This paper proposes the 1-affine transformation for rectangular video images. In the proposed method, each frame of the input rectangular video images is partitioned into small square subimages, which are stored separ...
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The Cellular Neural Network (CNN) has been widely used for associative memory, but has a problem called indeterminate cell. In this paper, we have proposed a CNN considering hysteresis characteristic as one of the met...
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ISBN:
(纸本)0780362535
The Cellular Neural Network (CNN) has been widely used for associative memory, but has a problem called indeterminate cell. In this paper, we have proposed a CNN considering hysteresis characteristic as one of the methods to avoid the indeterminate cell problem, and confirmed its effectiveness in simulations.
This paper considers the problem of impulse response identification for a linear sampled-data system where the input signal is held constantly within a multiple of the sampling period of the output signal. To improve ...
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This paper considers the problem of impulse response identification for a linear sampled-data system where the input signal is held constantly within a multiple of the sampling period of the output signal. To improve identification accuracy, this paper proposes a new identification approach by employing the Haar scaling and wavelet functions. At first, we point out that the discrete-time impulse response of a linear system with zero-order hold (ZOH) input is actually the piecewise-constant approximation of the continuous-time impulse response. Based on the close relation between piecewise-constant approximation with Haar scaling and wavelet functions, a hierarchical identification procedure is proposed which identifies the system impulse response from a coarse resolution level to a fine resolution level successively. At each resolution level, the BIC is utilized to determine the length of the decomposed impulse response in the corresponding subspace, so that some redundant parameters in the high frequency-domain which are sensitive to the noise effects are discarded. Since the identified impulse response model is not smooth when it is represented by some Haar scaling functions of different widths, we can replace each Haar scaling function in the preidentified impulse response model by a Gaussian basis function with corresponding position and width. Then an improved identification method is also proposed to achieve smooth continuous-time impulse response model from sampled data. It is shown through simulation study that the proposed methods yield accurate estimate of the impulse response even in the ill-conditioned cases.
In the last two decades, linear-in-parameter nonlinear polynomial models for NARX (Nonlinear Auto-Regressive with eXogenous input) systems have received considerable attention. The keypoint of polynomial model identif...
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In the last two decades, linear-in-parameter nonlinear polynomial models for NARX (Nonlinear Auto-Regressive with eXogenous input) systems have received considerable attention. The keypoint of polynomial model identification is how to select a set of significant terms employed to approximate the NARX system under study, from a large number of candidates. To this end, the orthogonal least-squares method which is a local search procedure, and the genetic algorithm approach which has a high potential for global optimization have been proposed in the literature. However, it is considered that the methods reported so far in the literature still lack potential to identify the polynomial models with relatively high-order. This limits the applicability of the polynomial models to the real complex nonlinear systems. Motivated by this fact, in this paper, a new genetic algorithm approach to polynomial model identification is proposed. Our contribution in this paper is to introduce a novel hierarchical encoding technique which is considered to be suitable to the structure of the polynomial models. Simulation and application results are also included to verify the efficiency of the proposed identification algorithm.
<正>Cellular Neural Network has been widely used for associative memory,but has a problem called indeterminate *** this paper,we have proposed CNN considering hysteresis characteristic as one of the methods to avoid...
<正>Cellular Neural Network has been widely used for associative memory,but has a problem called indeterminate *** this paper,we have proposed CNN considering hysteresis characteristic as one of the methods to avoid the indeterminate cell, and confirmed its effectiveness in simulations.
For high sensitivity measurements of isotope concentration-ratios of trace-level gas mixture, particularly including carbon dioxide isotopes, we tested a /sup 12/CO/sub 2/-/sup 13/CO/sub 2/ composite laser system cont...
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For high sensitivity measurements of isotope concentration-ratios of trace-level gas mixture, particularly including carbon dioxide isotopes, we tested a /sup 12/CO/sub 2/-/sup 13/CO/sub 2/ composite laser system containing intracavity absorption cells. Sensitivity enhancement obtainable by the intracavity absorption cell configuration is examined theoretically. /sup 13/CO/sub 2/ in atmospheric air is readily detected and minimum detectable concentration by the present system was estimated to be 70 ppb.
The exact location of the Steiner point in the Steiner minimum tree (SMT) for three given points in the λ-geometry plane is shown. SMTs are important to layout of LSIs and printed boards in rectilinear geometry and t...
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This paper deals with the estimation of an unknown process transfer function in the presence of colored measurement noise. A three-step estimation procedure has been previously developed for transfer functions, the de...
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This paper deals with the estimation of an unknown process transfer function in the presence of colored measurement noise. A three-step estimation procedure has been previously developed for transfer functions, the delay steps and the orders of which are known in advance. The procedure is extended to deal with transfer functions with unknown delay steps and orders. The auto-correlation function of the error between the process output and model output is utilized for evaluating the model fitness. The effectiveness of the proposed method is demonstrated by a simulation study using a sample set of data in MATLAB.
For high sensitivity measurements of isotope concentration-ratios of trace-level gas mixture,particulaly including carbon dioxide isotopes,we tested a CO-CO composite laser system containingintracavity absorption *** ...
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For high sensitivity measurements of isotope concentration-ratios of trace-level gas mixture,particulaly including carbon dioxide isotopes,we tested a CO-CO composite laser system containingintracavity absorption *** enhancement obtainable by the intracavity absorption cellconfiguration is examined *** in atmospheric air is readily detected and minimumdetectable concentration by the present system was estimated to be 70 *** isotopes,we tested a CO-CO composite laser system containingintracavity absorption *** enhancement obtainable by the intracavity absorption cellconfiguration is examined *** in atmospheric air is readily detected and minimumdetectable concentration by the present system was estimated to be 70 ppb.
Decision support systems that help physicians are becoming very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate...
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ISBN:
(纸本)0967335515
Decision support systems that help physicians are becoming very important part of medical decision making. They are based on different models and the best of them are providing an explanation together with an accurate, reliable and quick response. One of the most viable among decision-making models is the concept of decision trees, already successfully used for many medical decision making purposes. Although effective and reliable, the traditional decision tree construction approach still contains several deficiencies. Therefore we decided to develop and compare several decision supporting models, each of them built with different discretization of attributes and decision classes. For the construction of decision trees we used MtDeciT, in our laboratory developed tool for building decision trees using the classical induction method. All solutions were evolved for determining the influence of basic properties of child and his/her parents to length of successful breastfeeding. A comparison between developed models and obtained results has shown that the way of discretization obviously plays a great role in the reliable and accurate real-world medical decision making.
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