在卫星高速数传系统中,为了提高通信速率和频谱效率,M-QAM和M-QPSK等高阶调制方式被越来越多地采用,由此带来的功率放大器的非线性效应和记忆效应也日益严重,对通信系统性能造成很大影响。针对传统数字预失真算法收敛速度慢和计算复杂...在卫星高速数传系统中,为了提高通信速率和频谱效率,M-QAM和M-QPSK等高阶调制方式被越来越多地采用,由此带来的功率放大器的非线性效应和记忆效应也日益严重,对通信系统性能造成很大影响。针对传统数字预失真算法收敛速度慢和计算复杂度大等问题,提出了一种基于快速横向滤波递推最小二乘(Fast Transversal Recursive Least Square,FTRLS)的参数提取算法,并对该算法进行了理论分析和性能仿真。仿真结果表明,与经典RLS算法相比,该算法具有稳态误差小、收敛速度快和计算复杂度低的优势以及更优良的功放线性化效果。展开更多
Aiming at the drift problem that the tracking control of the actual load relative to the target load during the electromagnetic excitation biaxial fatigue test of wind turbine blades is easy to drift,a biaxial fatigue...Aiming at the drift problem that the tracking control of the actual load relative to the target load during the electromagnetic excitation biaxial fatigue test of wind turbine blades is easy to drift,a biaxial fatigue testingmachine for electromagnetic excitation is designed,and the following strategy of the actual load and the target load is studied.A Fast Transversal Recursive Least Squares algorithm based on fuzzy logic(Fuzzy FTRLS)is proposed to develop a fatigue loading following dynamic strategy,which adjusts the forgetting factor in the algorithmthrough fuzzy logic to overcome the contradiction between convergence accuracy and convergence speed and solve the phenomenon of amplitude overshoot and phase lag of the actual load relative to the target load.Combined with the previous research results,a simulation model was constructed to verify the strategy’s effectiveness.Field tests were carried out to verify its follow-up effect.The results showthat the tracking error of flapwise and edgewise direction iswithin 4%,which has better robustness and dynamic and static performance than the traditional Recursive Least Squares(RLS)algorithm.展开更多
The shadow tomography problem introduced by[1]is an important problem in quantum computing.Given an unknown-qubit quantum state,the goal is to estimate tr■,...,tr■using as least copies of■as possible,within an addi...The shadow tomography problem introduced by[1]is an important problem in quantum computing.Given an unknown-qubit quantum state,the goal is to estimate tr■,...,tr■using as least copies of■as possible,within an additive error of,whereF1,...,FM are known-outcome measurements.In this paper,we consider the shadow tomography problem with a potentially inaccurate prediction■of the true state■.This corresponds to practical cases where we possess prior knowledge of the unknown state.For example,in quantum verification or calibration,we may be aware of the quantum state that the quantum device is expected to generate.However,the actual state it generates may have deviations.We introduce an algorithm with sample complexity■(nmax{■ε}log2M/ε4.In the generic case,even if the prediction can be arbitrarily bad,our algorithm has the same complexity as the best algorithm without prediction[2].At the same time,as the prediction quality improves,the sample complexity can be reduced smoothly to■(nlog2M/ε3)when the trace distance between the prediction and the unknown state is■(ε).Furthermore,we conduct numerical experiments to validate our theoretical analysis.The experiments are constructed to simulate noisy quantum circuits that reflect possible real scenarios in quantum verification or calibration.Notably,our algorithm outperforms the previous work without prediction in most settings.展开更多
文摘在卫星高速数传系统中,为了提高通信速率和频谱效率,M-QAM和M-QPSK等高阶调制方式被越来越多地采用,由此带来的功率放大器的非线性效应和记忆效应也日益严重,对通信系统性能造成很大影响。针对传统数字预失真算法收敛速度慢和计算复杂度大等问题,提出了一种基于快速横向滤波递推最小二乘(Fast Transversal Recursive Least Square,FTRLS)的参数提取算法,并对该算法进行了理论分析和性能仿真。仿真结果表明,与经典RLS算法相比,该算法具有稳态误差小、收敛速度快和计算复杂度低的优势以及更优良的功放线性化效果。
基金funded by the National Natural Science Foundation of China (Grant Number 52075305).
文摘Aiming at the drift problem that the tracking control of the actual load relative to the target load during the electromagnetic excitation biaxial fatigue test of wind turbine blades is easy to drift,a biaxial fatigue testingmachine for electromagnetic excitation is designed,and the following strategy of the actual load and the target load is studied.A Fast Transversal Recursive Least Squares algorithm based on fuzzy logic(Fuzzy FTRLS)is proposed to develop a fatigue loading following dynamic strategy,which adjusts the forgetting factor in the algorithmthrough fuzzy logic to overcome the contradiction between convergence accuracy and convergence speed and solve the phenomenon of amplitude overshoot and phase lag of the actual load relative to the target load.Combined with the previous research results,a simulation model was constructed to verify the strategy’s effectiveness.Field tests were carried out to verify its follow-up effect.The results showthat the tracking error of flapwise and edgewise direction iswithin 4%,which has better robustness and dynamic and static performance than the traditional Recursive Least Squares(RLS)algorithm.
基金supported by the National Natural Science Foundation of China(Grant Nos.62325210,and 62272441)the Strategic Priority Research Program of Chinese Academy of Sciences(No.XDB28000000)+1 种基金supported by the National Natural Science Foundation of China(Grant Nos.62372006,92365117)the Fundamental Research Funds for the Central Universities,Peking University.
文摘The shadow tomography problem introduced by[1]is an important problem in quantum computing.Given an unknown-qubit quantum state,the goal is to estimate tr■,...,tr■using as least copies of■as possible,within an additive error of,whereF1,...,FM are known-outcome measurements.In this paper,we consider the shadow tomography problem with a potentially inaccurate prediction■of the true state■.This corresponds to practical cases where we possess prior knowledge of the unknown state.For example,in quantum verification or calibration,we may be aware of the quantum state that the quantum device is expected to generate.However,the actual state it generates may have deviations.We introduce an algorithm with sample complexity■(nmax{■ε}log2M/ε4.In the generic case,even if the prediction can be arbitrarily bad,our algorithm has the same complexity as the best algorithm without prediction[2].At the same time,as the prediction quality improves,the sample complexity can be reduced smoothly to■(nlog2M/ε3)when the trace distance between the prediction and the unknown state is■(ε).Furthermore,we conduct numerical experiments to validate our theoretical analysis.The experiments are constructed to simulate noisy quantum circuits that reflect possible real scenarios in quantum verification or calibration.Notably,our algorithm outperforms the previous work without prediction in most settings.
