Bar graphs are convenient for showing comparisons among items．The bars may be either horizontal or vertical,and they are used to show the amounts of different items．Figure 1 is an example of a typical bar graph．The...Bar graphs are convenient for showing comparisons among items．The bars may be either horizontal or vertical,and they are used to show the amounts of different items．Figure 1 is an example of a typical bar graph．The graph shows the average sales price of existing homes in the Northeast United States for three years——1970,1980,and 1997．展开更多
Magazines and newspapers often display information using circle,bar,and line graphs．The following examples illustrate how estimation techniques can be applied to each of these graphs． Circle graphs,also called pie c...Magazines and newspapers often display information using circle,bar,and line graphs．The following examples illustrate how estimation techniques can be applied to each of these graphs． Circle graphs,also called pie charts,show how a whole quantity is divided into parts．展开更多
For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data wi...For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data with artificial neural networks (ANN) could improve soil moisture estimation in various land cover types. To train and evaluate the model’s performance, we used field data (provided by La Tuscia University) on the study area collected during time periods between October 2022, and December 2022. Surface soil moisture was measured at 29 locations. The performance of the model was trained, validated, and tested using input features in a 60:10:30 ratio, using the feed-forward ANN model. It was found that the ANN model exhibited high precision in predicting soil moisture. The model achieved a coefficient of determination (R<sup>2</sup>) of 0.71 and correlation coefficient (R) of 0.84. Furthermore, the incorporation of Random Forest (RF) algorithms for soil moisture prediction resulted in an improved R<sup>2</sup> of 0.89. The unique combination of active microwave, meteorological data and multispectral data provides an opportunity to exploit the complementary nature of the datasets. Through preprocessing, fusion, and ANN modeling, this research contributes to advancing soil moisture estimation techniques and providing valuable insights for water resource management and agricultural planning in the study area.展开更多
GMS-5 satellite data at channels of infrared split windows and water vapor are analyzed to retrieve the precipitable water (PW) distributions under cloud-free conditions. Radiosonde data and surface station data are a...GMS-5 satellite data at channels of infrared split windows and water vapor are analyzed to retrieve the precipitable water (PW) distributions under cloud-free conditions. Radiosonde data and surface station data are applied to estimate the PW distributions under cloudy conditions. These two methods are then merged to obtain the PW distributions under all-weather conditions during the Huaihe River Basin Energy and Water Cycle Experiment (HUBEX). The results of the all-weather PW distributions from these methods demonstrate that this new merging technique may be applied to derive large-scale or global maps of PW. It is revealed that the atmospheric water vapor over the Yangtze-Huaihe River Basins came mainly from the southwest during the 1998 prevailing period of Meiyu. Sufficient atmospheric PW is a necessary condition for ground rainfall. Under certain dynamic conditions, it can be partially transformed into surface precipitation. Several types of rain are displayed and their PW conditions and characteristics, as well as atmospheric dynamic conditions, are analyzed. It is demonstrated that surface precipitation centers usually appear not at the high PW centers but on their downwind sides.展开更多
A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method ...A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.展开更多
A low-complexity method for direction of arrival（DOA） estimation based on estimation signal parameters via rotational invariance technique（ESPRIT） is proposed.Instead of using the cross-correlation vectors in mult...A low-complexity method for direction of arrival（DOA） estimation based on estimation signal parameters via rotational invariance technique（ESPRIT） is proposed.Instead of using the cross-correlation vectors in multistage Wiener filter（MSWF）,the orthogonal residual vectors obtained in conjugate gradient（CG） method span the signal subspace used by ESPRIT.The computational complexity of the proposed method is significantly reduced,since the signal subspace estimation mainly needs two matrixvector complex multiplications at the iteration of data level.Furthermore,the prior training data are not needed in the proposed method.To overcome performance degradation at low signal to noise ratio（SNR）,the expanded signal subspace spanned by more basis vectors is used and simultaneously renders ESPRIT yield redundant DOAs,which can be excluded by performing ESPRIT once more using the unexpanded signal subspace.Compared with the traditional ESPRIT methods by MSWF and eigenvalue decomposition（EVD）,numerical results demonstrate the satisfactory performance of the proposed method.展开更多
The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two rec...The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.展开更多
Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the re...Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the received signal to form data model with multi-invariance property,and multi-invariance ESPRIT algorithm for coherent DOA estimation is proposed in this paper.The proposed algorithm can resolve the DOAs of coherent signals and performs better in DOA estimation than that of ESPRIT-like algorithm.Meanwhile,it identifies more DOAs than ESPRIT-like algorithm.The simulation results demonstrate its validity.展开更多
A low-complexity angle estimation method for multiple-input multiple-output(MIMO) radar using beamspace unitary estimation of signal parameters via rotational invariance techniques(ESPRIT) is presented.Reduced-dimensi...A low-complexity angle estimation method for multiple-input multiple-output(MIMO) radar using beamspace unitary estimation of signal parameters via rotational invariance techniques(ESPRIT) is presented.Reduced-dimensional transformation is firstly utilized as a pre-processing to obtain the reduced-dimensional data matrix, and then a conjugate centrosymmetric discrete Fourier transform(DFT) matrix is employed to map the received data into lower-dimensional beamspace and transforms the complex covariance matrix into a realvalued one. At last, the rotational invariance structure of the real-valued signal subspace is constructed in the beamspace to obtain the estimation of direction of arrival(DOA). Compared with the other ESPRIT algorithms,the proposed method can achieve improved estimation performance with a significantly reduced computational complexity. Simulation results are presented to demonstrate the effectiveness of the proposed method.展开更多
This paper investigates the adaptive neural network(NN)event-triggered secure formation control problem for nonholonomic mobile robots(NMRs)subject to deception attacks.The NNs are employed to approximate unknown nonl...This paper investigates the adaptive neural network(NN)event-triggered secure formation control problem for nonholonomic mobile robots(NMRs)subject to deception attacks.The NNs are employed to approximate unknown nonlinear functions in robotic dynamics.Since the transmission channel from sensor-to-controller is vulnerable to deception attacks,a NN estimation technique is introduced to estimate the unknown deception attacks.In order to alleviate the amount of communication between controller-and-actuator,an event-triggered mechanism with relative threshold strategy is established.Then,an adaptive NN event-triggered secure formation control method is proposed.It is proved that all closed-loop signals of controlled systems are bounded and the formation tracking errors converge a neighborhood of the origin in the presence of deception attacks.The comparative simulations illustrate the effectiveness of the proposed secure formation control scheme.展开更多
Threshold voltage (V<sub>TH</sub>) is the most evocative aspect of MOSFET operation. It is the crucial device constraint to model on-off transition characteristics. Precise V<sub>TH</sub> value...Threshold voltage (V<sub>TH</sub>) is the most evocative aspect of MOSFET operation. It is the crucial device constraint to model on-off transition characteristics. Precise V<sub>TH</sub> value of the device is extracted and evaluated by several estimation techniques. However, these assessed values of V<sub>TH</sub> diverge from the exact values due to various short channel effects (SCEs) and non-idealities present in the device. Numerous prevalent V<sub>TH</sub> extraction methods are discussed. All the results are verified by extensive 2-D TCAD simulation and confirmed through analytical results at 10-nm technology node. Aim of this research paper is to explore and present a comparative study of largely applied threshold extraction methods for bulk driven nano-MOSFETs especially at 10-nm technology node along with various sub 45-nm technology nodes. Application of the threshold extraction methods to implement noise analysis is briefly presented to infer the most appropriate extraction method at nanometer technology nodes.展开更多
Deciphering hand motion intention from surface electromyography(sEMG)encounters challenges posed by the requisites of multiple degrees of freedom(DOFs)and adaptability.Unlike discrete action classification grounded in...Deciphering hand motion intention from surface electromyography(sEMG)encounters challenges posed by the requisites of multiple degrees of freedom(DOFs)and adaptability.Unlike discrete action classification grounded in pattern recognition,the pursuit of continuous kinematics estimation is appreciated for its inherent naturalness and intuitiveness.However,prevailing estimation techniques contend with accuracy limitations and substantial computational demands.Kalman estimation technology,celebrated for its ease of implementation and real-time adaptability,finds extensive application across diverse domains.This study introduces a continuous Kalman estimation method,leveraging a system model with sEMG and joint angles as inputs and outputs.Facilitated by model parameter training methods,the approach deduces multiple DOF finger kinematics simultaneously.The method’s efficacy is validated using a publicly accessible database,yielding a correlation coefficient(CC)of 0.73.With over 45,000 windows for training Kalman model parameters,the average computation time remains under 0.01 s.This pilot study amplifies its potential for further exploration and application within the realm of continuous finger motion estimation technology.展开更多
A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensor...A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method （ISM）, two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques （ESPRIT）, the direction-of-arrivals （DOAs） and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what＇s more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method.展开更多
The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction findin...The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the co- herent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method.展开更多
A decoupling-estimation signal parameters via rotarional invariance technique（ESPRIT） method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output（MIMO）...A decoupling-estimation signal parameters via rotarional invariance technique（ESPRIT） method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output（MIMO） radar.Two steps are carried out in this method.The decoupling operation between angle and mutual coupling estimates is realized by choosing the auxiliary elements on both sides of the transmit and receive uniform linear arrays（ULAs）.Then the ESPRIT method is resilient against the unknown mutual coupling matrix（MCM） and can be directly utilized to estimate the direction of departure（DOD） and the direction of arrival（DOA）.Moreover,the mutual coupling coefficient is estimated by finding the solution of the linear constrained optimization problem.The proposed method allows an efficient DOD and DOA estimates with automatic pairing.Simulation results are presented to verify the effectiveness of the proposed method.展开更多
The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization...The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.展开更多
A new edge tangential multi-energy soft x-ray（ME-SXR） diagnostic with high temporal（≤ 0.1 ms） and spatial（~1 cm） resolution has been developed for a variety of physics topics studies in the EAST tokamak plasma....A new edge tangential multi-energy soft x-ray（ME-SXR） diagnostic with high temporal（≤ 0.1 ms） and spatial（~1 cm） resolution has been developed for a variety of physics topics studies in the EAST tokamak plasma. The fast edge electron temperature profile（approximately from r a~ 0.6 to the scrape-off layer） is investigated using ME-SXR diagnostic system. The data process was performed by the ideal ‘multi-foil＇ technique, with no priori assumptions of plasma profiles. Reconstructed ME-SXR emissivity profiles for a variety of EAST experimental scenarios are presented here for the first time. The applications of the ME-SXR for study of the effects of resonant magnetic perturbation on edge localized modes and the first time neon radiating divertor experiment in EAST are also presented in this work. It has been found that neon impurity can suppress the 2/1 tearing mode and trigger a 3/1 MHD mode.展开更多
In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC ...In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC to extract the two-dimensional(2-D)angles of near-field signal in the Van-dermonde form,which allows for azimuth and elevation angle estimation by utilizing the improved estimation of signal para-meters via rotational invariance techniques(ESPRIT)algorithm.By substituting the calculated 2-D angles into the direction vec-tor of near-field signal,the range parameter can be conse-quently obtained by the 1-D multiple signal classification(MU-SIC)method.Simulations demonstrate that the proposed al-gorithm can achieve a single near-field signal localization,which can provide satisfactory performance and reduce computational complexity.展开更多
In this paper, Bayesian technique of direction finding based on two different priorities is described. Some useful formulas are deduced. The performance of the method and the influence of the priors on direction findi...In this paper, Bayesian technique of direction finding based on two different priorities is described. Some useful formulas are deduced. The performance of the method and the influence of the priors on direction finding are demonstrated by computer simulations.展开更多
文摘Bar graphs are convenient for showing comparisons among items．The bars may be either horizontal or vertical,and they are used to show the amounts of different items．Figure 1 is an example of a typical bar graph．The graph shows the average sales price of existing homes in the Northeast United States for three years——1970,1980,and 1997．
文摘Magazines and newspapers often display information using circle,bar,and line graphs．The following examples illustrate how estimation techniques can be applied to each of these graphs． Circle graphs,also called pie charts,show how a whole quantity is divided into parts．
文摘For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data with artificial neural networks (ANN) could improve soil moisture estimation in various land cover types. To train and evaluate the model’s performance, we used field data (provided by La Tuscia University) on the study area collected during time periods between October 2022, and December 2022. Surface soil moisture was measured at 29 locations. The performance of the model was trained, validated, and tested using input features in a 60:10:30 ratio, using the feed-forward ANN model. It was found that the ANN model exhibited high precision in predicting soil moisture. The model achieved a coefficient of determination (R<sup>2</sup>) of 0.71 and correlation coefficient (R) of 0.84. Furthermore, the incorporation of Random Forest (RF) algorithms for soil moisture prediction resulted in an improved R<sup>2</sup> of 0.89. The unique combination of active microwave, meteorological data and multispectral data provides an opportunity to exploit the complementary nature of the datasets. Through preprocessing, fusion, and ANN modeling, this research contributes to advancing soil moisture estimation techniques and providing valuable insights for water resource management and agricultural planning in the study area.
基金This work was supported by the National Natural Science Foundation of China under the Grant No. 49794030, the National Key Program of Science and Technology of China (2001BA610A-06-05), and the Science Foundation of the China Meteorological Administrat
文摘GMS-5 satellite data at channels of infrared split windows and water vapor are analyzed to retrieve the precipitable water (PW) distributions under cloud-free conditions. Radiosonde data and surface station data are applied to estimate the PW distributions under cloudy conditions. These two methods are then merged to obtain the PW distributions under all-weather conditions during the Huaihe River Basin Energy and Water Cycle Experiment (HUBEX). The results of the all-weather PW distributions from these methods demonstrate that this new merging technique may be applied to derive large-scale or global maps of PW. It is revealed that the atmospheric water vapor over the Yangtze-Huaihe River Basins came mainly from the southwest during the 1998 prevailing period of Meiyu. Sufficient atmospheric PW is a necessary condition for ground rainfall. Under certain dynamic conditions, it can be partially transformed into surface precipitation. Several types of rain are displayed and their PW conditions and characteristics, as well as atmospheric dynamic conditions, are analyzed. It is demonstrated that surface precipitation centers usually appear not at the high PW centers but on their downwind sides.
基金supported by the National Natural Science Foundation of China(61301211)and the Aviation Science Foundation(20131852028)
文摘A 2D-direction of arrival estimation (DOAE) for multi input and multi-output (MIMO) radar using improved multiple temporal-spatial subspaces in estimating signal parameters via rotational invariance techniques method (TS-ESPRIT) is introduced. In order to realize the improved TS-ESPRIT, the proposed algorithm divides the planar array into multiple uniform sub-planar arrays with common reference point to get a unified phase shifts measurement point for all sub-arrays. The TS-ESPRIT is applied to each sub-array separately, and in the same time with the others to realize the parallelly temporal and spatial processing, so that it reduces the non-linearity effect of model and decreases the computational time. Then, the time difference of arrival (TDOA) technique is applied to combine the multiple sub-arrays in order to form the improved TS-ESPRIT. It is found that the proposed method achieves high accuracy at a low signal to noise ratio (SNR) with low computational complexity, leading to enhancement of the estimators performance.
文摘A low-complexity method for direction of arrival（DOA） estimation based on estimation signal parameters via rotational invariance technique（ESPRIT） is proposed.Instead of using the cross-correlation vectors in multistage Wiener filter（MSWF）,the orthogonal residual vectors obtained in conjugate gradient（CG） method span the signal subspace used by ESPRIT.The computational complexity of the proposed method is significantly reduced,since the signal subspace estimation mainly needs two matrixvector complex multiplications at the iteration of data level.Furthermore,the prior training data are not needed in the proposed method.To overcome performance degradation at low signal to noise ratio（SNR）,the expanded signal subspace spanned by more basis vectors is used and simultaneously renders ESPRIT yield redundant DOAs,which can be excluded by performing ESPRIT once more using the unexpanded signal subspace.Compared with the traditional ESPRIT methods by MSWF and eigenvalue decomposition（EVD）,numerical results demonstrate the satisfactory performance of the proposed method.
基金Projects 60372081, 30170259 and 30570475 supported by the National Natural Science Foundation of China, VSN-2005-01 the Opened Foundation of National Key-Lab of Vibration, Impact and Noise, 80523+1 种基金the Science Foundation of Hainan Province and Hj200501 the Foundation of Education Department of Hainan Province
文摘The non-Gaussian α-stable distribution is introduced to model impulsive noise. Based on the theory of fractional lower order statistics (FLOS), the fractional lower order cross-covariance (FLOCC) sequence for two received signals is obtained and the fractional lower order cross-covariance spectrum (FLOCCS) can be approached by taking a Fourier transform for the FLOCC sequence. When the FLOCCS is treated as a sequence in the time domain, the problem of multipath time delay estimation (TDE) may be converted into one on multi-frequencies estimation or directions of arrival estimation. Accordingly, the high resolution multipath TDE can be realized with the ESPRIT technology. This idea on multipath TDE is referred to as FLOCCS-ESPRIT in this paper. Computer simulations show that this method has good performance both in a Gaussian noise and in an impulsive noise environment.
基金Supported by the National Natural Science Foundation of China (No.60801052)Aeronautical Science Foundation of China (No.2008ZC52026,2009ZC52036)
文摘Estimation of Signal Parameters via Rotational Invariance Technique(ESPRIT) algorithm can estimate Direction-Of-Arrival(DOA) of coherent signal,but its performance can not reach full satisfaction.We reconstruct the received signal to form data model with multi-invariance property,and multi-invariance ESPRIT algorithm for coherent DOA estimation is proposed in this paper.The proposed algorithm can resolve the DOAs of coherent signals and performs better in DOA estimation than that of ESPRIT-like algorithm.Meanwhile,it identifies more DOAs than ESPRIT-like algorithm.The simulation results demonstrate its validity.
基金the National Natural Science Foundation of China(No.61602377)
文摘A low-complexity angle estimation method for multiple-input multiple-output(MIMO) radar using beamspace unitary estimation of signal parameters via rotational invariance techniques(ESPRIT) is presented.Reduced-dimensional transformation is firstly utilized as a pre-processing to obtain the reduced-dimensional data matrix, and then a conjugate centrosymmetric discrete Fourier transform(DFT) matrix is employed to map the received data into lower-dimensional beamspace and transforms the complex covariance matrix into a realvalued one. At last, the rotational invariance structure of the real-valued signal subspace is constructed in the beamspace to obtain the estimation of direction of arrival(DOA). Compared with the other ESPRIT algorithms,the proposed method can achieve improved estimation performance with a significantly reduced computational complexity. Simulation results are presented to demonstrate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China under 62173172.
文摘This paper investigates the adaptive neural network(NN)event-triggered secure formation control problem for nonholonomic mobile robots(NMRs)subject to deception attacks.The NNs are employed to approximate unknown nonlinear functions in robotic dynamics.Since the transmission channel from sensor-to-controller is vulnerable to deception attacks,a NN estimation technique is introduced to estimate the unknown deception attacks.In order to alleviate the amount of communication between controller-and-actuator,an event-triggered mechanism with relative threshold strategy is established.Then,an adaptive NN event-triggered secure formation control method is proposed.It is proved that all closed-loop signals of controlled systems are bounded and the formation tracking errors converge a neighborhood of the origin in the presence of deception attacks.The comparative simulations illustrate the effectiveness of the proposed secure formation control scheme.
文摘Threshold voltage (V<sub>TH</sub>) is the most evocative aspect of MOSFET operation. It is the crucial device constraint to model on-off transition characteristics. Precise V<sub>TH</sub> value of the device is extracted and evaluated by several estimation techniques. However, these assessed values of V<sub>TH</sub> diverge from the exact values due to various short channel effects (SCEs) and non-idealities present in the device. Numerous prevalent V<sub>TH</sub> extraction methods are discussed. All the results are verified by extensive 2-D TCAD simulation and confirmed through analytical results at 10-nm technology node. Aim of this research paper is to explore and present a comparative study of largely applied threshold extraction methods for bulk driven nano-MOSFETs especially at 10-nm technology node along with various sub 45-nm technology nodes. Application of the threshold extraction methods to implement noise analysis is briefly presented to infer the most appropriate extraction method at nanometer technology nodes.
基金supported in part by the National Key R&D Program of China(#2020YFC2007900)the National Natural Science Foundation of China(#82161160341,#62271477,and #61901464)+2 种基金the Science and Technology Program of Guangdong Province(#2022A0505090007)“The Belt and Road”Innovative Talent Exchange program for foreign experts(DL2022024002L)Jinan 5150 Program for Talents Introduction.
文摘Deciphering hand motion intention from surface electromyography(sEMG)encounters challenges posed by the requisites of multiple degrees of freedom(DOFs)and adaptability.Unlike discrete action classification grounded in pattern recognition,the pursuit of continuous kinematics estimation is appreciated for its inherent naturalness and intuitiveness.However,prevailing estimation techniques contend with accuracy limitations and substantial computational demands.Kalman estimation technology,celebrated for its ease of implementation and real-time adaptability,finds extensive application across diverse domains.This study introduces a continuous Kalman estimation method,leveraging a system model with sEMG and joint angles as inputs and outputs.Facilitated by model parameter training methods,the approach deduces multiple DOF finger kinematics simultaneously.The method’s efficacy is validated using a publicly accessible database,yielding a correlation coefficient(CC)of 0.73.With over 45,000 windows for training Kalman model parameters,the average computation time remains under 0.01 s.This pilot study amplifies its potential for further exploration and application within the realm of continuous finger motion estimation technology.
文摘A new method for array calibration of array gain and phase uncertainties, which severely degrade the performance of spatial spectrum estimation, is presented. The method is based on the idea of the instrumental sensors method （ISM）, two well-calibrated sensors are added into the original array. By applying the principle of estimation of signal parameters via rotational invariance techniques （ESPRIT）, the direction-of-arrivals （DOAs） and uncertainties can be estimated simultaneously through eigen-decomposition. Compared with the conventional ones, this new method has less computational complexity while has higher estimation precision, what＇s more, it can overcome the problem of ambiguity. Both theoretical analysis and computer simulations show the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China (61102106)the Fundamental Research Funds for the Central Universities (HEUCF1208 HEUCF100801)
文摘The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the co- herent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method.
基金supported by the National Natural Science Foundation of China (60702015)
文摘A decoupling-estimation signal parameters via rotarional invariance technique（ESPRIT） method is presented for multi-target localization with unknown mutual coupling in bistatic multiple-input multiple-output（MIMO） radar.Two steps are carried out in this method.The decoupling operation between angle and mutual coupling estimates is realized by choosing the auxiliary elements on both sides of the transmit and receive uniform linear arrays（ULAs）.Then the ESPRIT method is resilient against the unknown mutual coupling matrix（MCM） and can be directly utilized to estimate the direction of departure（DOD） and the direction of arrival（DOA）.Moreover,the mutual coupling coefficient is estimated by finding the solution of the linear constrained optimization problem.The proposed method allows an efficient DOD and DOA estimates with automatic pairing.Simulation results are presented to verify the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(11234002)
文摘The signal to noise ratio （SNR） of seismic waves is usually very low after long distance transmission. For this condition, to improve the bearing estimation capability in the low SNR, a frequency domain polarization weighted ESPRIT method using a single vector device is proposed. The frequency domain polari- zation parameters extracted from the signals are used to design the weighted function which is applied to the received signals. The bearing angle and the target frequency are estimated through ESPRIT using the weighted signals. The simulation and experiment results show that the presented method can obtain accurate estimation values under the low SNR with little prior information.
基金supported by National Magnetic Confinement Fusion Science Program of China under Contracts Nos.2015GB101000,2013GB106000,and 2013GB107000National Natural Science Foundation of China under Contracts Nos.11575235,11422546 and 11505222Youth Foundation of ASIPP under Grant No.Y45ETY2306
文摘A new edge tangential multi-energy soft x-ray（ME-SXR） diagnostic with high temporal（≤ 0.1 ms） and spatial（~1 cm） resolution has been developed for a variety of physics topics studies in the EAST tokamak plasma. The fast edge electron temperature profile（approximately from r a~ 0.6 to the scrape-off layer） is investigated using ME-SXR diagnostic system. The data process was performed by the ideal ‘multi-foil＇ technique, with no priori assumptions of plasma profiles. Reconstructed ME-SXR emissivity profiles for a variety of EAST experimental scenarios are presented here for the first time. The applications of the ME-SXR for study of the effects of resonant magnetic perturbation on edge localized modes and the first time neon radiating divertor experiment in EAST are also presented in this work. It has been found that neon impurity can suppress the 2/1 tearing mode and trigger a 3/1 MHD mode.
基金supported by the National Natural Science Foundation of China(6192100162022091)the Natural Science Foundation of Hunan Province(2017JJ3368).
文摘In this paper,we propose a beam space coversion(BSC)-based approach to achieve a single near-field signal local-ization under uniform circular array(UCA).By employing the centro-symmetric geometry of UCA,we apply BSC to extract the two-dimensional(2-D)angles of near-field signal in the Van-dermonde form,which allows for azimuth and elevation angle estimation by utilizing the improved estimation of signal para-meters via rotational invariance techniques(ESPRIT)algorithm.By substituting the calculated 2-D angles into the direction vec-tor of near-field signal,the range parameter can be conse-quently obtained by the 1-D multiple signal classification(MU-SIC)method.Simulations demonstrate that the proposed al-gorithm can achieve a single near-field signal localization,which can provide satisfactory performance and reduce computational complexity.
文摘In this paper, Bayesian technique of direction finding based on two different priorities is described. Some useful formulas are deduced. The performance of the method and the influence of the priors on direction finding are demonstrated by computer simulations.
