Two existing Hammerstein-Wiener identification algorithms and a third novel Hammerstein-Wiener identification algorithm are considered for application to the magnetospheric system. A modified subspace algorithm that allows missing data points is described and used for identifying periodically switching Hammerstein-Wiener models, to capture the periodically time-varying nature of the system. The...

An explicit, non-recursive formula for the Wiener index of any given benzenoid chain is derived, greatly speeding up calculations and rendering it manually manageable, through a novel envisioning of chains as ternary strings. Previous results are encompassed and two completely new and useful ones are obtained, a formula to determine Wiener indices of benzenoid chains in periodic patterns, and a...

We show that multi-window Gabor frames with windows in the Wiener algebra W (L∞, `) are Banach frames for all Wiener amalgam spaces. As a by-product of our results we prove the canonical dual of a Gabor frame with a continuous generator in the Wiener algebra also belongs to this space. Our proofs are mostly based on recent noncommutative versions of Wiener’s 1/f lemma.

The paper presents speech enhancement scheme for suppression of different background noises. The objective of speech enhancement is to improve the quality of the processed speech. This paper also investigate the use of two different transforms for speech enhancement. Speech enhancement using wiener filtering approach is presented using transforms DFT and DCT. The type of transform shows differe...

The problem of distances in a graph, G, is one of the most studied questions, both from theoretical point of view and applications (the reader can consult two recent reviews ). It is connected to the Wiener number, W, or "the path number" as denominated by its initiator. In acyclic structures, Wiener number and its extension, hyper-Wiener number, can be defined as edge/path contributions, Ie/p ...

This article presents a survey of various methods for nonparametric identification of nonlinear systems. Nonparametric identification methods are those that measure Wiener kernels or Volterra kernels, since an output of a nonlinear system can be described by the convolution integral of Wiener or Volterra kernels and the system input. Section 1 highlights the representation methods of nonlinear ...

The aim of this work is to construct the stochastic calculus of variations on Poisson space and some of its applications via the stochastic analysis on Wiener space. We define a new gradient operator on Wiener space, whose adjoint extends the Poisson stochastic integral. This yields a new decomposition of the Ornstein-Uhlenbeck operator and a substructure of the standard Dirichlet structure on ...