Tensor decomposition for Independent Component Analysis: Through implicit cumulant tensor manipulation

Blind Source Separation (BSS), the separation of latent source components from observed mixtures, is relevant to many fields of expertise such as neuro-imaging, economics and machine learning. Reliable estimates of the sources can be obtained through diagonalization of the cumulant tensor, i.e., a fourth-order symmetric multi-linear array...

High Resolution Model-Independent Carbon Monoxide Emission Localization and Characterization Using TROPOMI

Independent Component Analysis Filter for Small Vessel Contrast Imaging During Fast Tissue Motion

Suppressing tissue clutter is an essential step in blood flow estimation and visualization, even when using ultrasound contrast agents. Blind source separation (BSS)-based clutter filter for high-framerate ultrasound imaging has been reported to perform better in tissue clutter suppression than the conventional frequency-based wall filter and...

Blind Polarization Demultiplexing of Probabilistically Shaped Signals

We propose a novel method for blind polarization-demultiplexing of probabilistically shaped signals for coherent receivers. The method is capable of separating signals with (quasi) Gaussian distributions by exploiting temporal correlations added to the transmit signals. The proposed method is evaluated in challenging mixing scenarios.

Low Complex Accurate Multi-Source RTF Estimation

Many multi-microphone algorithms depend on knowing the relative acoustic transfer functions (RTFs) of the individual sound sources in the acoustic scene. However, accurate joint RTF estimation for multiple sources is a challenging problem. Existing methods to jointly estimate the RTF for multiple sources have either no satisfying performance, or...

Analyzing Functional Ultra- sound Images of the Brain Using Tensor Decompositions

Functional ultrasound (fUS) is a neuroimaging modality that offers high spatial and temporal resolution while also providing portability. In this thesis, neuroimaging data acquired with fUS at Center for Ultrasound and Brain imaging at Erasmus MC (CUBE) is processed. Due to the fact that fUS data is inherently multidimensional, we propose using...

Augmenting interictal mapping with neurovascular coupling biomarkers by structured factorization of epileptic EEG and fMRI data

EEG-correlated fMRI analysis is widely used to detect regional BOLD fluctuations that are synchronized to interictal epileptic discharges, which can provide evidence for localizing the ictal onset zone. However, the typical, asymmetrical and mass-univariate approach cannot capture the inherent, higher order structure in the EEG data, nor...

Ventricular Activity Signal Removal in Atrial Electrograms of Atrial Fibrillation

Diagnosis and treatment of atrial fibrillation can benefit from various signal processing approaches employed on atrial electrograms. However, the performance and interpretation of these approaches get highly degraded by far-field ventricular activities (VAs) that distort the morphology of the pure atrial activities (AAs). In this study, we...

Robust Joint Estimation of Multimicrophone Signal Model Parameters

One of the biggest challenges in multimicrophone applications is the estimation of the parameters of the signal model, such as the power spectral densities (PSDs) of the sources, the early (relative) acoustic transfer functions of the sources with respect to the microphones, the PSD of late reverberation, and the PSDs of microphone-self noise...

The cocktail party problem: GSVD-beamformers for speech in reverberant environments

Hearing aids as a form of audio preprocessing is increasingly common in everyday life. The goal of this thesis is to implement a blind approach to the cocktail party problem and challenge some of the regular assumptions made in literature. We approach the problemas wideband FD-BSS. From this field of research, the common assumption of contineous...

Treatment of source separated urine and its effects on wastewater systems

Abstract not available

Algorithms for Separation of Secondary Surveillance Radar Replies

Air Traffic Control (ATC) centers aim at ensuring safety of aircrafts cruising in their area. The information required to face this mission includes the data provided by primary and Secondary Surveillance Radar (SSR). The first one indicates the presence of an aircraft, whereas the second gives information on its identity and altitude. All...