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Houda Daoud Sawssen Lahiani Samir Ben Salem Mourad Loulou 《International Journal of Electronics》2020,107(4):659-682
ABSTRACTWith the aggressive scaling of integrated circuit technology, parametric estimation is a critical task for designers who looked for solutions to the challenges of some Nanoscale CMOS parameters. This paper presented the prediction of primary parameters of CMOS transistor for 16 nm to 10 nm process nodes using both of Bisquare Weights (BW) method and a novel recursive least squares (RLS) parameter estimation algorithm. The proposed RLS algorithm consists of the minimisation of a quadratic criterion relating to the prediction error in order to attain the best estimated parameters of the developed mathematical model. The obtained results thanks to the proposed RLS algorithm were better than those reached using the BW method. Comparisons between Predictive Technology Model (PTM) data and parameters estimated with RLS algorithm were made to check the validity and the consistency of the proposed algorithm. These predicted primary parameters were helpful to estimate and to optimise the performances of the Variable Gain Amplifier (VGA) which was a basic circuit element with a key role in the design of new upcoming receivers. 相似文献
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针对建模误差对预测控制的影响,提出一种基于神经网络预测误差修正的广义预测控制算法.被控对象采用递推最小二乘法(RLS)辨识其线性模型;预测误差由前馈神经网络进行建模,并用Powell快速优化方法训练网络.该方法无需预先离线训练神经网络,即可投入闭环控制,并具有理想的稳定性、跟踪性能和鲁棒性.仿真结果表明该算法能够有效地控制复杂系统. 相似文献
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Mixed norm regularized recursive total least squares for group sparse system identification 下载免费PDF全文
Jun‐seok Lim Hee‐Suk Pang 《International Journal of Adaptive Control and Signal Processing》2016,30(4):664-673
A mixed lp,0‐regularized recursive total least squares (RTLS) algorithm is considered for group sparse system identification. Regularized recursive least squares (RLS) has been successfully applied to group sparse system identification; however, the estimation performance in regularized RLS‐based algorithms deteriorates when both input and output are contaminated by noise (the error‐in‐variables problem). We propose an lp,0‐RTLS algorithm to handle group sparse system identification with errors‐in‐variables. The proposed algorithm is an RLS‐like solution that utilizes lp,0‐regularization. The proposed algorithm provides excellent performance as well as reduces the required complexity by effective inversion matrix handling. Simulations demonstrate the superiority of the proposed lp,0‐regularized RTLS for a group sparse system identification setting. Copyright © 2015 John Wiley & Sons, Ltd. 相似文献
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In this paper, the Artificial Bee Colony (ABC) algorithm is applied to construct Adaptive Noise Canceller (ANC) for electroencephalogram (EEG)/Event Related Potential (ERP) filtering with modified range selection, described as Bounded Range ABC (BR-ABC). ERP generated due to hand movement is filtered through Adaptive Noise Canceller (ANC) from the EEG signals. ANCs are also implemented with Least Mean Square (LMS) and Recursive Least Square (RLS) algorithm. Performance of the algorithms is evaluated in terms of Signal-to-Noise Ratio (SNR) in dB, correlation between resultant and template ERP, and mean value difference. Testing of their noise attenuation capability is done on contaminated ERP with white noise at different SNR levels. A comparative study of the performance of conventional gradient based methods like LMS, RLS, and ABC algorithm is also made which reveals that ABC algorithm gives better performance in highly noisy environment. 相似文献
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基于RLS的永磁同步电机离线参数辨识研究 总被引:1,自引:0,他引:1
为了获取准确的电机参数以提高电机驱动系统的控制性能,针对面贴式永磁同步电机,通过直流注入的方式,采用递推最小二乘法(RLS)对定子电阻和电感进行离线辨识。辨识方法为在α轴注入阶跃激励电压在稳态阶段辨识电阻,在阶跃过渡过程中辨识电感。辨识中通过补偿驱动器因死区时间及IGBT、续流二极管导通压降造成的电压误差来提高电阻辨识结果的准确性。并通过加入基值电压的方式消除这些因素对电感辨识的影响。最后,通过仿真和实验验证了所提方法的正确性和实用性。 相似文献
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本文介绍了阳离子表面活性剂,两性离子表面活性剂,非离子表面活性剂与DNA的相互作用.通过共振光散射(RLS),荧光显微镜,浊度法等方法测定表面活性剂与DNA之间的作用.试验发现:阳离子型表面活性剂分子可能通过静电作用和疏水作用,以DNA分子为模板在其表面形成了聚集,这种聚集增强了体系的RLS响应.当pH值低时,两性表面... 相似文献
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提出一种基于人类听觉特性的自适应小波滤波算法。该方法用听觉感知小波变换对含噪语音信号进行小波分解,这样可以保证对信号频率和幅值的听觉特性,将经听觉感知小波变换所分离出来的噪声成分作为自适应滤波器的输入。通过采用递推最小二乘算法从而实现信噪分离的最佳滤波,以保证去除信号中的相关噪声。结果表明,该方法能实现非平稳信号在同频段对噪声成分和有用信号的最佳估计,提高了语音的清晰度和可懂度。 相似文献