The recursive least squares (RLS) algorithm is well known for its good convergence property and small mean square error in stationary environments. However RLS using constant forgetting factor cannot provide satisfactory performance in time varying environments. In this seminar, three variable forgetting factor (VFF) adaptation schemes for RLS are presented in order to improve the tracking perf...

We formulate and evaluate weighted and ordinary least squares procedures for estimating the parametric rate function of a nonhomogeneous Poisson process. Special emphasis is given to processes having an exponential rate function, where the exponent may include a polynomial component or some trigonometric components or both. Theoretical and experimental evidence is provided to explain some surpr...

Wixted and Ebbesen (1991) showed that forgetting functions produced by a variety of procedures are often well described by the power function, at-b, where a and b are free parameters. However, all of their analyses were based on data arithmetically averaged over subjects. R. B. Anderson and Tweney (1997) argue that the power law of forgetting may be an artifact of arithmetically averaging indiv...

In this paper we consider the problem of estimation of the frequencies and damping factors of exponential signals in the presence of noise. We propose a non-iterative method based on using forward–backward linear prediction and the notion of extended order modeling. In addition to providing estimators of the unknown parameters in the model, the proposed method can be used to specify initial val...

This paper tackles the problem of incremental and decremental learning of an evolving and customizable fuzzy inference system for classi cation. We explain the interest of integrating a forgetting capacity in such an evolving system to improve its performances in changing environment. In this paper, we describe two decremental learning strategies, to introduce a forgetting capacity in evolving ...

In this correspondence, the bit-error-rate (BER) performance evaluation of the space-time block-coded (STBC) communication systems using the numeric-variable-forgetting-factor (NVFF) least-squares (LS) channel estimator is presented. The polynomial channel paradigm is incorporated in LS algorithm in conjunction with NVFF to improve the channel tracking performance under the nonstationary wirele...

We propose a stable nonparametric method for constructing an option pricing model of exponential Lévy type, consistent with a given data set of option prices. After demonstrating the ill-posedness of the usual and least squares version of this inverse problem, we suggest to regularize the calibration problem by reformulating it as the problem of finding an exponential Lévy model that minimizes ...