Search results for "Multilinear"
showing 3 items of 43 documents
Automated detection and localization system of myocardial infarction in single-beat ECG using Dual-Q TQWT and wavelet packet tensor decomposition
2020
Background and objective. It is challenging to conduct real-time identification of myocardial infarction (MI) due to artifact corruption and high dimensionality of multi-lead electrocardiogram (ECG). In the present study, we proposed an automated single-beat MI detection and localization system using dual-Q tunable Q-factor wavelet transformation (Dual-Q TQWT) denoising algorithm. Methods. After denoising and segmentation of ECG, a fourth-order wavelet tensor (leads × subbands × samples × beats) was constructed based on thediscretewavelet packet transform (DWPT), to represent the features considering the information of inter-beat, intra-beat, inter-frequency, and inter-lead. To reduce the t…
Senso, ritmo, multimodalità. Uno studio comparativo dei processi traduttivi nelle lingue dei segni (LIS e LSF)
2021
La presente tesi di dottorato analizza i processi traduttivi nelle lingue segnate, indagando la maniera di (re-)enunciare il senso in traduzione. La riflessione si costruisce come dialogo fra la linguistica delle lingue segnate e la traduttologia, a partire da presupposti teorici comuni a entrambe le discipline benché differentemente declinati, come il concetto di oralità. Lo studio, che intende definirsi come non assimilazionista (così come auspicato da C. Cuxac), tiene conto delle peculiarità proprie delle lingue segnate, fra cui le caratteristiche di multimodalità e multilinearità, e analizza le lingue dei segni sulla base del modèle sémiologique. Considerando la prospettiva dell’embodie…
Exploiting ongoing EEG with multilinear partial least squares during free-listening to music
2016
During real-world experiences, determining the stimulus-relevant brain activity is excitingly attractive and is very challenging, particularly in electroencephalography. Here, spectrograms of ongoing electroencephalogram (EEG) of one participant constructed a third-order tensor with three factors of time, frequency and space; and the stimulus data consisting of acoustical features derived from the naturalistic and continuous music formulated a matrix with two factors of time and the number of features. Thus, the multilinear partial least squares (PLS) conforming to the canonical polyadic (CP) model was performed on the tensor and the matrix for decomposing the ongoing EEG. Consequently, we …