In this paper, firstly, we propose a new method for choosing regularization parameter λ for lasso regression, which differs from traditional method such as multifold cross-validation, our new method gives the maximum...In this paper, firstly, we propose a new method for choosing regularization parameter λ for lasso regression, which differs from traditional method such as multifold cross-validation, our new method gives the maximum value of parameter λ directly. Secondly, by considering another prior form over model space in the Bayes approach, we propose a new extended Bayes information criterion family, and under some mild condition, our new EBIC (NEBIC) is shown to be consistent. Then we apply our new method to choose parameter for sequential lasso regression which selects features by sequentially solving partially penalized least squares problems where the features selected in earlier steps are not penalized in the subsequent steps. Then sequential lasso uses NEBIC as the stopping rule. Finally, we apply our algorithm to identify the nonzero entries of precision matrix for high-dimensional linear discrimination analysis. Simulation results demonstrate that our algorithm has a lower misclassification rate and less computation time than its competing methods under considerations.展开更多
采用0.13μm Si Ge双极互补型金属氧化物半导体（Bi CMOS）工艺,设计了一款X波段功率放大器芯片。通过采用共射共基放大器电路结构和有源线性化偏置电路,提高了电路耐压值和功放最大输出功率。通过两级共射共基放大电路级联,结合级间匹...采用0.13μm Si Ge双极互补型金属氧化物半导体（Bi CMOS）工艺,设计了一款X波段功率放大器芯片。通过采用共射共基放大器电路结构和有源线性化偏置电路,提高了电路耐压值和功放最大输出功率。通过两级共射共基放大电路级联,结合级间匹配电路及输出匹配电路,提高了放大器的增益和工作带宽。采用非均匀功率管版图布局及镇流电阻,提升功率放大器电路可靠性。测试结果表明,在8-12 GHz频段内,放大器回波损耗均小于-10 d B,小信号增益大于30 d B,1 d B压缩点输出功率为16 d Bm,饱和功率大于19 d Bm,峰值饱和功率附加效率大于18%。该放大器工作在AB类,采用5 V供电,静态工作电流为80 m A,面积为1.22 mm×0.73 mm。展开更多
文摘In this paper, firstly, we propose a new method for choosing regularization parameter λ for lasso regression, which differs from traditional method such as multifold cross-validation, our new method gives the maximum value of parameter λ directly. Secondly, by considering another prior form over model space in the Bayes approach, we propose a new extended Bayes information criterion family, and under some mild condition, our new EBIC (NEBIC) is shown to be consistent. Then we apply our new method to choose parameter for sequential lasso regression which selects features by sequentially solving partially penalized least squares problems where the features selected in earlier steps are not penalized in the subsequent steps. Then sequential lasso uses NEBIC as the stopping rule. Finally, we apply our algorithm to identify the nonzero entries of precision matrix for high-dimensional linear discrimination analysis. Simulation results demonstrate that our algorithm has a lower misclassification rate and less computation time than its competing methods under considerations.
文摘采用0.13μm Si Ge双极互补型金属氧化物半导体（Bi CMOS）工艺,设计了一款X波段功率放大器芯片。通过采用共射共基放大器电路结构和有源线性化偏置电路,提高了电路耐压值和功放最大输出功率。通过两级共射共基放大电路级联,结合级间匹配电路及输出匹配电路,提高了放大器的增益和工作带宽。采用非均匀功率管版图布局及镇流电阻,提升功率放大器电路可靠性。测试结果表明,在8-12 GHz频段内,放大器回波损耗均小于-10 d B,小信号增益大于30 d B,1 d B压缩点输出功率为16 d Bm,饱和功率大于19 d Bm,峰值饱和功率附加效率大于18%。该放大器工作在AB类,采用5 V供电,静态工作电流为80 m A,面积为1.22 mm×0.73 mm。
