A recursive instrumental variable algorithm is proposed for estimating the structural parameters of a simultaneous equation model with autoregressive error terms. The choice of the instruments is discussed in order to...
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A recursive instrumental variable algorithm is proposed for estimating the structural parameters of a simultaneous equation model with autoregressive error terms. The choice of the instruments is discussed in order to obtain asymptotically efficient estimation of the structural parameters.
The parameter estimation problem in systems governed by sto chastic partial differential equations is discussed. A recursive algo rithm is derived to identify space-dependent parameters in a class of distributed syste...
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The parameter estimation problem in systems governed by sto chastic partial differential equations is discussed. A recursive algo rithm is derived to identify space-dependent parameters in a class of distributed systems driven by random inputs. The algorithm uses noisy observations taken over a finite number of equidistant observation points located in a spatial domain. The estimates obtained are r.m.s. - optimal due to the assumptions about the original system and the noise. Simula tion studies reveal good convergence of the algorithm. This algorithm was computer realized for parabolic, hyperbolic, and the Helmholtz equa tions. Simulation results show its undisputable advantages in compare to the algorithm of Kubrusly and Curtain derived for the same situation, since it lends itself more readily to digital computer realization and the estimates obtained converge at a faster rate. For systems with con stant parameters the computation procedure is much simplified.
The purpose of this paper is to study the boundedness of the tracking position error of robot controls based on the computed-torque method. It is seen that the nature of the input vector bears heavily on the results: ...
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The purpose of this paper is to study the boundedness of the tracking position error of robot controls based on the computed-torque method. It is seen that the nature of the input vector bears heavily on the results: only resolved-acceleration input permits to null the error. The later part of the Paper deals with the robustness of the conventional computed-torque structure and in particular, with a robust recursive control algorithm for robots proposed in a previous paper
The quadratic approximation is a three dimensional analogue of the two dimensional Padé approximation. A determinantal expression for the polynomial coefficients of the quadratic approximation is given. A recursi...
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The quadratic approximation is a three dimensional analogue of the two dimensional Padé approximation. A determinantal expression for the polynomial coefficients of the quadratic approximation is given. A recursive algorithm for the construction of these coefficients is derived. The algorithm constructs a table of quadratic approximations analogous to the Padé table of rational approximations.
A new recursive algorithm for adaptive Kalman filtering is proposed. The signal state-space model and its noise statistics are assumed to depend on an unknown parameter taking values in a subset [', '] of Rs. ...
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A new recursive algorithm for adaptive Kalman filtering is proposed. The signal state-space model and its noise statistics are assumed to depend on an unknown parameter taking values in a subset [', '] of Rs. The parameter is estimated recursively using the gradient of the innovation sequence of the Kalman filter. The unknown parameter is replaced by its current estimate in the Kalman-filtering algorithm. The asymptotic properties of the adaptive Kalman filter are discussed.
A recursive algorithm for the construction of the generalized form of the interpolating rational function is derived. This generalization of the Neville-Aitken algorithm constructs a table of all possible rational int...
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A recursive algorithm for the construction of the generalized form of the interpolating rational function is derived. This generalization of the Neville-Aitken algorithm constructs a table of all possible rational interpolants in implicit form. The algorithm may be simply modified so that it does not break down when a singularity occasionally appears. The coefficients of the interpolant and the evaluation of the interpolant at an arbitrary point may be easily calculated.
This paper presents a new method of converting a curve into chain-code representation. At every step of chain encoding, a predictive searching is conducted so that an optimal code direction is determined. Optimization...
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This paper presents a new method of converting a curve into chain-code representation. At every step of chain encoding, a predictive searching is conducted so that an optimal code direction is determined. Optimization is performed on the basis of a minimum mean-square-error criterion. This approach works very well for complex geometrical configuration with overlapping, crossing, and touching characteristics. We have applied this method with great success to computer analysis of chromosomes.
A recursive algorithm of stochastic approximation type is derived for the estimation of space-dependent parameters in a class of distributed parameter systems driven by random inputs. The algorithm uses noisy observat...
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A recursive algorithm of stochastic approximation type is derived for the estimation of space-dependent parameters in a class of distributed parameter systems driven by random inputs. The algorithm uses noisy observations taken over at a finite number of discrete points located in the spatial domain. Stochastic convergence of the estimates is proved. Simulation studies illustrate the good convergence property of the algorithm. The algorithm is much more simple both in structure and implementation and less restrictive on system structure to apply the algorithm, compared to the algorithm of Kubrusly and Curtain (1977).
This paper describes an algorithm which builds a ``Peano scanning,"" i.e., the reciprocal mapping, from [0, 1]n to [0, 1], of the well-known ``Peano curve."" This Peano scanning is applied to a set...
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This paper describes an algorithm which builds a ``Peano scanning,"" i.e., the reciprocal mapping, from [0, 1]n to [0, 1], of the well-known ``Peano curve."" This Peano scanning is applied to a set of points in [0, 1]n and gives a one-dimensional image of it. Several applications of this technique have already been developed and are presented in this paper.
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