Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 99 for “"Independent Component Analysis"”.
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Independent component analysis and beyond
'Independent component analysis' (ICA) ist ein Werkzeug der statistischen Datenanalyse und Signalverarbeitung, welches multivariate Signale in ihre Quellkomponenten zerlegen kann. Obwohl das klassische ICA Modell sehr nützlich ist, gibt es viele Anwendungen, die Erweiterungen von ICA erfordern. In …
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Appearance based object recognition using independent component analysis
… Karhunen-Loeve transform (KLT), or principal component analysis (PCA). The lower dimensional space has been called the eigenspace. For recognition, the test image is projected likewise onto the eigenspace and its position on the appearance manifold is used for the recognition phase. In object …
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Enhancing brain-computer interfacing through advanced independent component analysis techniques
… etc. are used to reduce the noise and extract components of interest. However these methods process the data on the observed mixture domain which mixes components of interest and noise. Such a limitation means that extracted EEG signals possibly still contain the noise residue or coarsely that …
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The value of independent component analysis in identifying climate processes
… a useful tool in the problem of identifying components of climate change signals from ensembles of multiple climate models.
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Frequency Domain Independent Component Analysis Applied To Wireless Communications Over Frequency-selective Channels
… In this research, a novel Frequency-Domain Independent Component Analysis (ICA-F) approach is proposed to blindly separate and deconvolve signals traveling through frequency-selective, slow fading channels. Compared with existing time-domain approaches, the ICA-F is computationally efficient …
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PARALLEL INDEPENDENT COMPONENT ANALYSIS WITH REFERENCE FOR IMAGING GENETICS: A SEMI-BLIND MULTIVARIATE APPROACH
… a semi-blind multivariate approach, parallel independent component analysis with reference (pICA-R), to better reveal relationships between hidden factors of particular attributes. First, a consistency-based order estimation approach is introduced to advance the application of ICA to genotype …
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An offline multi-class auditory P300 brain-computer interface using principal and independent component analysis
… to classification. A combination of principal component analysis (PCA) and independent component analysis (ICA), together with a method of enhancing the P300 properties through temporal and spatial manipulation are investigated as a means of improving classification accuracy. The combination of …
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Independent component analysis and source analysis of auditory evoked potentials for assessment of cochlear implant users
Source analysis of the Auditory Evoked Potential (AEP) has been used before to evaluate the maturation of the auditory system in both adult and children; in the same way, this technique could be applied to ongoing EEG recordings, in response to acoustic specific frequency stimuli, from children …
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On the Use of Independent Component Analysis & Functional Network Connectivity Analysis: Evaluation on Two Distinct Large-Scale Psychopathology Studies
Medical image analysis techniques are becoming ever useful in allowing us to better understand the complexities and constructs of the brain and its functions. These analysis methods have proven to be integral in revealing trends in brain activity within individuals with mental disorders that are …
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Independent Component Analysis of Event-Related Electroencephalography During Speech and Non-Speech Discrimination: : Implications for the Sensorimotor ∆∞ Rhythm in Speech Processing
… articulatory goals functioning to weight sensory analysis toward expected acoustic features (e.g. analysis-by-synthesis; internal models). Direct-realist accounts posit that sensorimotor integration is achieved via a direct match between incoming acoustic cues and articulatory gestures. A method …
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A study on the application of independent component analysis to \(in vivo\) \(^1\)H magnetic resonance spectra of childhood brain tumours for data processing
Independent component analysis (ICA) has the potential of automatically determining metabolite, macromolecular and lipid (MMLip) components that make up magnetic resonance (MR) spectra. However, the realiability with which this is accomplished and the optimal ICA approach for investigating in vivo …
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Mapping the Spatial and Temporal Dynamics of Sensorimotor Integration During the Perception and Performance of Wallowing
… neurological compromise. Recent advances in EEG analysis blind source separation techniques via independent component analysis offer a novel and exciting opportunity to measure cortical sensorimotor activity in realtime during swallowing, concurrently with muscle activity during swallow …
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Determining the optimal paradigm for investigating if M1 activations associated with step tracking wrist movements are direction or muscle related using EEG
… EEG data to remove this artefact were compared. Independent component analysis was applied to the averaged epochs and components resulting from artefacts were removed. Source localisation methods were applied to the processed averages and their results assessed for physiological and anatomical …
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Approximate credibility intervals on electromyographic decomposition algorithms within a Bayesian framework
… This framework is then demonstrated using independent component analysis with electromyographic data. Blind source separation (BSS) algorithms, such as independent component analysis (ICA), are often used to solve the inverse problem arising when, for example, attempting to retrieve the …
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Computational Dissection of Composite Molecular Signatures and Transcriptional Modules
… is developed, namely, nonnegative partially independent component analysis (nPICA), for tissue heterogeneity correction (THC). The THC problem is formulated as a constrained optimization problem and solved with a learning algorithm based on geometrical and statistical principles. The second …
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Issues in the processing and analysis of functional NIRS imaging and a contrast with fMRI findings in a study of sensorimotor deactivation and connectivity
… thesis examines issues in the processing and analysis of continuous wave functional linear infrared spectroscopy (fNIRS) of the brain usung the DYNOT system. In the second part, the same sensorimotor experiment is carried out using functional magnetic resonance imaging (fMRI) and near infrared …
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