scispace - formally typeset
A

A. van Veen

Researcher at Delft University of Technology

Publications -  438
Citations -  12230

A. van Veen is an academic researcher from Delft University of Technology. The author has contributed to research in topics: Helium & Vacancy defect. The author has an hindex of 45, co-authored 438 publications receiving 11541 citations. Previous affiliations of A. van Veen include Stanford University & University of Groningen.

Papers
More filters
Journal ArticleDOI

LOFAR: The LOw-Frequency ARray

M. P. van Haarlem, +199 more
TL;DR: The International LOFAR Telescope (ILT) as mentioned in this paper is a new-generation radio interferometer constructed in the north of the Netherlands and across europe, which covers the largely unexplored low frequency range from 10-240 MHz and provides a number of unique observing capabilities.
Journal ArticleDOI

An analytical constant modulus algorithm

TL;DR: It is shown that the underlying constant modulus factorization problem is, in fact, a generalized eigenvalue problem, and may be solved via a simultaneous diagonalization of a set of matrices.
Journal ArticleDOI

Analog Beamforming in MIMO Communications With Phase Shift Networks and Online Channel Estimation

TL;DR: This paper considers the design of the analog and digital beamforming coefficients, for the case of narrowband signals, and proposes the optimal analog beamformer to minimize the mean squared error between the desired user and its receiver estimate.
Proceedings ArticleDOI

Analysis of positron profiling data by means of ‘‘VEPFIT’’

TL;DR: In this paper, the authors presented a semi-linear fitting procedure for the Doppler broadening parameter S and the positronium fraction F vs the energy of the incident positrons.
Journal ArticleDOI

Subspace-based signal analysis using singular value decomposition

TL;DR: A unified approach is presented to the related problems of recovering signal parameters from noisy observations and identifying linear system model parameters from observed input/output signals, both using singular value decomposition (SVD) techniques.