http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Decay Rate Estimation of Continuous Time Series Using Instantaneous Lyapunov Exponent
Yusuke Totoki,Haruo Suemitsu,Takami Matsuo 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
The Lyapunov exponent give same a sure of the mean decay/divergence rates of the flows of nonlinear systems. However, the Lyapunov exponent needs an infinite time interval of flows and the Jacobi an matrix of system dynamics. In this paper, we propose an instantaneous decay that is a kind of generalized Lyapunov exponent and call the instantaneous Lyapunov exponent(ILE) with respect to adecay function. The instantaneous Lyapunov exponent is one of the measures that estimate the decay rates of flows of nonlinear systems by assign inga comparison functon and can apply as table system whose decay rate is slower than an exponential function.
Simultaneous Parameter and Input Estimation of Hindmarsh-Rose Neuron by Adaptive Observer
Yusuke Totoki,Ryuta Ito,Haruo Suemitsu,Takami Matsuo 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, we present an adaptive observer for a Hind marsh-Rose(HR) neuron with the membrane potential measurement under the as sumption that some of parameters in an individual HR neuron are known.Using the adaptive observers for a single HR neuron, we propose a simultaneous estimator of a parameter and the input current of a HR neuron. The procedure allows us to recover the internal states and to distinguish the firing patterns of the synaptically coupled HR neurons.
Adaptive Input Estimation of a Hodgkin-Huxley Neuron
Ryuta Ito,Yusuke Totoki,Haruo Suemitsu,Takami Matsuo 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, we propose an a daptive observer based on the HH model equations without any linearization method. The nonlinear adaptive observer based on the HH dynamic structure is proposed to estimate the internal states and the input current of a HH neuron. The input current is estimated as a slow-varying parameter using the adaptive parameter update law with a signum function. The MATLAB simulations demonstrate the estimation performance of the proposed adaptive observers.