Dingguo Chen

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In this paper we present an accurate technique for automatic detection of fiducial markers in 3d brain images so that fully automatic landmark-based coregistration can be implemented. In our tests, our approach detected successfully 429 out of 430 fiducial markers that can be recognized by human eyes. Thus, in landmarkbased image-registrations, our(More)
This paper attempts to present a neural inverse control design framework for a class of nonlinear multiple-input multiple-output (MIMO) system with uncertainties. This research effort is motivated by the following considerations: (a) An appropriate reference model that accurately represents the desired system dynamics is usually assumed to exist and to be(More)
BACKGROUND CASMIL aims to develop a cost-effective and efficient approach to monitor and predict deformation during surgery, allowing accurate, and real-time intra-operative information to be provided reliably to the surgeon. METHOD CASMIL is a comprehensive Image-guided Neurosurgery System with extensive novel features. It is an integration of various(More)
This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system (FES); the second is synergetic pattern recognition system (SPRS). Hough transform is proposed for feature extraction of unrecognized object, with(More)
It has been a common consensus that general techniques for stabilization of nonlinear systems are available only for some special classes of nonlinear systems. Control design for nonlinear systems with uncertain components is usually carried out on a per system basis, especially when physical control constraints, and certain control performance measures(More)
The derivation of a mathematical model from physical laws according to the use of the model (e.g., for control), is most basic here to determine the mathematical structure. For example, it is shown (Laszlo, 1972) that a close connection exists between dynamic identification of an environment and its control. System identification itself is a well developed(More)
In this paper, the practical possibility of function approximations through neural networks is discussed based on the result for the perfect function approximation which is established on the basis of the countable dense set. More practically, a neural network model is established in hope to match the given data set based on some criteria. Generally, when a(More)