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This version is made available in accordance with publisher policies. Please cite only the published...
The Wiener–Kolmogorov principle of minimizing the mean square estimation error is discussed in the f...
This paper proposes a stochastic model to study the evolution of normal and excess weight population...
The purpose of this work is to present a new methodology for fitting Wiener networks to datasets wit...
The Wiener model is a block oriented model, having a linear dynamic system followed by a static nonl...
AbstractA statistical model for global optimization is constructed generalizing some properties of t...
To my husband System identication deals with the problem of constructing models of sys-tems from obs...
AbstractIt is well known that optimally stopping the sample mean W(t)t of a standard Wiener process ...
which permits unrestricted use, distribution, and reproduction in any medium, provided the original ...
Abstract: This paper describes a new algorithm for initializing and estimating Wiener-Hammerstein mo...
The Wiener model is a block oriented model, having a linear dynamic system followed by a static nonl...
It is shown that the commonly used adaptive algorithms are closely related to each other and can be ...
This work generalizes the Wiener-Kolmogorov theory of optimum linear filtering and prediction of sta...
This paper describes a new algorithm for initializing and estimating Wiener-Hammerstein models. The ...
We develop a tractable algorithms for finding the optimal power spectral density of the Gaussian inp...
This version is made available in accordance with publisher policies. Please cite only the published...
The Wiener–Kolmogorov principle of minimizing the mean square estimation error is discussed in the f...
This paper proposes a stochastic model to study the evolution of normal and excess weight population...
The purpose of this work is to present a new methodology for fitting Wiener networks to datasets wit...
The Wiener model is a block oriented model, having a linear dynamic system followed by a static nonl...
AbstractA statistical model for global optimization is constructed generalizing some properties of t...
To my husband System identication deals with the problem of constructing models of sys-tems from obs...
AbstractIt is well known that optimally stopping the sample mean W(t)t of a standard Wiener process ...
which permits unrestricted use, distribution, and reproduction in any medium, provided the original ...
Abstract: This paper describes a new algorithm for initializing and estimating Wiener-Hammerstein mo...
The Wiener model is a block oriented model, having a linear dynamic system followed by a static nonl...
It is shown that the commonly used adaptive algorithms are closely related to each other and can be ...
This work generalizes the Wiener-Kolmogorov theory of optimum linear filtering and prediction of sta...
This paper describes a new algorithm for initializing and estimating Wiener-Hammerstein models. The ...
We develop a tractable algorithms for finding the optimal power spectral density of the Gaussian inp...
This version is made available in accordance with publisher policies. Please cite only the published...
The Wiener–Kolmogorov principle of minimizing the mean square estimation error is discussed in the f...
This paper proposes a stochastic model to study the evolution of normal and excess weight population...