In this paper, we propose an efficient adaptive iteratively reweighted l<sub>1</sub> algorithm (A-IRL1 algorithm) for solving the elastic l<sub>q</sub> regularization problem. We prove that the...In this paper, we propose an efficient adaptive iteratively reweighted l<sub>1</sub> algorithm (A-IRL1 algorithm) for solving the elastic l<sub>q</sub> regularization problem. We prove that the sequence generated by the A-IRL1 algorithm is convergent for any rational and the limit is a critical point of the elastic l<sub>q</sub> regularization problem. Under certain conditions, we present an error bound for the limit point of convergent sequence.展开更多
设计了一个DS18B20温度传感器校验平台。将Pt100测得的温度值作为标准温度值,校验温度传感器是否合格。为了提高Pt100测得温度的精准性,使用格罗布斯准则和算术平均值法分别消除粗大误差和随机误差。以P89LPC935为核心设计了校验平台的...设计了一个DS18B20温度传感器校验平台。将Pt100测得的温度值作为标准温度值,校验温度传感器是否合格。为了提高Pt100测得温度的精准性,使用格罗布斯准则和算术平均值法分别消除粗大误差和随机误差。以P89LPC935为核心设计了校验平台的硬件和软件,并使用Visual C++ 6.0设计了上位机显示界面。展开更多
文摘In this paper, we propose an efficient adaptive iteratively reweighted l<sub>1</sub> algorithm (A-IRL1 algorithm) for solving the elastic l<sub>q</sub> regularization problem. We prove that the sequence generated by the A-IRL1 algorithm is convergent for any rational and the limit is a critical point of the elastic l<sub>q</sub> regularization problem. Under certain conditions, we present an error bound for the limit point of convergent sequence.
文摘设计了一个DS18B20温度传感器校验平台。将Pt100测得的温度值作为标准温度值,校验温度传感器是否合格。为了提高Pt100测得温度的精准性,使用格罗布斯准则和算术平均值法分别消除粗大误差和随机误差。以P89LPC935为核心设计了校验平台的硬件和软件,并使用Visual C++ 6.0设计了上位机显示界面。