11 papers · 1 filter
CRB-Optimal Arrays and Waveforms in Active Sensing: Role of Redundancy and Spatial Covariance of Array Geometry
Ids van der Werf, Robin Rajamäki, Geert Leus
This paper characterizes the performance limits of optimal array designs using orthogonal and coherent waveforms for both linear and planar arrays. For orthogonal waveforms, we sho…
A Covariance Matching Approach to Graph Topology Identification
Yongsheng Han, Raj Thilak Rajan, Geert Leus
Graph topology identification (GTI) is a central challenge in networked systems, where the underlying structure is often hidden, yet nodal data are available. Conventional solution…
Joint Simplicial Complex Learning via Binary Linear Programming
Varun Sarathchandran, Geert Leus
Learning the topology of higher-order networks from data is a fundamental challenge in many signal processing and machine learning applications. Simplicial complexes provide a prin…
Robust Covariance-Based DoA Estimation under Weather-Induced Distortion
Chenyang Yan, Geert Leus, Mats Bengtsson
We investigate robust direction-of-arrival (DoA) estimation for sensor arrays operating in adverse weather conditions, where weather-induced distortions degrade estimation accuracy…
Learning the Topology of a Simplicial Complex Using Simplicial Signals: A Greedy Approach
A. Buciulea, E. Isufi, G. Leus +1
Graphs are ubiquitous to model the irregular (non-Euclidean) structure of complex data, but they are limited to pairwise relationships and fail to model the complexities of the dat…
Topological Signal Processing and Learning: Recent Advances and Future Challenges
Elvin Isufi, Geert Leus, Baltasar Beferull-Lozano +2
Developing methods to process irregularly structured data is crucial in applications like gene-regulatory, brain, power, and socioeconomic networks. Graphs have been the go-to alge…