最近剛剛在線發表在《Journal of Integrative Agriculture》，這對面臨文章發表壓力的學生來說是一個重要的肯定，歡迎各位同行指教，
吃角子老虎機英文
Liang P錛 Qin C-Z*錛 Zhu A-X錛 Hou Z-W錛 Fan N-Q錛 Wang Y-J. A case-based method of selecting covariates for digital soil mapping. Journal of Integrative Agriculture錛 2020. doi:10.1016/S2095-3119(19)62857-1https://ieeexplore.ieee.org/document/8964345就貝葉斯估計的幾個關鍵問題進行了研究，結果還是不錯的，
有味道的雲小攤兒
解決了幾個疑惑問題，In this paper錛 we investigate the benefit of intentionally added noise to observed data in various scenarios of Bayesian parameter estimation. For optimal estimators錛 we theoretically demonstrate that the Bayesian Cram□r-Rao bound for the case with added noise is never smaller than for the original data錛 and the minimum mean-square error (MSE) estimator performs no better. This motivates us to explore the feasibility of noise benefit in some useful suboptimal estimators. Several Bayesian estimators established from one-bit-quantizer sensors are considered錛 and for different types of pre-existing background noise錛 optimal distributions are determined for the added noise in order to improve the performance in estimation. With a single sensor錛 it is shown that the optimal added noise for reducing the MSE is actually a constant bias. However錛 with parallel arrays of such sensors錛 bona fide optimal added noise錛 no longer a constant bias錛 is shown to reduce the MSE. Moreover錛 it is found that the designed Bayesian estimators can benefit from the optimal added noise to effectively approach the performance of the minimum MSE estimator錛 even when the assembled sensors possess different quantization thresholds.，
