Digital applications have developed rapidly over the last few decades. Since many sources
of information are of analog or continuous-time nature, discrete-time signal processing …

Finding a tube of small width that covers a certain percentage of the training data samples is
a robust way to estimate a location: the values of the data samples falling outside the tube …

A Sobolev reproducing-kernel Hilbert space approach to image interpolation is introduced.
The underlying kernels are exponential functions and are related to stochastic …

Causal processing of a signal's samples is crucial in on-line applications such as audio rate
conversion, compression, tracking and more. This paper addresses the problems of …

Orthogonal projection offers the optimal solution for many sampling-reconstruction problems
in terms of the least square error. In the standard interpolation setting where the sampling is …

In this paper, a novel adaptive filter algorithm, called boxed-constraint least mean square
(BXCLMS) algorithm, is proposed for identifying the boxed-constrained system where the …

Sampling theory has benefited from a surge of research in recent years, due in part to
intense research in wavelet theory and the connections made between the two fields. In this …

Although chirp-coded signals can theoretically improve the performance of ultrasound
medical imaging, these signals are presently of limited use. Their main advantage is better …

This paper considers the problem of optimum reconstruction in generalized sampling-
reconstruction processes (GSRPs). We propose constrained GSRP, a novel framework that …

Sampling theory has benefited from a surge of research in recent years, due in part to the
intense research in wavelet theory and the connections made between the two fields. In this …