The bimodulus material is a classical model to describe the elastic behavior of materials with tension-compression asymmetry.Due to the inherently nonlinear properties of bimodular materials,traditional iteration meth...The bimodulus material is a classical model to describe the elastic behavior of materials with tension-compression asymmetry.Due to the inherently nonlinear properties of bimodular materials,traditional iteration methods suffer from low convergence efficiency and poor adaptability for large-scale structures in engineering.In this paper,a novel 3D algorithm is established by complementing the three shear moduli of the constitutive equation in principal stress coordinates.In contrast to the existing 3D shear modulus constructed based on experience,in this paper the shear modulus is derived theoretically through a limit process.Then,a theoretically self-consistent complemented algorithm is established and implemented in ABAQUS via UMAT;its good stability and convergence efficiency are verified by using benchmark examples.Numerical analysis shows that the calculation error for bimodulus structures using the traditional linear elastic theory is large,which is not in line with reality.展开更多
This paper investigates adaptive blind source separation and equalization for Multiple Input Multiple Output (MIMO) systems. To effectively recover input signals, remove Inter-Symbol Interference (ISI) and suppress In...This paper investigates adaptive blind source separation and equalization for Multiple Input Multiple Output (MIMO) systems. To effectively recover input signals, remove Inter-Symbol Interference (ISI) and suppress Inter-User Interference (IUI), the array input is first transformed into the signal subspace, then with the derived orthogonality between weight vectors of different input signals, a new orthogonal Constant Modulus Algorithm (CMA) is proposed. Computer simulation results illustrate the promising performance of the proposed method. Without channel identification, the proposed method can recover all the system inputs simultaneously and can be adaptive to channel changes without prior knowledge about signals.展开更多
The algorithmic tangent modulus at finite strains in current configuration plays an important role in the nonlinear finite element method. In this work, the exact tensorial forms of the algorithmic tangent modulus at ...The algorithmic tangent modulus at finite strains in current configuration plays an important role in the nonlinear finite element method. In this work, the exact tensorial forms of the algorithmic tangent modulus at finite strains are derived in the principal space and their corresponding matrix expressions are also presented. The algorithmic tangent modulus consists of two terms. The first term depends on a specific yield surface, while the second term is independent of the specific yield surface. The elastoplastic matrix in the principal space associated with the specific yield surface is derived by the logarithmic strains in terms of the local multiplicative decomposition. The Drucker-Prager yield function of elastoplastic material is used as a numerical example to verify the present algorithmic tangent modulus at finite strains.展开更多
Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm (WL-UKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the con...Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm (WL-UKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the constant modulus criterion and takes full advantage of the noncircular property of the signal of interest (SOI), significantly increasing the output signal-to interference-plus-noise ratio (SINR), enhancing the convergence speed and decreasing the steady-state misadjustment. Since it requires no known training data, the proposed algorithm saves a large amount of the available spectrum. Theoretical analysis and simulation results are presented to demonstrate its superiority over the conventional linear least mean square-based CMA (L-LMS-CMA), the conventional linear recursive least square-based CMA (L-RLS-CMA), WL-LMS-CMA, WL-RLS-CMA and L-UKF-CMA.展开更多
Subgrade reaction modulus (Ks) is one of the main factors in evaluating engineering properties of soils for structural calculations and operations. So, many studies have been performed on the effect of other soil geot...Subgrade reaction modulus (Ks) is one of the main factors in evaluating engineering properties of soils for structural calculations and operations. So, many studies have been performed on the effect of other soil geotechnical parameters on it. One is the effect of soil grains shape on engineering properties of soils, especially Ks. The aim of the present research is to evaluate the effect of soil grains shape on Ks for coarse-grained soils of the west of Mashhad, Iran. For this purpose, 20 PLTs were performed on coarse-grained soils of the west of Mashhad and Ks amounts were determined. Then, flakiness and elongation of the samples measured and changes of Ks by soil grain shape were evaluated. The results showed the strength dependency of Ks to grain forms which an increase in flakiness and elongation indices leads to a decrease in Ks. Therefore, it is necessary to reduce Ks estimated form empirical relationships for flaky and elongated soils. So, by writing a genetic algorithm-based program to find the optimal relationship between the grain shape and the subgrade reaction coefficient, a valid equation for correcting the results from previous empirical equations was presented.展开更多
Blind Adaptive Step-size Constant Modulus Algorithm (AS-CMA) for multiuser detection in DS-CDMA systems is presented. It combines the CMA and the concept of variable step-size, uses a second LMS algorithm for the step...Blind Adaptive Step-size Constant Modulus Algorithm (AS-CMA) for multiuser detection in DS-CDMA systems is presented. It combines the CMA and the concept of variable step-size, uses a second LMS algorithm for the step size. It adjusts the step-size according to the minimum output-energy principle within a specified range, thus overcomes the problems of bad effect of fixed step-size LMS algorithm. Compared with Adaptive Step-size LMS (AS-LMS) algoritilrn, through simulations, this algorithm can adapt the changes of the environment, suppress multiple access interference in the dynamic environment and the stability of Signal to Interference Ratio (SIR) is superior to that of AS-LMS.展开更多
This study introduces and evaluates a novel artificial hummingbird algorithm-optimised boosted tree(AHAboosted)model for predicting the dynamic modulus(E*)of hot mix asphalt concrete.Using a substantial dataset from N...This study introduces and evaluates a novel artificial hummingbird algorithm-optimised boosted tree(AHAboosted)model for predicting the dynamic modulus(E*)of hot mix asphalt concrete.Using a substantial dataset from NCHRP Report-547,the model was trained and rigorously tested.Performance metrics,specifically RMSE,MAE,and R2,were employed to assess the model's predictive accuracy,robustness,and generalisability.When benchmarked against well-established models like support vector machines(SVM)and gaussian process regression(GPR),the AHA-boosted model demonstrated enhanced performance.It achieved R2 values of 0.997 in training and 0.974 in testing,using the traditional Witczak NCHRP 1-40D model inputs.Incorporating features such as test temperature,frequency,and asphalt content led to a 1.23%increase in the test R2,signifying an improvement in the model's accuracy.The study also explored feature importance and sensitivity through SHAP and permutation importance plots,highlighting binder complex modulus|G*|as a key predictor.Although the AHA-boosted model shows promise,a slight decrease in R2 from training to testing indicates a need for further validation.Overall,this study confirms the AHA-boosted model as a highly accurate and robust tool for predicting the dynamic modulus of hot mix asphalt concrete,making it a valuable asset for pavement engineering.展开更多
The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soil...The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.展开更多
The compression modulus(Es)is one of the most significant soil parameters that affects the compressive deformation of geotechnical systems,such as foundations.However,it is difficult and sometime costly to obtain this...The compression modulus(Es)is one of the most significant soil parameters that affects the compressive deformation of geotechnical systems,such as foundations.However,it is difficult and sometime costly to obtain this parameter in engineering practice.In this study,we aimed to develop a non-parametric ensemble artificial intelligence(AI)approach to calculate the Es of soft clay in contrast to the traditional regression models proposed in previous studies.A gradient boosted regression tree(GBRT)algorithm was used to discern the non-linear pattern between input variables and the target response,while a genetic algorithm(GA)was adopted for tuning the GBRT model's hyper-parameters.The model was tested through 10-fold cross validation.A dataset of 221 samples from 65 engineering survey reports from Shanghai infrastructure projects was constructed to evaluate the accuracy of the new model5 s predictions.The mean squared error and correlation coefficient of the optimum GBRT model applied to the testing set were 0.13 and 0.91,respectively,indicating that the proposed machine learning(ML)model has great potential to improve the prediction of Es for soft clay.A comparison of the performance of empirical formulas and the proposed ML method for predicting foundation settlement indicated the rationality of the proposed ML model and its applicability to the compressive deformation of geotechnical systems.This model,however,cannot be directly applied to the prediction of Es in other sites due to its site specificity.This problem can be solved by retraining the model using local data.This study provides a useful reference for future multi-parameter prediction of soil behavior.展开更多
A new mulfitarget constant modulus array is proposed for CDMA systems based on least squares constant modulus algorithm. The new algorithm is called pre-despreading decision directed least squares constant modulus alg...A new mulfitarget constant modulus array is proposed for CDMA systems based on least squares constant modulus algorithm. The new algorithm is called pre-despreading decision directed least squares constant modulus algorithm （D-DDLSCMA）. In the new algorithm, the pre-despreading is first applied for multitarget arrays to remove some multiple access signals, then the despreaded signal is processed by the algorithm which united the constant modulus algorithm and decision directed method. Simulation results illustrate the good performance for the proposed algorithm.展开更多
A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output （MIMO） induced and spacedivision multiple-access based wireless systems that employ high order phase shift keying signaling. A mi...A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output （MIMO） induced and spacedivision multiple-access based wireless systems that employ high order phase shift keying signaling. A minimum number of training symbols, very close to the number of receiver antenna elements, are used to provide a rough initial least squares estimate of the beamformer＇s weight vector. A novel cost function combining the constant modulus criterion with decision-directed adaptation is adopted to adapt the beamformer weight vector. This cost function can be approximated as a quadratic form with a closed-form solution, based on which we then derive the recursive least squares （RLS） semi-blind adaptive beamforming algorithm. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study. Our proposed semi-blind RLS beamforming algorithm therefore provides an efficient detection scheme for the future generation of MIMO aided mobile communication systems.展开更多
This paper proposes a new multitarget constant modulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant mod...This paper proposes a new multitarget constant modulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant modulus algorithm (D-WD-CMA). In the new algorithm, the pre-despreading is applied to multitarget arrays to remove some multiple access inter- ferences. After that the received signal is subjected to wavelet de-noising to reduce some noise, and used in CMA adaptive iteration for signal separation. Simulation results showed that the proposed algorithm performed better than the traditional CMA algorithm.展开更多
This paper considers three algorithms for the extraction of square roots of complex integers {called Gaussians} using arithmetic based on complex modulus p + iq. These algorithms are almost twice as fast as the analog...This paper considers three algorithms for the extraction of square roots of complex integers {called Gaussians} using arithmetic based on complex modulus p + iq. These algorithms are almost twice as fast as the analogous algorithms extracting square roots of either real or complex integers in arithmetic based on modulus p, where is a real prime. A cryptographic system based on these algorithms is provided in this paper. A procedure reducing the computational complexity is described as well. Main results are explained in several numeric illustrations.展开更多
A new blind equalization algorithm based on the modified constant modulus algorithm （MCMA） and dithered signederror constant modulus algorithm （DSE-CMA） is proposed. This dithered signed-error MCMA （DSE-MCMA） ca...A new blind equalization algorithm based on the modified constant modulus algorithm （MCMA） and dithered signederror constant modulus algorithm （DSE-CMA） is proposed. This dithered signed-error MCMA （DSE-MCMA） can not only reduce the computational complexity, but also recover the phase rotation in the complex channel. Simulation results have verified the analysis and indicated the good property of DSE-MCMA.展开更多
Shor proposed a polynomial time algorithm for computing the order of one element in a multiplicative group using a quantum computer. Based on Miller’s randomization, he then gave a factorization algorithm. But the al...Shor proposed a polynomial time algorithm for computing the order of one element in a multiplicative group using a quantum computer. Based on Miller’s randomization, he then gave a factorization algorithm. But the algorithm has two shortcomings, the order must be even and the output might be a trivial factor. Actually, these drawbacks can be overcome if the number is an RSA modulus. Applying the special structure of the RSA modulus, an algorithm is presented to overcome the two shortcomings. The new algorithm improves Shor’s algorithm for factoring RSA modulus. The cost of the factorization algorithm almost depends on the calculation of the order of 2 in the multiplication group.展开更多
A novel Least Squares Constant Modulus (LSCM) beam-forming algorithm in smart antenna Multi-Carrier Code Division Multiple Access (MC-CDMA) system is proposed in this paper. It adaptively beam-forms the multi-carrier ...A novel Least Squares Constant Modulus (LSCM) beam-forming algorithm in smart antenna Multi-Carrier Code Division Multiple Access (MC-CDMA) system is proposed in this paper. It adaptively beam-forms the multi-carrier antenna array signal using the LSCM Algorithm (LSCMA), and in the meantime, the beam-formed signals on every sub-carrier are combined by using Orthogonal Restore Combination (ORC), Equal Gain Combination (EGC) or Maximum Ratio Combination (MRC). Then the decision of the combined signals and the spread-code of the expected user are used to re-construct the signals on every sub-carrier. At last, the difference between the re-constructed signal and the output signal of the beam-former is used to con-trol the coefficients of the beam-former. The bit error probability of the proposed algorithm is analyzed. We simulated and compared it with the conventional LSCM beam-forming algorithm. Simulation results show that the proposed algorithm is superior to the latter in Bit Error Rate (BER).展开更多
This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decompositio...This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decomposition of the channel received complex baseband signals and proposes a new two-stage blind algorithm. Exploited the second-order cyclostationarity inherent in OFDM with cyclic prefix and the characteristics of the phased antenna, the practical HIPERLAN/2 standard based OFDM-MIMO simulator is established with the sufficient consideration of statistical correlations between the multiple antenna channels under wireless wideband multipath fading environment, and a new two-stage blind algorithm is formulated using rank reduced subspace channel matrix approximation and adaptive Constant Modulus (CM)criterion. Simulation results confirm the theoretical analysis and illustrate that the proposed algorithm is capable of tracking matrix channel variations with fast convergence rate and improving acceptable overall system performance over various common wireless and mobile communication links.展开更多
Two blind multiuser detection algorithms for antenna array in Code Division Multiple Access （CDMA） system which apply the linearly constrained condition to the Least Squares Constant Modulus Algorithln （LSCMA） are...Two blind multiuser detection algorithms for antenna array in Code Division Multiple Access （CDMA） system which apply the linearly constrained condition to the Least Squares Constant Modulus Algorithln （LSCMA） are proposed in this paper. One is the Linearly Constrained LSCMA （LC-LSCMA）, the other is the Preprocessing LC-LSCMA （PLC-LSCMA）. The two algorithms are compared with the conventional LSCMA. The results show that the two algorithms proposed in this paper are superior to the conventional LSCMA and the best one is PLC-LSCMA.展开更多
基金the National Natural Science Foundation of China(Grant 51908071)Scientific Research Project of Education Department of Hunan Province(Grant 18C0194)Open Fund of Key Laboratory of Road Structure and Material of Ministry of Transport,Changsha University of Science&Technology(Grant kfi 170303).
文摘The bimodulus material is a classical model to describe the elastic behavior of materials with tension-compression asymmetry.Due to the inherently nonlinear properties of bimodular materials,traditional iteration methods suffer from low convergence efficiency and poor adaptability for large-scale structures in engineering.In this paper,a novel 3D algorithm is established by complementing the three shear moduli of the constitutive equation in principal stress coordinates.In contrast to the existing 3D shear modulus constructed based on experience,in this paper the shear modulus is derived theoretically through a limit process.Then,a theoretically self-consistent complemented algorithm is established and implemented in ABAQUS via UMAT;its good stability and convergence efficiency are verified by using benchmark examples.Numerical analysis shows that the calculation error for bimodulus structures using the traditional linear elastic theory is large,which is not in line with reality.
文摘This paper investigates adaptive blind source separation and equalization for Multiple Input Multiple Output (MIMO) systems. To effectively recover input signals, remove Inter-Symbol Interference (ISI) and suppress Inter-User Interference (IUI), the array input is first transformed into the signal subspace, then with the derived orthogonality between weight vectors of different input signals, a new orthogonal Constant Modulus Algorithm (CMA) is proposed. Computer simulation results illustrate the promising performance of the proposed method. Without channel identification, the proposed method can recover all the system inputs simultaneously and can be adaptive to channel changes without prior knowledge about signals.
基金Project supported by the National Natural Science Foundation of China(Nos.41172116,U1261212,and 51134005)
文摘The algorithmic tangent modulus at finite strains in current configuration plays an important role in the nonlinear finite element method. In this work, the exact tensorial forms of the algorithmic tangent modulus at finite strains are derived in the principal space and their corresponding matrix expressions are also presented. The algorithmic tangent modulus consists of two terms. The first term depends on a specific yield surface, while the second term is independent of the specific yield surface. The elastoplastic matrix in the principal space associated with the specific yield surface is derived by the logarithmic strains in terms of the local multiplicative decomposition. The Drucker-Prager yield function of elastoplastic material is used as a numerical example to verify the present algorithmic tangent modulus at finite strains.
基金supported by the National Natural Science Foundation of China(61573113)the Harbin Science and Technology Innovation Talents(Excellent Discipline Leader)Research Fund(2014RFXXJ074)the National Scholarship([2016]3100)
文摘Based on a uniform linear array, a new widely linear unscented Kalman filter-based constant modulus algorithm (WL-UKF-CMA) for blind adaptive beamforming is proposed. The new algorithm is designed according to the constant modulus criterion and takes full advantage of the noncircular property of the signal of interest (SOI), significantly increasing the output signal-to interference-plus-noise ratio (SINR), enhancing the convergence speed and decreasing the steady-state misadjustment. Since it requires no known training data, the proposed algorithm saves a large amount of the available spectrum. Theoretical analysis and simulation results are presented to demonstrate its superiority over the conventional linear least mean square-based CMA (L-LMS-CMA), the conventional linear recursive least square-based CMA (L-RLS-CMA), WL-LMS-CMA, WL-RLS-CMA and L-UKF-CMA.
文摘Subgrade reaction modulus (Ks) is one of the main factors in evaluating engineering properties of soils for structural calculations and operations. So, many studies have been performed on the effect of other soil geotechnical parameters on it. One is the effect of soil grains shape on engineering properties of soils, especially Ks. The aim of the present research is to evaluate the effect of soil grains shape on Ks for coarse-grained soils of the west of Mashhad, Iran. For this purpose, 20 PLTs were performed on coarse-grained soils of the west of Mashhad and Ks amounts were determined. Then, flakiness and elongation of the samples measured and changes of Ks by soil grain shape were evaluated. The results showed the strength dependency of Ks to grain forms which an increase in flakiness and elongation indices leads to a decrease in Ks. Therefore, it is necessary to reduce Ks estimated form empirical relationships for flaky and elongated soils. So, by writing a genetic algorithm-based program to find the optimal relationship between the grain shape and the subgrade reaction coefficient, a valid equation for correcting the results from previous empirical equations was presented.
基金Supported by the National Natural Science Fundation of China(No.60172018)
文摘Blind Adaptive Step-size Constant Modulus Algorithm (AS-CMA) for multiuser detection in DS-CDMA systems is presented. It combines the CMA and the concept of variable step-size, uses a second LMS algorithm for the step size. It adjusts the step-size according to the minimum output-energy principle within a specified range, thus overcomes the problems of bad effect of fixed step-size LMS algorithm. Compared with Adaptive Step-size LMS (AS-LMS) algoritilrn, through simulations, this algorithm can adapt the changes of the environment, suppress multiple access interference in the dynamic environment and the stability of Signal to Interference Ratio (SIR) is superior to that of AS-LMS.
文摘This study introduces and evaluates a novel artificial hummingbird algorithm-optimised boosted tree(AHAboosted)model for predicting the dynamic modulus(E*)of hot mix asphalt concrete.Using a substantial dataset from NCHRP Report-547,the model was trained and rigorously tested.Performance metrics,specifically RMSE,MAE,and R2,were employed to assess the model's predictive accuracy,robustness,and generalisability.When benchmarked against well-established models like support vector machines(SVM)and gaussian process regression(GPR),the AHA-boosted model demonstrated enhanced performance.It achieved R2 values of 0.997 in training and 0.974 in testing,using the traditional Witczak NCHRP 1-40D model inputs.Incorporating features such as test temperature,frequency,and asphalt content led to a 1.23%increase in the test R2,signifying an improvement in the model's accuracy.The study also explored feature importance and sensitivity through SHAP and permutation importance plots,highlighting binder complex modulus|G*|as a key predictor.Although the AHA-boosted model shows promise,a slight decrease in R2 from training to testing indicates a need for further validation.Overall,this study confirms the AHA-boosted model as a highly accurate and robust tool for predicting the dynamic modulus of hot mix asphalt concrete,making it a valuable asset for pavement engineering.
基金Project(51878078)supported by the National Natural Science Foundation of ChinaProject(2018-025)supported by the Training Program for High-level Technical Personnel in Transportation Industry,ChinaProject(CTKY-PTRC-2018-003)supported by the Design Theory,Method and Demonstration of Durability Asphalt Pavement Based on Heavy-duty Traffic Conditions in Shanghai Area,China。
文摘The resilient modulus(MR)of subgrade soils is usually used to characterize the stiffness of subgrade and is a crucial parameter in pavement design.In order to determine the resilient modulus of compacted subgrade soils quickly and accurately,an optimized artificial neural network(ANN)approach based on the multi-population genetic algorithm(MPGA)was proposed in this study.The MPGA overcomes the problems of the traditional ANN such as low efficiency,local optimum and over-fitting.The developed optimized ANN method consists of ten input variables,twenty-one hidden neurons,and one output variable.The physical properties(liquid limit,plastic limit,plasticity index,0.075 mm passing percentage,maximum dry density,optimum moisture content),state variables(degree of compaction,moisture content)and stress variables(confining pressure,deviatoric stress)of subgrade soils were selected as input variables.The MR was directly used as the output variable.Then,adopting a large amount of experimental data from existing literature,the developed optimized ANN method was compared with the existing representative estimation methods.The results show that the developed optimized ANN method has the advantages of fast speed,strong generalization ability and good accuracy in MR estimation.
基金the National Natural Science Foundation of China(Nos.51608380 and 51538009)the Key Innovation Team Program of the Innovation Talents Promotion Plan by Ministry of Science and Technology of China(No.2016RA4059)the Specific Consultant Research Project of Shanghai Tunnel Engineering Company Ltd.(No.STEC/KJB/XMGL/0130),China。
文摘The compression modulus(Es)is one of the most significant soil parameters that affects the compressive deformation of geotechnical systems,such as foundations.However,it is difficult and sometime costly to obtain this parameter in engineering practice.In this study,we aimed to develop a non-parametric ensemble artificial intelligence(AI)approach to calculate the Es of soft clay in contrast to the traditional regression models proposed in previous studies.A gradient boosted regression tree(GBRT)algorithm was used to discern the non-linear pattern between input variables and the target response,while a genetic algorithm(GA)was adopted for tuning the GBRT model's hyper-parameters.The model was tested through 10-fold cross validation.A dataset of 221 samples from 65 engineering survey reports from Shanghai infrastructure projects was constructed to evaluate the accuracy of the new model5 s predictions.The mean squared error and correlation coefficient of the optimum GBRT model applied to the testing set were 0.13 and 0.91,respectively,indicating that the proposed machine learning(ML)model has great potential to improve the prediction of Es for soft clay.A comparison of the performance of empirical formulas and the proposed ML method for predicting foundation settlement indicated the rationality of the proposed ML model and its applicability to the compressive deformation of geotechnical systems.This model,however,cannot be directly applied to the prediction of Es in other sites due to its site specificity.This problem can be solved by retraining the model using local data.This study provides a useful reference for future multi-parameter prediction of soil behavior.
文摘A new mulfitarget constant modulus array is proposed for CDMA systems based on least squares constant modulus algorithm. The new algorithm is called pre-despreading decision directed least squares constant modulus algorithm （D-DDLSCMA）. In the new algorithm, the pre-despreading is first applied for multitarget arrays to remove some multiple access signals, then the despreaded signal is processed by the algorithm which united the constant modulus algorithm and decision directed method. Simulation results illustrate the good performance for the proposed algorithm.
文摘A new semi-blind adaptive beamforming scheme is proposed for multi-input multi-output （MIMO） induced and spacedivision multiple-access based wireless systems that employ high order phase shift keying signaling. A minimum number of training symbols, very close to the number of receiver antenna elements, are used to provide a rough initial least squares estimate of the beamformer＇s weight vector. A novel cost function combining the constant modulus criterion with decision-directed adaptation is adopted to adapt the beamformer weight vector. This cost function can be approximated as a quadratic form with a closed-form solution, based on which we then derive the recursive least squares （RLS） semi-blind adaptive beamforming algorithm. This semi-blind adaptive beamforming scheme is capable of converging fast to the minimum mean-square-error beamforming solution, as demonstrated in our simulation study. Our proposed semi-blind RLS beamforming algorithm therefore provides an efficient detection scheme for the future generation of MIMO aided mobile communication systems.
基金Project supported by the National Natural Science Foundation of China (No. 60372107) and the Hi-Tech Research and Development Program (863) of China (No. 2002AA121068)
文摘This paper proposes a new multitarget constant modulus array structure for code division multiple access (CDMA) systems. The new algorithm for the structure is called pre-despreading and wavelet denoising constant modulus algorithm (D-WD-CMA). In the new algorithm, the pre-despreading is applied to multitarget arrays to remove some multiple access inter- ferences. After that the received signal is subjected to wavelet de-noising to reduce some noise, and used in CMA adaptive iteration for signal separation. Simulation results showed that the proposed algorithm performed better than the traditional CMA algorithm.
文摘This paper considers three algorithms for the extraction of square roots of complex integers {called Gaussians} using arithmetic based on complex modulus p + iq. These algorithms are almost twice as fast as the analogous algorithms extracting square roots of either real or complex integers in arithmetic based on modulus p, where is a real prime. A cryptographic system based on these algorithms is provided in this paper. A procedure reducing the computational complexity is described as well. Main results are explained in several numeric illustrations.
基金Supported by the National Natural Science Foundation of China (60372057)
文摘A new blind equalization algorithm based on the modified constant modulus algorithm （MCMA） and dithered signederror constant modulus algorithm （DSE-CMA） is proposed. This dithered signed-error MCMA （DSE-MCMA） can not only reduce the computational complexity, but also recover the phase rotation in the complex channel. Simulation results have verified the analysis and indicated the good property of DSE-MCMA.
文摘Shor proposed a polynomial time algorithm for computing the order of one element in a multiplicative group using a quantum computer. Based on Miller’s randomization, he then gave a factorization algorithm. But the algorithm has two shortcomings, the order must be even and the output might be a trivial factor. Actually, these drawbacks can be overcome if the number is an RSA modulus. Applying the special structure of the RSA modulus, an algorithm is presented to overcome the two shortcomings. The new algorithm improves Shor’s algorithm for factoring RSA modulus. The cost of the factorization algorithm almost depends on the calculation of the order of 2 in the multiplication group.
基金Sponsored by the National Natural Science Fundation of China (No.60472104), Natural Science Research Project of Jiangsu Province (04KJB510094) and Doctoral In-novative Fund of Jiangsu Province (xm04-32).
文摘A novel Least Squares Constant Modulus (LSCM) beam-forming algorithm in smart antenna Multi-Carrier Code Division Multiple Access (MC-CDMA) system is proposed in this paper. It adaptively beam-forms the multi-carrier antenna array signal using the LSCM Algorithm (LSCMA), and in the meantime, the beam-formed signals on every sub-carrier are combined by using Orthogonal Restore Combination (ORC), Equal Gain Combination (EGC) or Maximum Ratio Combination (MRC). Then the decision of the combined signals and the spread-code of the expected user are used to re-construct the signals on every sub-carrier. At last, the difference between the re-constructed signal and the output signal of the beam-former is used to con-trol the coefficients of the beam-former. The bit error probability of the proposed algorithm is analyzed. We simulated and compared it with the conventional LSCM beam-forming algorithm. Simulation results show that the proposed algorithm is superior to the latter in Bit Error Rate (BER).
文摘This paper investigates the blind algorithm for channel estimation of Orthogonal Frequency Division Multiplexing-Multiple Input Multiple Output (OFDM-MIMO) wireless communication system using the subspace decomposition of the channel received complex baseband signals and proposes a new two-stage blind algorithm. Exploited the second-order cyclostationarity inherent in OFDM with cyclic prefix and the characteristics of the phased antenna, the practical HIPERLAN/2 standard based OFDM-MIMO simulator is established with the sufficient consideration of statistical correlations between the multiple antenna channels under wireless wideband multipath fading environment, and a new two-stage blind algorithm is formulated using rank reduced subspace channel matrix approximation and adaptive Constant Modulus (CM)criterion. Simulation results confirm the theoretical analysis and illustrate that the proposed algorithm is capable of tracking matrix channel variations with fast convergence rate and improving acceptable overall system performance over various common wireless and mobile communication links.
基金Supported by the National Natural Science Foundation of China (No.60472104)Doctoral innovative fund of Jiangsu province (xm04-32).
文摘Two blind multiuser detection algorithms for antenna array in Code Division Multiple Access （CDMA） system which apply the linearly constrained condition to the Least Squares Constant Modulus Algorithln （LSCMA） are proposed in this paper. One is the Linearly Constrained LSCMA （LC-LSCMA）, the other is the Preprocessing LC-LSCMA （PLC-LSCMA）. The two algorithms are compared with the conventional LSCMA. The results show that the two algorithms proposed in this paper are superior to the conventional LSCMA and the best one is PLC-LSCMA.
