An iterative approach is developed for reconstructing electrical parameters of stratified lossy media using time-domain reflection and/or transmission data. The finite-difference time-domain (FDTD) method is used. Num...
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An iterative approach is developed for reconstructing electrical parameters of stratified lossy media using time-domain reflection and/or transmission data. The finite-difference time-domain (FDTD) method is used. Numerical simulations are performed to reconstruct the images of lossy dielectric slabs with high-contrast permittivity. (C) 1997 John Wiley & Sons, Inc.
A new cell immobilization method based on the replacement of KCl by KCl+chitosan as the gelling agent was developed. The experimental results showed that through addition of chitosan into gelling agent, the mechanica...
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A new cell immobilization method based on the replacement of KCl by KCl+chitosan as the gelling agent was developed. The experimental results showed that through addition of chitosan into gelling agent, the mechanical strength and the thermal stability of the carrageenan gel were greatly improved. The new immobilization method was used to entrap a chlorophenol degrading microorganism. The immobilized microbial cells were applied for chlorophenol biodegradation. The experiments demonstrated that immobilized cells exhibit a higher bioactivity in the degradation of chlorophenol than free cells.
In the field of system identification, the coefficients of a digital filter, which are used to illustrate the transfer function of a system, are often fixed by known input and output signal sequences. The least mean s...
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In the field of system identification, the coefficients of a digital filter, which are used to illustrate the transfer function of a system, are often fixed by known input and output signal sequences. The least mean square (LMS) adaptive algorithm is often used for its small computational requirement and convergence ***, the input or the output signal sequence often contains directive current (DC) components. What is the effect of the DC component upon the adaptive algorithm? This is just the main objective of this note. Here we propose an improved LMS adaptive algorithm with varying stepsize, which is based on the DC components analyzing.
<正>In this paper,we first discuss the structure, principle and learning algorithm of CMAC neural network model.A new adaptive quantization method based on competitive learning is then proposed to quantimize the inp...
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<正>In this paper,we first discuss the structure, principle and learning algorithm of CMAC neural network model.A new adaptive quantization method based on competitive learning is then proposed to quantimize the inputs of CMAC according to the degree of variations of the approximated *** analysis and simulation results show that with the input layer using this algorithm CMAC can approximate more accurately and efficiently than the original model using equal-size quantization method.
The design of structured mathematical models of processes in a certain level of abstraction defined by the given task appears to be difficult and time consuming even for experienced experts. This paper reports on a ne...
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It is proved that all monic-polynomials of order n with roots lying in some open region on the complex plane forms a simply connected set in the polynomial parameter space. Based on this result, edge theorems for D-st...
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ISBN:
(纸本)0780335902
It is proved that all monic-polynomials of order n with roots lying in some open region on the complex plane forms a simply connected set in the polynomial parameter space. Based on this result, edge theorems for D-stability of general polyhedrons of polynomials and boundary theorems for D-stability of compact sets of polynomials are obtained. Different from previous ones, our edge theorems and boundary theorems do not require the convexity or the connectivity of the set of polynomials. Moreover, our boundary theorem for families of polynomials with dependent coefficients does not require the coefficient dependency relation to be affine.
作者:
Uchida, MNakano, KFukuoka Institute of Technology
Fukuoka Japan 811-02 [?]Graduated from Kyushu University in 1958 and received his Dr. of Eng. degree from there. He joined Kyushu Electric Power Co.
Inc. and there he engaged in the planning construction operation and maintenance of thermal power plants as the technical staffer section chief assistant manager and superintendent. Since 1994 he has been a Professor in the Department of Electrical Engineering Fukuoka Institute of Technology Japan. His main interest is in the application of modern control theory to actual plants. For his contribution to this field he was awarded the Okochi Memorial Technical Prize and SICE Technical Prize in 1980. He is a member of the Society of Institute of Instrument and Control Engineers of Japan (SICE).
A new concept to achieve an ideal transient control performance is described. It is also possible to examine control performance on the frequency domain. Generally speaking, better control performance will be realized...
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A new concept to achieve an ideal transient control performance is described. It is also possible to examine control performance on the frequency domain. Generally speaking, better control performance will be realized by using more exact information on the plant. A simulator should be built that has both correct initial values of state variables and parameters on dominant parts of the plant. The internal states of the simulator are used to represent the internal states of the plant, and control input is synthesized with the internal states of the simulator and the plant output. Using information on the simulator allows an ideal control performance at a dominant frequency area to be obtained in spite of the existence of unmodeled dynamics at a higher frequency domain. This control system is called simulator-based foresight control (SFC), and is available for both nonlinear and time-varying plants.
The article at hand describes an integrating system for the intelligent control of complex bio technological processes including automatic modelling and model based control strategy generation. Starting with a summary...
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The article at hand describes an integrating system for the intelligent control of complex bio technological processes including automatic modelling and model based control strategy generation. Starting with a summary of previously achieved results, some new approaches that provide better transparency to process engineers and operators are discussed. This includes aspects of self-organizing generation of structured dynamic nonlinear process models based upon the ideas of genetic programming as well as the transparent generation of fuzzy rules in a particular NeuroFuzzy approach. The latter is used for the classification of physiological states during batch and fed-batch fermentations and for the long time strategy generation to optimize the achievable product yield.
In this paper, an overview of the structure and learning algorithm of the Elman neural network is first presented. A modified Elman network is then proposed by adding new adjustable weights that connect the context no...
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In this paper, an overview of the structure and learning algorithm of the Elman neural network is first presented. A modified Elman network is then proposed by adding new adjustable weights that connect the context nodes with output nodes. Convergence speed of the two network structures are compared. A parallel dynamic system identification scheme based on the modified Elman network is set up as well. Theoretical analysis and simulation results show that our improved neural network-based identification method has the advantage of identifying both linear and nonlinear dynamic systems without any prior knowledge of their orders and structures.
In the analysis of a general linear system including the electromagnetic wave transmission systems, it is often necessary to derive system functions such as the immittance function and the transfer function from the f...
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In the analysis of a general linear system including the electromagnetic wave transmission systems, it is often necessary to derive system functions such as the immittance function and the transfer function from the frequency characteristics. In solving these problems, it is possible to use the Herglotz-Cauer theorem for the immittance function and Hosono's theorem for the transfer function. In these theorems, it is necessary to calculate integrals on the frequency when the system function is derived. There are a limited number of cases that can be solved analytically. However, when Hosono's theorem is combined with the fast inversion of Laplace transform (FILT), it is predicted that such a combination is a powerful tool for analyzing the transient phenomena of the electromagnetic wave propagating in plasma, wave-guides, and optical fibers. To confirm such a prediction, the transient phenomena of the electromagnetic wave propagating in a plasma were analyzed as an example so that the effectiveness was supported.
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