One of the essential components of a neuromotor prosthetic device is a neural decoder that translates the activity of a set of neurons into an estimate of the intended movement of the prosthetic limb. Wiener filter style approaches model this transformation as a linear function of the number of spikes observed from a set of neurons and over a range of distinct time bins. More recently, research...

The estimation of diagonal elements of a Wiener model kernel is a well known practical and theoretical problem. The new operators and notations here proposed aim at the automatic code generation for the implementation of efficient and accurate nonparametric algorithms for the identification of diagonal points. The resulting formulas here presented allow the direct implementation of the Wiener k...

A simple and effective algorithm is introduced for the system identification of Wiener system based on the observational input/output data. The B-spline neural network is used to approximate the nonlinear static function in the Wiener system. We incorporate the Gauss-Newton algorithm with De Boor algorithm (both curve and the first order derivatives) for the parameter estimation of the Wiener m...

the wiener index is a graph invariant that has found extensive application in chemistry. inaddition to that a generating function, which was called the wiener polynomial, who’sderivate is a q-analog of the wiener index was defined. in an article, sagan, yeh and zhang in[the wiener polynomial of a graph, int. j. quantun chem., 60 (1996), 959969] attainedwhat graph operations do to the wiener po...

In this paper the Wiener and hyper Wiener index of two kinds of dendrimer graphs are determined. Using the Wiener index formula, the Szeged, Schultz, PI and Gutman indices of these graphs are also determined.

We present a closed form expression for the information matrix associated with the Wiener model identification problem under the assumption that the input signal is a stationary Gaussian process. This expression holds under quite generic assumptions. We allow the linear sub-system to have a rational transfer function of arbitrary order, and the static nonlinearity to be a polynomial of arbitrar...

1. Pearson RK. Selecting nonlinear model structures for computer control. J Process Control 2003; 13: 1–26 2. Bloemen HHJ, Chou CT, van den Boom TJJ, Verdult V, Verhaegen M, Backx TC. Wiener model identification and predictive control for dual composition control of a distillation column. J Process Control 2001; 11: 601–620 3. Westwick D, Verhaegen M. Identifying MIMO Wiener systems using subsp...

The Wiener index of a connected graph G, denoted by W(G) , is defined as ∑ ( , ) , ∈ ( ) .Similarly, hyper-Wiener index of a connected graph G,denoted by WW(G), is defined as ( ) + ∑ ( , ) , ∈ ( ) .In this paper, we present the explicit formulae for the Wiener, hyper-Wiener and reverse Wiener indices of some graph operations. Using the results obtained here, the exact formulae for Wiener, hyper...

the unitary cayley graph xn has vertex set zn = {0, 1,…, n-1} and vertices u and v areadjacent, if gcd(uv, n) = 1. in [a. ilić, the energy of unitary cayley graphs, linear algebraappl. 431 (2009) 1881–1889], the energy of unitary cayley graphs is computed. in this paperthe wiener and hyperwiener index of xn is computed.

It is suggested that the differences between the Hammerstein and Wiener models be interpreted and understood in terms of the system eigenvalues. In particular, it is shown that the Wiener representation should be preferred when the system dynamics vary with the operating point. Conversely, when only the system gain varies with the operating point, Hammerstein models generally outperform the Wie...