Based on the synthesis and analysis of recursive receivers, a new algorithm, namely partial grouping maximization likelihood algorithm, is proposed to achieve satisfactory performance with moderate computational compl...Based on the synthesis and analysis of recursive receivers, a new algorithm, namely partial grouping maximization likelihood algorithm, is proposed to achieve satisfactory performance with moderate computational complexity.During the analysis, some interesting properties shared by the proposed procedures are described.Finally, the performance assessment shows that the new scheme is superior to the linear detector and ordinary grouping algorithm, and achieves a bit-error rate close to that of the optimum receiver.展开更多
The technology investment strategy under uncertainty is the key subject. However, the expected utility maximization often employed as the decision process fails to consider the high risk with low probability cases. On...The technology investment strategy under uncertainty is the key subject. However, the expected utility maximization often employed as the decision process fails to consider the high risk with low probability cases. On the other hand, the existing min-max regret strategy tends to be dominated by the ＂worst assumption＂ regardless of its probability. This research proposes a new framework by formulating the regret by the Minkowski＇s generalized distance. The authors then apply the formulation to the IAM （integrated assessment model） MARIA. This study focuses on the uncertainties of CCS （carbon capture and storage） costs and the global warming damages. This formulation is then extended to the multi-stage decision frame, known as ATL （act-then-learn） method. The simulation results suggest that the substantial changes in CCS and nuclear deployment strategies depending on the future uncertainty scenarios. The results also suggest that the minimum regret strategy favors the capital accumulation in the early stage.展开更多
基金Supported by National Natural Science Foundation of China (No. 60372107, 10371106, 10471114)Natural Science Foundation of Jiangsu Province (No. 04KJB110097)
文摘Based on the synthesis and analysis of recursive receivers, a new algorithm, namely partial grouping maximization likelihood algorithm, is proposed to achieve satisfactory performance with moderate computational complexity.During the analysis, some interesting properties shared by the proposed procedures are described.Finally, the performance assessment shows that the new scheme is superior to the linear detector and ordinary grouping algorithm, and achieves a bit-error rate close to that of the optimum receiver.
文摘The technology investment strategy under uncertainty is the key subject. However, the expected utility maximization often employed as the decision process fails to consider the high risk with low probability cases. On the other hand, the existing min-max regret strategy tends to be dominated by the ＂worst assumption＂ regardless of its probability. This research proposes a new framework by formulating the regret by the Minkowski＇s generalized distance. The authors then apply the formulation to the IAM （integrated assessment model） MARIA. This study focuses on the uncertainties of CCS （carbon capture and storage） costs and the global warming damages. This formulation is then extended to the multi-stage decision frame, known as ATL （act-then-learn） method. The simulation results suggest that the substantial changes in CCS and nuclear deployment strategies depending on the future uncertainty scenarios. The results also suggest that the minimum regret strategy favors the capital accumulation in the early stage.
