In this paper, we address the problem of blind extraction and separation of a continuous chaotic signal from a linear mixture consisting of some chaotic signal and/or random signals. The problem of blind extraction is...In this paper, we address the problem of blind extraction and separation of a continuous chaotic signal from a linear mixture consisting of some chaotic signal and/or random signals. The problem of blind extraction is firstly formulated as a problem of the synchronization-based parameter estimation. Then an efficient least square based parameter estimation method is introduced to determine the desired extracting vector. The proposed blind signal extraction scheme is applicable to blind separation of chaotic signals by formulating the separation problem as the extraction of each chaotic source. Numerical simulation shows that the proposed approach can blindly extract and separate the desired chaotic signals and it is also robust to measurement noise.展开更多
目的系统评价急性缺血性卒中(AIS)患者卒中相关性肺炎(SAP)风险预测模型。方法检索Web of Science、Cochrane Library、PubMed、Embase、中国知网、中国生物医学文献数据库、维普网、万方数据知识服务平台发表的有关AIS患者SAP风险预测...目的系统评价急性缺血性卒中(AIS)患者卒中相关性肺炎(SAP)风险预测模型。方法检索Web of Science、Cochrane Library、PubMed、Embase、中国知网、中国生物医学文献数据库、维普网、万方数据知识服务平台发表的有关AIS患者SAP风险预测模型的开发研究,检索时限为各数据库建库至2023-08-30。由两名研究人员进行文献筛选及数据提取,并采用预测模型偏倚风险评估工具(PROBAST)评价纳入文献的质量。结果最终纳入文献15篇,共构建了24个模型,本研究仅选择各文献中性能表现最佳的模型。在模型性能表现方面,所有模型预测AIS患者发生SAP的AUC为0.739~0.966;7篇文献报道了模型的校准方法;在模型验证方法方面,5篇文献仅进行了内部验证,2篇文献仅进行了外部验证,2篇文献同时进行了内部验证和外部验证。文献质量评价结果显示,15篇文献均为高偏倚风险;6篇文献为高适用性风险,9篇文献为低适用性风险。结论现有AIS患者SAP风险预测模型具有良好的区分度,但其校准度尚不明确,偏倚风险较高,适用性一般,未来研究人员应参照PROBAST构建性能更好的AIS患者SAP风险预测模型。展开更多
The self-cascade(SC) method is an effective technique for chaos enhancement and complexity increasing in chaos maps.Additionally, the controllable self-cascade(CSC) method allows for more accurate control of Lyapunov ...The self-cascade(SC) method is an effective technique for chaos enhancement and complexity increasing in chaos maps.Additionally, the controllable self-cascade(CSC) method allows for more accurate control of Lyapunov exponents of the discrete map. In this work, the SC and CSC systems of the original map are derived, which enhance the chaotic performance while preserving the fundamental dynamical characteristics of the original map. Higher Lyapunov exponent of chaotic sequences corresponding to higher frequency are obtained in SC and CSC systems. Meanwhile, the Lyapunov exponent could be linearly controlled with greater flexibility in the CSC system. The verification of the numerical simulation and theoretical analysis is carried out based on the platform of CH32.展开更多
基金Supported by the National Natural Science Foundation of China (No.60472059)the Aeronautical Science Foundation of China (2008ZC 52026)
文摘In this paper, we address the problem of blind extraction and separation of a continuous chaotic signal from a linear mixture consisting of some chaotic signal and/or random signals. The problem of blind extraction is firstly formulated as a problem of the synchronization-based parameter estimation. Then an efficient least square based parameter estimation method is introduced to determine the desired extracting vector. The proposed blind signal extraction scheme is applicable to blind separation of chaotic signals by formulating the separation problem as the extraction of each chaotic source. Numerical simulation shows that the proposed approach can blindly extract and separate the desired chaotic signals and it is also robust to measurement noise.
文摘目的系统评价急性缺血性卒中(AIS)患者卒中相关性肺炎(SAP)风险预测模型。方法检索Web of Science、Cochrane Library、PubMed、Embase、中国知网、中国生物医学文献数据库、维普网、万方数据知识服务平台发表的有关AIS患者SAP风险预测模型的开发研究,检索时限为各数据库建库至2023-08-30。由两名研究人员进行文献筛选及数据提取,并采用预测模型偏倚风险评估工具(PROBAST)评价纳入文献的质量。结果最终纳入文献15篇,共构建了24个模型,本研究仅选择各文献中性能表现最佳的模型。在模型性能表现方面,所有模型预测AIS患者发生SAP的AUC为0.739~0.966;7篇文献报道了模型的校准方法;在模型验证方法方面,5篇文献仅进行了内部验证,2篇文献仅进行了外部验证,2篇文献同时进行了内部验证和外部验证。文献质量评价结果显示,15篇文献均为高偏倚风险;6篇文献为高适用性风险,9篇文献为低适用性风险。结论现有AIS患者SAP风险预测模型具有良好的区分度,但其校准度尚不明确,偏倚风险较高,适用性一般,未来研究人员应参照PROBAST构建性能更好的AIS患者SAP风险预测模型。
基金supported by the National Natural Science Foundation of China (Grant No. 61871230)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions。
文摘The self-cascade(SC) method is an effective technique for chaos enhancement and complexity increasing in chaos maps.Additionally, the controllable self-cascade(CSC) method allows for more accurate control of Lyapunov exponents of the discrete map. In this work, the SC and CSC systems of the original map are derived, which enhance the chaotic performance while preserving the fundamental dynamical characteristics of the original map. Higher Lyapunov exponent of chaotic sequences corresponding to higher frequency are obtained in SC and CSC systems. Meanwhile, the Lyapunov exponent could be linearly controlled with greater flexibility in the CSC system. The verification of the numerical simulation and theoretical analysis is carried out based on the platform of CH32.
