Searched for: contributor%3A%22Hendriks%2C+R.C.+%28graduation+committee%29%22
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Stunnenberg, Kenneth (author)
Brain disorders in children pose significant challenges to their development, impacting cognition, speech, movement, and behavior. The uncertainty surrounding prognostic information at the time of diagnosis leaves families with numerous questions about the future. The Child Brain Lab at Erasmus MC Sophia Children's Hospital conducts IQ,...
master thesis 2023
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Zhong, BingXiang (author)
Rank detection is crucial in array processing applications, as many algorithms rely on accurately estimating the rank of the data matrix to ensure optimal performance. Under Gaussian white noise, rank can be detected through eigenvalue analysis. However, in arbitrary noise, prewhitening the data matrix with the noise covariance matrix is...
master thesis 2023
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de Groot, Dimme (author)
The work presented in this thesis investigates the creation of virtual sound sources in a room equipped with a limited number of loudspeakers. This limited number of loudspeakers is typical for consumer loudspeaker systems. Ideally, these systems can provide a listening experience in which localisation cues are completely present. However, in...
master thesis 2023
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Schupp, Eleen (author)
When a person suffers from severe to profound hearing loss, a cochlear implant (CI) can aid in restoring auditory perception and speech comprehension. To obtain good speech comprehension, fitting of a CI to the user’s specific characteristics is crucial. Fitting can be a time-consuming process which requires the cooperation of a CI user and is...
master thesis 2023
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Wenink, Kristel (author)
Introduction: Currently, there is no method available for intra-operative evaluation of the completeness (transmurality and continuity) of surgical ablation lesions. This study aimed to investigate the changes in electrogram characteristics and activation patterns caused by different (non)transmural and (dis)continuous ablation lesions in ex...
master thesis 2023
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Sharma, Sumeet (author)
The main purpose of a radar is to detect, recognize, and track objects of interest. When it is known that only a single target is present, the matched filter is proven to be optimal detector. However, in practice, a radar scene often consists of multiple targets. For example, in air surveillance and monitoring applications, multiple aircrafts...
master thesis 2023
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Tao, Yitong (author)
To better understand how brain signals are processed and even how the human mind works, analyzing the hemodynamic signal model is one of the most essential steps. In the CUBE group of Erasmus MC, functional ultrasound (fUS) data of a mouse’s brain is recorded. By using this fUS dataset, this thesis will solve the problem regarding the joint...
master thesis 2022
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Freyer, Caroline (author)
Outlier detection in time series has important applications in a wide variety of fields, such as patient health, weather forecasting, and cyber security. Unfortunately, outlier detection in time series data poses many challenges, making it difficult to establish an accurate and efficient detection method. In this thesis, we propose the Random...
master thesis 2022
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Jordan, Sebastian (author)
In recent years, the large increase in connected devices and the data that is collected by these devices has caused a heightened interest in distributed processing. Many practical distributed networks are of heterogeneous nature. Because of this, algorithms operating within these networks need to be simple, robust against network dynamics and...
master thesis 2022
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Gong, Huaiyang (author)
This project develops and tests algorithms for joint signal processing of data from two radars located on the rooftop of EWI (PARSAX and MESEWI). The particular tasks consist of automatic alignment of radar data in space (2D map) and time by observing moving targets of opportunity in the high-resolution mode. After the data alignment procedure,...
master thesis 2021
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Roest, Jeroen (author)
Introduction: Potentials measured at the epicardial surface contain information regarding the conductive properties of the atrial tissue. The current lack of morphological categorization during atrial fibrillation (AF) provokes the usage of unsupervised learning methods to evaluate time series electrograms across the atrial surface. Analysis of...
master thesis 2021
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ZHANG, Bichi (author)
In recent decades, the field of autonomous driving has witnessed rapid development, benefiting from the development of artificial intelligence-related technologies such as machine learning. Autonomous perception in driving is a key challenge, in which multi-sensor fusion is a common feature. Due to the high resolution and rich information, the...
master thesis 2021
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van Twist, Eris (author)
Background: Unipolar electrograms (U-EGMs) contain additional information about interatrial activation and conduction in their morphology, which may aid towards improved diagnosis and staging of atrial fibrillation (AF).Objective: The primary objective is to investigate regional differences in electrogram area (EA) during SR and AF and to design...
master thesis 2021
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Bons, Wouther (author)
Currently, trained machine learning models are readily available, but their training data might not be (for example due to privacy reasons). This thesis investigates how pre-trained models can be combined for performance on all their source domains, without access to data. This problem is formulated as a Multiple-Source Domain Adaptation (MSA)...
master thesis 2021
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Fernandez Santoro, Elias Mateo (author)
The olivocerebellar system plays a central role in motor learning, crucially contributing to the coordination, precision and accurate timing of movements. The system is formed by Purkinje cells (PC), the Deep Cerebellar Nucleus (DCN) and Inferior Olive (IO). Its input activate the PC which produces simple (SS) and complex spikes (CS). The latter...
master thesis 2019
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Maswan, Jelimo (author)
Atrial fibrillation (AF) is one of the more common clinical arrhythmias with a high morbidity and mortality. Despite this, the electrophysiological and pathological mechanisms associated with AF largely remain a mystery, encouraging the use of ever more sophisticated techniques to extract vital information for diagnostic and therapeutic purposes...
master thesis 2017
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