education(No.20090092120027)
文摘In order to overcome data-quantization, networked-induced delay, network packet dropouts and wrong sequences in the nonlinear networked control system, a novel nonlinear networked control system model is built by the T-S fuzzy method. Two time-varying quantizers are added in the model. The key analysis steps in the method are to construct an improved interval-delay-dependent Lyapunov functional and to introduce the free-weighting matrix. By making use of the parallel distributed compensation technology and the convexity of the matrix function, the improved criteria of the stabilization and stability are obtained. Simulation experiments show that the parameters of the controllers and quantizers satisfying a certain performance can be obtained by solving a set of LMIs. The application of the nonlinear mass-spring system is provided to show that the proposed method is effective.
基金financially supported by National Nonprofit institute Research Grant of IGGE(Nos.AS2017J06,AS2017Y04,and AS2016J10)Survey on coastal area for airborne magnetic method of UNV in Jiangsu(No.DD20160151-03)+3 种基金Key National Research Project of China(No.2017YFC0601900)Key Program of National Natural Science Foundation of China(No.41530320)Natural Science Foundation(No.41274121)China Natural Science Foundation for Young Scientists(No.41404093)
文摘Electrically anisotropic strata are abundant in nature, so their study can help our data interpretation and our understanding of the processes of geodynamics. However, current data processing generally assumes isotropic conditions when surveying anisotropic structures, which may cause discrepancies between reality and electromagnetic data interpretation. Moreover, the anisotropic interpretation of the time-domain airborne electromagnetic （TDAEM） method is still confined to one dimensional （1D） cases, and the corresponding three-dimensional （3D） numerical simulations are still in development. In this study, we expanded the 3D TDAEM modeling of arbitrarily anisotropic media. First, through coordinate rotation of isotropic conductivity, we obtained the conductivity tensor of an arbitrary anisotropic rock. Next, we incorporated this into Maxwell＇s equations, using a regular hexahedral grid of vector finite elements to subdivide the solution area. A direct solver software package provided the solution for the sparse linear equations that resulted. Analytical solutions were used to verify the accuracy and feasibility of the algorithm. The proven model was then applied to analyze the effects of arbitrary anisotropy in 3D TDAEM via the distribution of responses and amplitude changes, which revealed that different anisotropy situations strongly affected the responses of TDAEM.
