This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-thresho...This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.展开更多
针对帧内实施可逆水印造成误差传播的问题,基于高效视频编码(High Efficiency Video Coding,HEVC)标准,提出一种用于消除帧内误差传播的可逆水印算法。算法充分考虑了HEVC新的编码特性,对帧内嵌入水印后的误差传播情况进行了分析,随后...针对帧内实施可逆水印造成误差传播的问题,基于高效视频编码(High Efficiency Video Coding,HEVC)标准,提出一种用于消除帧内误差传播的可逆水印算法。算法充分考虑了HEVC新的编码特性,对帧内嵌入水印后的误差传播情况进行了分析,随后给出了在帧内4×4预测单元中嵌入水印后不会引起误差传播的条件;最后选出满足条件的4×4系数块,采用"和不变"方法将水印自适应地嵌入其量化离散正弦变换系数中。出于减小码率增长的考虑,全0系数块不嵌入水印。实验结果表明,该算法能够有效地消除帧内由嵌入水印引起的误差传播,从而减小视觉失真。同时,算法对码率的影响也较小。展开更多
基金This work was supported by the National Natural Science Foundation of China(62076025).
文摘This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm(M-AM-SGRPIA)for a class of single input single output(SISO)linear output error models with multi-threshold quantized observations.It proves the convergence of the designed algorithm.A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output(SIMO)or SISO nonlinear systems,and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system.The system input design is accomplished using the measurement technology of random repeatability test,and the probabilistic characteristic of the explicit metric value is employed to estimate the implicit metric value of the pattern class variable.A modified auxiliary model stochastic gradient recursive algorithm(M-AM-SGRA)is designed to identify the model parameters,and the contraction mapping principle proves its convergence.Two numerical examples are given to demonstrate the feasibility and effectiveness of the achieved identification algorithm.
文摘针对帧内实施可逆水印造成误差传播的问题,基于高效视频编码(High Efficiency Video Coding,HEVC)标准,提出一种用于消除帧内误差传播的可逆水印算法。算法充分考虑了HEVC新的编码特性,对帧内嵌入水印后的误差传播情况进行了分析,随后给出了在帧内4×4预测单元中嵌入水印后不会引起误差传播的条件;最后选出满足条件的4×4系数块,采用"和不变"方法将水印自适应地嵌入其量化离散正弦变换系数中。出于减小码率增长的考虑,全0系数块不嵌入水印。实验结果表明,该算法能够有效地消除帧内由嵌入水印引起的误差传播,从而减小视觉失真。同时,算法对码率的影响也较小。
