We prove the existence and nonexistence of elliptic curves having good reduction everywhere over certain real quadratic fields Q(m) for m≤200. These results of computations give best-possible data including structure...We prove the existence and nonexistence of elliptic curves having good reduction everywhere over certain real quadratic fields Q(m) for m≤200. These results of computations give best-possible data including structures of Mordell-Weil groups over some real quadratic fields via two-descent. We also prove similar results for the case of certain cubic fields. Especially, we give the first example of elliptic curve having everywhere good reduction over a pure cubic field using our method.展开更多
为进一步提高多输入多输出(MIMO)双向中继系统性能,该文在梯度下降法的基础上,引入用户端功率分配和发射预编码与接收波束成形,结合中继站波束成形矩阵和分配功率相,构成一个完整的联合交替迭代结构(AIS);通过固定变量循环计算,逐个得...为进一步提高多输入多输出(MIMO)双向中继系统性能,该文在梯度下降法的基础上,引入用户端功率分配和发射预编码与接收波束成形,结合中继站波束成形矩阵和分配功率相,构成一个完整的联合交替迭代结构(AIS);通过固定变量循环计算,逐个得到各个变量的最优值。仿真表明,与梯度下降法、迫零和最小均方误差加注水功率分配法相比,该文交替迭代结构方法的速率有所提高,误码性能提高较明显。当误码率等于10-2时,与3种算法中最优的梯度下降法相比,该文方法可获得2.5 d B的信噪比增益。展开更多
针对单用户对双向中继系统中的功率分配问题,提出了一种基于梯度下降法的功率分配方案。该方案在总功率约束的条件下,以最大化和速率为目标函数,通过对中继波束成形矩阵和功率分配矩阵的反复迭代,求解出局部最优的功率分配和中继波束成...针对单用户对双向中继系统中的功率分配问题,提出了一种基于梯度下降法的功率分配方案。该方案在总功率约束的条件下,以最大化和速率为目标函数,通过对中继波束成形矩阵和功率分配矩阵的反复迭代,求解出局部最优的功率分配和中继波束成形矩阵。仿真结果表明:提出方案的误码性能相比于等功率分配有明显提高,在误码率为10-2时,可获得2.5d B^3 d B的信噪比增益;同时,在中高信噪比下,相比于等功率分配,该方案可获得0.3(bit/s)/Hz^0.5(bit/s)/Hz的和速率增益。展开更多
A neuro-fuzzy system model based on automatic fuzzy dustering is proposed. A hybrid model identification algorithm is also developed to decide the model structure and model parameters. The algorithm mainly includes th...A neuro-fuzzy system model based on automatic fuzzy dustering is proposed. A hybrid model identification algorithm is also developed to decide the model structure and model parameters. The algorithm mainly includes three parts：1） Automatic fuzzy C-means （AFCM）, which is applied to generate fuzzy rttles automatically, and then fix on the size of the neuro-fuzzy network, by which the complexity of system design is reducesd greatly at the price of the fitting capability; 2） R.ecursive least square estimation （RLSE）. It is used to update the parameters of Takagi-Sugeno model, which is employed to describe the behavior of the system;3） Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network. Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.展开更多
在统计学中,多借助零膨胀模型研究零膨胀数据潜在的模型结构及变量选择问题。然而,在多数情况下,响应变量的非零部分为定量数据,简单的零膨胀模型无法刻画这类数据的模型结构,对应的参数估计方法也不再适用。鉴于此,学者提出处理零膨胀...在统计学中,多借助零膨胀模型研究零膨胀数据潜在的模型结构及变量选择问题。然而,在多数情况下,响应变量的非零部分为定量数据,简单的零膨胀模型无法刻画这类数据的模型结构,对应的参数估计方法也不再适用。鉴于此,学者提出处理零膨胀半连续数据的两部模型。本文将组合惩罚似然估计方法引入两部模型,研究其变量选择问题。提出一种新的处理高维统计分析问题的惩罚似然估计方法:NCPM (New Combined Punishment Method),并将该方法应用于太原市降水量数据,分析其影响因素。模拟及实例分析结果均表明本文的方法行之有效,较传统的惩罚似然估计方法具有更高的预测精度。展开更多
文摘We prove the existence and nonexistence of elliptic curves having good reduction everywhere over certain real quadratic fields Q(m) for m≤200. These results of computations give best-possible data including structures of Mordell-Weil groups over some real quadratic fields via two-descent. We also prove similar results for the case of certain cubic fields. Especially, we give the first example of elliptic curve having everywhere good reduction over a pure cubic field using our method.
文摘为进一步提高多输入多输出(MIMO)双向中继系统性能,该文在梯度下降法的基础上,引入用户端功率分配和发射预编码与接收波束成形,结合中继站波束成形矩阵和分配功率相,构成一个完整的联合交替迭代结构(AIS);通过固定变量循环计算,逐个得到各个变量的最优值。仿真表明,与梯度下降法、迫零和最小均方误差加注水功率分配法相比,该文交替迭代结构方法的速率有所提高,误码性能提高较明显。当误码率等于10-2时,与3种算法中最优的梯度下降法相比,该文方法可获得2.5 d B的信噪比增益。
文摘针对单用户对双向中继系统中的功率分配问题,提出了一种基于梯度下降法的功率分配方案。该方案在总功率约束的条件下,以最大化和速率为目标函数,通过对中继波束成形矩阵和功率分配矩阵的反复迭代,求解出局部最优的功率分配和中继波束成形矩阵。仿真结果表明:提出方案的误码性能相比于等功率分配有明显提高,在误码率为10-2时,可获得2.5d B^3 d B的信噪比增益;同时,在中高信噪比下,相比于等功率分配,该方案可获得0.3(bit/s)/Hz^0.5(bit/s)/Hz的和速率增益。
文摘A neuro-fuzzy system model based on automatic fuzzy dustering is proposed. A hybrid model identification algorithm is also developed to decide the model structure and model parameters. The algorithm mainly includes three parts：1） Automatic fuzzy C-means （AFCM）, which is applied to generate fuzzy rttles automatically, and then fix on the size of the neuro-fuzzy network, by which the complexity of system design is reducesd greatly at the price of the fitting capability; 2） R.ecursive least square estimation （RLSE）. It is used to update the parameters of Takagi-Sugeno model, which is employed to describe the behavior of the system;3） Gradient descent algorithm is also proposed for the fuzzy values according to the back propagation algorithm of neural network. Finally,modeling the dynamical equation of the two-link manipulator with the proposed approach is illustrated to validate the feasibility of the method.
文摘在统计学中,多借助零膨胀模型研究零膨胀数据潜在的模型结构及变量选择问题。然而,在多数情况下,响应变量的非零部分为定量数据,简单的零膨胀模型无法刻画这类数据的模型结构,对应的参数估计方法也不再适用。鉴于此,学者提出处理零膨胀半连续数据的两部模型。本文将组合惩罚似然估计方法引入两部模型,研究其变量选择问题。提出一种新的处理高维统计分析问题的惩罚似然估计方法:NCPM (New Combined Punishment Method),并将该方法应用于太原市降水量数据,分析其影响因素。模拟及实例分析结果均表明本文的方法行之有效,较传统的惩罚似然估计方法具有更高的预测精度。
