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Computer-Aided Diagnosis of Gastrointestinal Radiographs Using Adaptive Differential Filter
Nobumichi Nagano,Takami Matsuo 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
For improving detectability of the gastric lesions in the X-ray examinations, the computer image processing methods are studied in radiographs of gastric cancer lesions. We propose an adaptive differential filters to the edge detection. Moreover, the level set method is adopted to the segmentation. Furthermore, the numerical examples are carried out, using the case radiograph of the gastric intestines medical picture database produced by National Kyushu Cancer Center.
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.
Adaptive Back stepping Control for a Two-Wheeled Autonomous Robot
Tatsuya Nomura,Yuta Kitsuka,Haruo Suemitsu,Takami Matsuo 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, we deal with the backstepping control design of the two-wheeled inverted-pendulum-type autonomous robot, the e-nuvo-wheel, made in ZMP Inc.[5]. First, we derive a second-order motion equation of the angle and design an adaptive integral backstepping controller to stabilize the angle in the manner of the modeling in[1,3]. This controller requires the full-state measurements. In the output feedback case, the Kfilter or the observer backstepping is needed[7,8]. However, the structure of the controller becomes complicated. We have presented then on-model-based differentiator based on the adaptive update law citewada. Since the non-model-based differentiator does not need the knowledge of the dynamic structure of the signal, we can use it a save locity estimator for unknown nonlinear systems. Next, we replace the velocity measurement with the estimates by the non-model-based differentiator. Finally, simulation and experimental results for the proposed controller are presented.
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.