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Neural Representation Learning for Speech and Audio Signals
Representation learning is the branch of machine learning consisting of techniques that are capable of automatically discovering meaningful representations from raw data for efficient information extraction. In recent ...
Development of Synchro-Phasor Algorithms on Parallella - A Credit Card Sized Super Computer
In recent years, usage of GPS time-stamped phasor magnitude and angle measure-
ments of voltage and current samples, called synchrophasors, is getting great atten-
tion for wide area monitoring, protection, and control ...
Protection Schemes for Maintaining the Coordination Time Interval Between the Relays in Micro-grid
Conventional power system alone cannot meet the ever growing needs of electrical power
in the world in a reliable manner. Under these circumstances, large penetration of Dis-
tributed generators in the distribution level ...
Tuning of Multi-Band Power System Stabilizers in Multi-Machine Power Systems
Intermittent nature of renewables acts as a frequent trigger for small signal oscillations in power grid. These oscillatory modes correspond to either the rotor modes associated with the synchronous machines of conventional ...
Modulation of Power Electronic Converter Fed Split-phase Induction Machine Drive
Induction machine (IM) is the workhorse of several industries due to its low cost and minimal
maintenance. Power electronic converters play a major role in driving IMs which give
better
flexibility in these applications. ...
Speech task-specific representation learning using acoustic-articulatory data
Human speech production involves modulation of the air stream by the vocal tract shape determined by the articulatory configuration. Articulatory gestures are often used to represent the speech units. It has been shown ...
Speech and noise analysis using sparse representation and acoustic-phonetics knowledge
This thesis addresses different aspects of machine listening using two different approaches, namely (1) A
supervised and adaptive sparse representation based approach for identifying the type of background
noise and the ...
Fast total variation minimizing image restoration under mixed Poisson-Gaussian noise
Image acquisition in many biomedical imaging modalities is corrupted by Poisson noise followed by
additive Gaussian noise. Maximum Likelihood Estimation (MLE) based restoration methods that use
the exact Likelihood ...
Total Electric Field due to an Electron Avalanche and it's coupling to Transmission Line Conductors
Transmission of bulk electric power from the generating stations to the load centres can be carried out only through high voltages transmission lines. One of the main issues in the design and maintenance of extra and ...
Pronunciation assessment and semi-supervised feedback prediction for spoken English tutoring
Spoken English pronunciation quality is often influenced by the nativity of a learner, for whom English is the second language. Typically, the pronunciation quality of a learner depends on the degree of the following four ...

