Abstract. In the mid-1980s B.N. Parsons [29] and the author [10] independently had the idea to generalize linear stationary k-step methods to stationary (k, l)-step methods, which were further generalized to nonstationary and even nonlinear (k, l)-step methods. Later, conjugate-gradient-type methods that are (k, l)-step methods of a similar sort were introduced and investigated in the PhD thesi...

This paper overviews some recent developments in panel data asymptotics, concentrating on the nonstationary panel case and gives a new result for models with individual effects. Underlying recent theory are asymptotics for multi-indexed processes in which both indexes may pass to infinity. We review some of the new limit theory that has been developed, show how it can be applied and give a new ...

Possibility of the pipelining technique application in a highly nonstationary two-dimensional (2D) frequency-modulated (FM) signals estimation is considered in this paper. The considered design technique allows the implemented filter to overlape in execution unconditional steps performing in neighboring space/spatial-frequency (S/SF) instants and, consequently, to significantly improve executio...

A linear nonstationary quasi-geostrophic model is considered with extevnal and internal heating and for-ing. First, a stationary problem is solved. As it is slipposed that the nonstationary component of the ultra!ong wave is mainly generated by the nonlinear interaction of cyclonic waves, initially it is taken to be the same at all atmospheric levels, with the amplitude and phase being equal to...

-Empirical Mode Decomposition (EMD) has recently been introduced as a local and fully data-driven technique aimed at analyzing nonstationary signals, by decomposing nonstationary signals into Intrinsic Mode Functions (IMFs). In this contribution, we employ it to process the signals of partial discharge, a typical type of nonstationary signal. Based on the IMFs extracted from the corrupted signa...

Signal analysis with classical Gabor frames leads to a fixed time-frequency resolution over the whole time-frequency plane. To overcome the limitations imposed by this rigidity, we propose an extension of Gabor theory that leads to the construction of frames with time-frequency resolution changing over time or frequency. We describe the construction of the resulting nonstationary Gabor frames a...

Many spatial processes in environmental applications, such as climate variables and climate model errors on a global scale, exhibit complex nonstationary dependence structure, in not only their marginal covariance but also their cross-covariance. Flexible crosscovariance models for processes on a global scale are critical for an accurate description of each spatial process as well as the cross-...

Stationary regression is the backbone of different seismic data processing algorithms including match filtering, which is commonly applied for adaptive multiple subtraction. However, the assumption of stationarity is not always adequate for describing seismic signals. I present a general method of nonstationary regression and show its application to nonstationary match filtering. The key idea i...

In order to evaluate the performance of third-generation mobile communication systems, radio channel models are required. The models should be capable of handling nonstationary scenarios with dynamic evolution of multipaths. In this context and due to the introduction of advanced antenna systems to exploit the spatial domain, a further expansion is needed in order to include the nonstationary c...

The statistical properties of the paralinear and LogDet distances under nonstationary nucleotide frequencies were studied. First, we developed formulas for correcting the estimation biases of the paralinear and LogDet distances, i.e., the bias-corrected distance is estimated by dc = d - 2var(d), where d and var(d) are the estimated distance and sampling variance, respectively. The performances ...