本文研究了两变量函数 f(x,y)用单变量函数 g(x)作混合范数逼近问题,即求g~*(x)∈G,G 是一 Haar 子空间,使(?)integral from Y|f(x,y)-g~*(x)|dμ=(?)integral from Y|f((?),y)-g(x)|dμ我们建立了包括交错定理、de la Vallee Poussin ...本文研究了两变量函数 f(x,y)用单变量函数 g(x)作混合范数逼近问题,即求g~*(x)∈G,G 是一 Haar 子空间,使(?)integral from Y|f(x,y)-g~*(x)|dμ=(?)integral from Y|f((?),y)-g(x)|dμ我们建立了包括交错定理、de la Vallee Poussin 定理、唯一性定理和强唯一性定理在内的 Chebyshev 逼近理论。展开更多
A complex exothermic batch reactor model was developed by using structure approaching hybrid neural networks(SAHNN).The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum prod...A complex exothermic batch reactor model was developed by using structure approaching hybrid neural networks(SAHNN).The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum product concentration problem based on recurrent neural network(RNN).Considering model-plant mismatches and unmeasured disturbances,a novel extended integral square error index(EISE)was proposed,which introduced mismatches of model-plant into the optimal control profile.The approach used a feedback channel for the control and therefore dramatically enhanced the robustness and anti-disturbance performance.The stability analysis of the one-step-ahead control strategy through SAHNN-based model was described based on Lyapunov theory in detail.The result fully demonstrated the effectiveness of the proposed optimal control profile.展开更多
基于状态空间模型的许多传统滤波算法都基于Rn空间中的高斯分布模型,但当状态向量中包含角变量或方向变量时,难以达到理想的效果。针对J.T.Horwood等提出的nS?R流形上的Gauss Von Mises(GVM)多变量概率密度分布,扩展了狄拉克混合逼近方...基于状态空间模型的许多传统滤波算法都基于Rn空间中的高斯分布模型,但当状态向量中包含角变量或方向变量时,难以达到理想的效果。针对J.T.Horwood等提出的nS?R流形上的Gauss Von Mises(GVM)多变量概率密度分布,扩展了狄拉克混合逼近方法,给出了联合分布的GVM逼近方法,推导了后验分布的GVM参数计算公式,设计了量测更新状态估计算法。将J.T.Horwood等的时间更新算法与所提出的量测更新算法相结合,可实现基于GVM分布的递推贝叶斯滤波器(GVMF)。仿真结果表明,当状态向量符合GVM概率分布模型时,GVMF对角变量的估计明显优于传统的扩展卡尔曼滤波器。展开更多
New mixed finite element methods are presented for the second order ellip tic problem :-Δu = f in Ω , with u ∈ H01(Ω).These new methods are coercive, and the resulting linear systems are positively definite, with ...New mixed finite element methods are presented for the second order ellip tic problem :-Δu = f in Ω , with u ∈ H01(Ω).These new methods are coercive, and the resulting linear systems are positively definite, with condition number O(h-2).Moreover, they allow the use of much more finite elements.展开更多
文摘本文研究了两变量函数 f(x,y)用单变量函数 g(x)作混合范数逼近问题,即求g~*(x)∈G,G 是一 Haar 子空间,使(?)integral from Y|f(x,y)-g~*(x)|dμ=(?)integral from Y|f((?),y)-g(x)|dμ我们建立了包括交错定理、de la Vallee Poussin 定理、唯一性定理和强唯一性定理在内的 Chebyshev 逼近理论。
文摘A complex exothermic batch reactor model was developed by using structure approaching hybrid neural networks(SAHNN).The optimal reactor temperature profiles were obtained via the PSO-SQP algorithm solving maximum product concentration problem based on recurrent neural network(RNN).Considering model-plant mismatches and unmeasured disturbances,a novel extended integral square error index(EISE)was proposed,which introduced mismatches of model-plant into the optimal control profile.The approach used a feedback channel for the control and therefore dramatically enhanced the robustness and anti-disturbance performance.The stability analysis of the one-step-ahead control strategy through SAHNN-based model was described based on Lyapunov theory in detail.The result fully demonstrated the effectiveness of the proposed optimal control profile.
文摘基于状态空间模型的许多传统滤波算法都基于Rn空间中的高斯分布模型,但当状态向量中包含角变量或方向变量时,难以达到理想的效果。针对J.T.Horwood等提出的nS?R流形上的Gauss Von Mises(GVM)多变量概率密度分布,扩展了狄拉克混合逼近方法,给出了联合分布的GVM逼近方法,推导了后验分布的GVM参数计算公式,设计了量测更新状态估计算法。将J.T.Horwood等的时间更新算法与所提出的量测更新算法相结合,可实现基于GVM分布的递推贝叶斯滤波器(GVMF)。仿真结果表明,当状态向量符合GVM概率分布模型时,GVMF对角变量的估计明显优于传统的扩展卡尔曼滤波器。
文摘New mixed finite element methods are presented for the second order ellip tic problem :-Δu = f in Ω , with u ∈ H01(Ω).These new methods are coercive, and the resulting linear systems are positively definite, with condition number O(h-2).Moreover, they allow the use of much more finite elements.
