The problem of identifying system parameters for time-invariant distributed parameter systems subject to unknown boundary conditions and initial conditions is investigated. An extension of the linear integral filter i...
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The problem of identifying system parameters for time-invariant distributed parameter systems subject to unknown boundary conditions and initial conditions is investigated. An extension of the linear integral filter is made for handling partial derivatives of multi-variable functions. In the noise-free case, applying the extended linear integral filter to the nonlinear partial differential equation leads to an integral equation, and then the unknown system parameters are obtained conveniently using an on-line least squares algorithm. In the noisy case, instrumental variables are introduced in the gradient of the criterion function, and the met hod of stochastic approximations (SA) is employed to obt ain consistent estimates. This method does not require as much information on the noise statistics as the bias-compensating SA methods. A number of illustrative numerical examples are also included.
Presents an effective recursive algorithm for computing multiplicative inverses in GF(2m), where m=2k, employing normal bases. The proposed algorithm requires m-1 cyclic shifts and two multiplications in GF (2m) and i...
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Presents an effective recursive algorithm for computing multiplicative inverses in GF(2m), where m=2k, employing normal bases. The proposed algorithm requires m-1 cyclic shifts and two multiplications in GF (2m) and in each subfield of GF(2m): GF(2m/2), GF(2m/4),. . ., GF (28) and GF(24)
For a system described by the triple (A9B9C) where the matrix A has a set of distinct eigenvalues and a wellconditionedmodal matrix, we propose measures of modal controllability and observability. The angles between t...
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Solution-Time and data-storage requirements for the solution of full linear systems have become increasingly unwieldy with problem growth. Two parallel solution algorithms are proposed that can greatly decrease the so...
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Solution-Time and data-storage requirements for the solution of full linear systems have become increasingly unwieldy with problem growth. Two parallel solution algorithms are proposed that can greatly decrease the solution time of full systems by employing multiple processes in the problem solution. Furthermore, the algorithms lend themselves to extremely efficient operation on disk resident problems because of benign demands on data transfer to and from disk. The basis for algorithms is LU decomposition with partial row pivoting.
This paper is concerned with the recursive estimation of autoregressive models, in particular the realtime determination of the order of such a specification. A model selection criterion based on the minimum descripti...
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This paper is concerned with the recursive estimation of autoregressive models, in particular the realtime determination of the order of such a specification. A model selection criterion based on the minimum description length principle due to Rissanen is discussed and strong consistency in the stationary situation is shown. Alternative criteria are also considered and modifications required to introduce forgetting when the procedures are implemented in the non-stationary case are presented. Some simulation evidence on the performance of the criteria when applied to stationary and non-stationary processes is given.
The paper describes the derivation, design and evaluation of a parameter-adaptive integrated controller for a turbogenerator. The control strategy is to minimise the variances between the outputs of the turbogenerator...
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The paper describes the derivation, design and evaluation of a parameter-adaptive integrated controller for a turbogenerator. The control strategy is to minimise the variances between the outputs of the turbogenerator and the outputs of a linear optimal predictor under all operating conditions. The design of the controller is based on an autoregressive moving-average model, and does not require any information about the parameters of the turbogenerator. A nonlinear feedback approach to the control strategy is achieved by a simple recursive algorithm, which can be implemented as an online real-time computer control scheme for a turbogenerator without persistent excitation of inputs. The performance of the adaptive controller depends on the successful design of the optimal predictor, which can be achieved by choosing suitable pole values. Results obtained using a detailed nonlinear simulation of a turbogenerator are presented.
Calculated reactance between relay point and fault represents an accurate estimation of fault distance when the fault resistance or the R/L ratios of the equivalent impedance at line ends are very small. When these co...
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Calculated reactance between relay point and fault represents an accurate estimation of fault distance when the fault resistance or the R/L ratios of the equivalent impedance at line ends are very small. When these conditions are not satisfied, a large error results in locating fault distance due to back-feed effect from the remote end. A new recursive algorithm for distance protection is developed, which accurately determines the fault location by predicting the back-feed current. The prediction needs estimated values of the remote end source impedance to be passed to the relay via a communication link. Trip decision is based on checking the evaluated fault location and its variation with time. The algorithm is validated by digitally simulating transmission lines with different fault conditions taking into consideration the reduction in the generator reactance after fault inception. Simulation results show a fault detection time of about one half-cycle.
A recursive method is developed for the solution of coupled algebraic Riccati equations and corresponding linear Nash strategies of weakly interconnected systems. It is shown that the given algorithm converges to the ...
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A recursive method is developed for the solution of coupled algebraic Riccati equations and corresponding linear Nash strategies of weakly interconnected systems. It is shown that the given algorithm converges to the exact solution with the rate of convergence ofO(ε2), where ε is a small coupling parameter. In addition, only low-order systems are involved in algebrdic computations; the amount of computations required does not grow per iteration and no analyticity assumption is imposed on the system coefficients.
作者：
HOU, HSElectronics and Optics Division
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The fast Hartley transform (FHT) is similar to the Cooley-Tukey fast Fourier transform (FFT) but performs much faster because it requires only real arithmetic computations compared to the complex arithmetic computatio...
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The fast Hartley transform (FHT) is similar to the Cooley-Tukey fast Fourier transform (FFT) but performs much faster because it requires only real arithmetic computations compared to the complex arithmetic computations required by the FFT. Through use of the FHT, discrete cosine transforms (DCT) and discrete Fourier transforms (DFT) can be obtained. The recursive nature of the FHT algorithm derived in this paper enables us to generate the next higher order FHT from two identical lower order FHT"s. In practice, this recursive relationship offers flexibility in programming different sizes of transforms, while the orderly structure of its signal flow-graphs indicates an ease of implementation in VLSI.
We describe an extension of the recursive algorithm of Howard (1972) and Krailo and Pike (1984) for computation of conditional maximum likelihood estimates in multiple logistic regression models for stratum-matched re...
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We describe an extension of the recursive algorithm of Howard (1972) and Krailo and Pike (1984) for computation of conditional maximum likelihood estimates in multiple logistic regression models for stratum-matched retrospective studies to the multivariate case involving polytomous disease states. APL procedures, suitable for a desktop computing environment, are provided and analyzed.
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