欧盟正式颁布实施《一般数据保护条例》(General Data Protection Regulation,GDPR)至今,各成员国企业在其影响下已纷纷采取措施适应GDPR的合规要求,但还是面临着难以跟进监管要求、合规成本高昂、违规成本高昂等巨大挑战。GDPR基于其...欧盟正式颁布实施《一般数据保护条例》(General Data Protection Regulation,GDPR)至今,各成员国企业在其影响下已纷纷采取措施适应GDPR的合规要求,但还是面临着难以跟进监管要求、合规成本高昂、违规成本高昂等巨大挑战。GDPR基于其宽泛的管辖权,也给我国涉欧企业带来了数据合规挑战。面对这一挑战,我国涉欧企业应将其视为机遇而非负担,积极构建数据合规路径,提升企业的核心竞争力。基于此,主要从以下几个方面构建数据合规之路:一是构建成熟的数据合规组织体系,二是建立完备的数据合规防范体系,三是形成健全的数据风险应对体系,四是积极运用智能化方式推进数据合规建设。展开更多
In this study, hybrid computational frameworks are developed for active noise control（ANC） systems using an evolutionary computing technique based on genetic algorithms（GAs） and interior-point method（IPM）, follo...In this study, hybrid computational frameworks are developed for active noise control（ANC） systems using an evolutionary computing technique based on genetic algorithms（GAs） and interior-point method（IPM）, following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima（LM）. This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.展开更多
文摘欧盟正式颁布实施《一般数据保护条例》(General Data Protection Regulation,GDPR)至今,各成员国企业在其影响下已纷纷采取措施适应GDPR的合规要求,但还是面临着难以跟进监管要求、合规成本高昂、违规成本高昂等巨大挑战。GDPR基于其宽泛的管辖权,也给我国涉欧企业带来了数据合规挑战。面对这一挑战,我国涉欧企业应将其视为机遇而非负担,积极构建数据合规路径,提升企业的核心竞争力。基于此,主要从以下几个方面构建数据合规之路:一是构建成熟的数据合规组织体系,二是建立完备的数据合规防范体系,三是形成健全的数据风险应对体系,四是积极运用智能化方式推进数据合规建设。
文摘In this study, hybrid computational frameworks are developed for active noise control（ANC） systems using an evolutionary computing technique based on genetic algorithms（GAs） and interior-point method（IPM）, following an integrated approach, GA-IPM. Standard ANC systems are usually implemented with the filtered extended least mean square algorithm for optimization of coefficients for the linear finite-impulse response filter, but are likely to become trapped in local minima（LM）. This issue is addressed with the proposed GA-IPM computing approach which is considerably less prone to the LM problem. Also, there is no requirement to identify a secondary path for the ANC system used in the scheme. The design method is evaluated using an ANC model of a headset with sinusoidal, random, and complex random noise interferences under several scenarios based on linear and nonlinear primary and secondary paths. The accuracy and convergence of the proposed scheme are validated based on the results of statistical analysis of a large number of independent runs of the algorithm.
