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RISS 인기검색어
- 검색키워드
- 저자 : Jinchun Hu (검색결과 3 건)
- 무료
- 기관 내 무료
- 유료
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A Variable Step-Size SIG Algorithm for Realizing the Optimal Adaptive FIR Filter
Badong Chen,Yu Zhu,Jinchun Hu,Jose C. Principe 제어·로봇·시스템학회 2011 International Journal of Control, Automation, and Vol.9 No.6
In this paper, we propose an optimal adaptive FIR filter, in which the step-size and error nonlinearity are simultaneously optimized to maximize the decrease of the mean square deviation (MSD) of the weight error vector at each iteration. The optimal step-size and error nonlinearity are derived, and a variable step-size stochastic information gradient (VS-SIG) algorithm is developed to approximately implement the optimal adaptation. Simulation results indicate that this new algorithm achieves faster convergence rate and lower misadjustment error in comparison with other adaptive algorithms.
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Adaptive Filtering under Minimum Information Divergence Criterion
Badong Chen,Yu Zhu,Jinchun Hu,Zengqi Sun 제어·로봇·시스템학회 2009 International Journal of Control, Automation, and Vol.7 No.2
Traditional filtering theory is always based on optimization of the expected value of a suitably chosen function of error, such as the minimum mean-square error (MMSE) criterion, the minimum error entropy (MEE) criterion, and so on. None of those criteria could capture all the probabilistic in-formation about the error distribution. In this work, we propose a novel approach to shape the probabil-ity density function (PDF) of the errors in adaptive filtering. As the PDF contains all the probabilistic information, the proposed approach can be used to obtain the desired variance or entropy, and is ex-pected to be useful in the complex signal processing and learning systems. In our method, the informa-tion divergence between the actual errors and the desired errors is chosen as the cost function, which is estimated by kernel approach. Some important properties of the estimated divergence are presented. Also, for the finite impulse response (FIR) filter, a stochastic gradient algorithm is derived. Finally, simulation examples illustrate the effectiveness of this algorithm in adaptive system training.
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Qiang Li,Yu Zhu,Dengfeng Xu,Jinchun Hu,Wei Min,Lacheng Pang 대한기계학회 2013 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.27 No.3
The most important characteristic of a passive vibration isolator is its natural frequency and load capacity. The vibration isolation performance of a passive vibration isolator in low input frequencies is considerably improved by reducing its natural frequency. This paper presents a negative stiffness magnetic suspension vibration isolator (NSMSVI) using a magnetic spring combined with a rubber membrane to obtain lower natural frequency. To study the vibration isolation performance of the NSMSVI, the stretching force of the rubber membrane is measured through experiments. The stiffness of the rubber membrane comes from the derivative of the stretching force. A parametric study of load capacity, axial magnetic stiffness, and natural frequency of the magnetic spring is also performed. Consequently, as a case study, the size dimensions of the magnetic spring are determined. An NSMSVI table is set up for experimental validation, after which the transmissibility curves of the NSMSVI are calculated and tested. Experimental results show that the lowest natural frequency of the NSMSVI reaches 1.5 Hz with a maximum attenuation of -40 dB between 0 Hz and 100 Hz, whereas the NSMSVI has the maximum load capacity at the lowest stiffness. This paper essentially provides an efficient method to construct a negative stiffness vibration isolator for practical applications.
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