The methods of Traditional Chinese Medicine(TCM)’s diagnosis and treatment have undergone several changes.It is crucial to build a proper model which is capable to modernize TCM into a both standardized and individua...The methods of Traditional Chinese Medicine(TCM)’s diagnosis and treatment have undergone several changes.It is crucial to build a proper model which is capable to modernize TCM into a both standardized and individualized treatment.Tong xiao-lin proposed the state-target strategy to build a bridge for the integration of Chinese and Western medicine.It is a model based on modern medical disease concepts and using the method of TCM to balance the pathological states and adopting the achievements of pharmacology of Chinese medicine to focus on the disease targets,symptom targets,and biochemical indicator targets.The reconstruction of TCM diagnosis and treatment system for diabetes is a good example to demonstrate this theory.It could improve the clinical efficacy,support the scientific research,and reinforce the standardization of TCM.展开更多
Deep neural networks(DNNs)and auto differentiation have been widely used in computational physics to solve variational problems.When a DNN is used to represent the wave function and solve quantum many-body problems us...Deep neural networks(DNNs)and auto differentiation have been widely used in computational physics to solve variational problems.When a DNN is used to represent the wave function and solve quantum many-body problems using variational optimization,various physical constraints have to be injected into the neural network by construction to increase the data and learning efficiency.We build the unitary constraint to the variational wave function using a monotonic neural network to represent the cumulative distribution function(CDF)F(x)=ʃ^(x)_(-∞)Ψ*Ψdx',.Using this constrained neural network to represent the variational wave function,we solve Schrodinger equations using auto-differentiation and stochastic gradient descent(SGD)by minimizing the violation of the trial wave function(x)to the Schrodinger equation.For several classical problems in quantum mechanics,we obtain their ground state wave function and energy with very low errors.The method developed in the present paper may pave a new way for solving nuclear many-body problems in the future.展开更多
A modular approach of the estimation-based design in adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noise...A modular approach of the estimation-based design in adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters.By using Itô’s differentiation rule,nonlinear damping and adaptive Backstepping procedure,the input-to-state stable controller of global stabilization in probability is developed,which guarantees that system states are bounded and the system has a robust stabilization.According to Swapping technique,we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed.Transient performance of the system is estimated by the norm of error.Results of simulation show the effectiveness of the control algorithms.The modular design,which has a concise hierarchy,is more flexible and versatile than a Lyapunov-based algorithm.展开更多
文摘The methods of Traditional Chinese Medicine(TCM)’s diagnosis and treatment have undergone several changes.It is crucial to build a proper model which is capable to modernize TCM into a both standardized and individualized treatment.Tong xiao-lin proposed the state-target strategy to build a bridge for the integration of Chinese and Western medicine.It is a model based on modern medical disease concepts and using the method of TCM to balance the pathological states and adopting the achievements of pharmacology of Chinese medicine to focus on the disease targets,symptom targets,and biochemical indicator targets.The reconstruction of TCM diagnosis and treatment system for diabetes is a good example to demonstrate this theory.It could improve the clinical efficacy,support the scientific research,and reinforce the standardization of TCM.
基金Supported by the National Natural Science Foundation of China(12035006,12075098)the Natural Science Foundation of Hubei Province(2019CFB563)+1 种基金the Hubei Province Department of Education(D20201108)Hubei Province Department of Science and Technology(2021BLB171)。
文摘Deep neural networks(DNNs)and auto differentiation have been widely used in computational physics to solve variational problems.When a DNN is used to represent the wave function and solve quantum many-body problems using variational optimization,various physical constraints have to be injected into the neural network by construction to increase the data and learning efficiency.We build the unitary constraint to the variational wave function using a monotonic neural network to represent the cumulative distribution function(CDF)F(x)=ʃ^(x)_(-∞)Ψ*Ψdx',.Using this constrained neural network to represent the variational wave function,we solve Schrodinger equations using auto-differentiation and stochastic gradient descent(SGD)by minimizing the violation of the trial wave function(x)to the Schrodinger equation.For several classical problems in quantum mechanics,we obtain their ground state wave function and energy with very low errors.The method developed in the present paper may pave a new way for solving nuclear many-body problems in the future.
基金supported by National Natural Science Foundation of China(61374065,61374002,61503225,61573215)the Research Fund for the Taishan Scholar Project of Shandong Province of Chinathe Natural Science Foundation of Shandong Province(ZR2015FQ003)
基金supported by the National science Foundation of Anhui(03042302)。
文摘A modular approach of the estimation-based design in adaptive linear control systems has been extended to the adaptive robust control of strict-feedback stochastic nonlinear systems with additive standard Wiener noises and constant unknown parameters.By using Itô’s differentiation rule,nonlinear damping and adaptive Backstepping procedure,the input-to-state stable controller of global stabilization in probability is developed,which guarantees that system states are bounded and the system has a robust stabilization.According to Swapping technique,we develop two filters and convert dynamic parametric models into static ones to which the gradient update law is designed.Transient performance of the system is estimated by the norm of error.Results of simulation show the effectiveness of the control algorithms.The modular design,which has a concise hierarchy,is more flexible and versatile than a Lyapunov-based algorithm.
