Browsing Division of Electrical, Electronics, and Computer Science (EECS) by Title
Now showing items 1071-1090 of 1253
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Space-Vector-Based Pulse Width Modulation Strategies To Reduce Pulsating Torque In Induction Motor Drives
(2015-05-27)Voltage source inverter (VSI) is used to control the speed of an induction motor by applying AC voltage of variable amplitude and frequency. The semiconductor switches in a VSI are turned on and off in an appropriate ... -
Sparse Bayesian Learning For Joint Channel Estimation Data Detection In OFDM Systems
(2018-08-30)Bayesian approaches for sparse signal recovery have enjoyed a long-standing history in signal processing and machine learning literature. Among the Bayesian techniques, the expectation maximization based Sparse Bayesian ... -
Sparse Multiclass And Multi-Label Classifier Design For Faster Inference
(2013-06-20)Many real-world problems like hand-written digit recognition or semantic scene classification are treated as multiclass or multi-label classification prob-lems. Solutions to these problems using support vector machines (SVMs) ... -
Sparsity Driven Solutions to Linear and Quadratic Inverse Problems
The problem of signal reconstruction from inaccurate and possibly incomplete set of linear/non-linear measurements occurs in a variety of signal and image processing applications. In this thesis, we develop reconstruction ... -
Sparsity Motivated Auditory Wavelet Representation and Blind Deconvolution
(2018-08-29)In many scenarios, events such as singularities and transients that carry important information about a signal undergo spreading during acquisition or transmission and it is important to localize the events. For example, ... -
Spatial Analysis and Reconstruction of Reverberant Speech
Speech signal includes the spoken message and a lot more information such as speaker emotion, identity, language, speaking location characteristic etc., which makes the human interaction lively, desirable and more useful. ... -
Spatially Adaptive Regularization for Image Restoration
Image restoration/reconstruction refers to the estimation of an underlying image from measurements generated by imaging devices. This problem is generally ill-posed since the measurements are corrupted by the physical ... -
Spatially Correlated Data Accuracy Estimation Models in Wireless Sensor Networks
(2018-02-10)One of the major applications of wireless sensor networks is to sense accurate and reliable data from the physical environment with or without a priori knowledge of data statistics. To extract accurate data from the physical ... -
Spatio-temporal Memories: Theory and Algorithms
This thesis is primarily focused on building a systematic theory for spatio-temporal memories based on unsupervised learning and exploring its applications. Also, contributions are made in the area of supervised learning ... -
Speaker verification using whispered speech
Like neutral speech, whispered speech is one of the natural modes of speech production, and it is often used by speakers in their day-to-day life. For some people, such as laryngectomees, whispered speech is the only ... -
Specification Synthesis with Constrained Horn Clauses
Many practical problems in software development, verification and testing rely on specifications. The problem of specification synthesis is to automatically find relational constraints for undefined functions, called ... -
Spectral And Temporal Zero-Crossings-Based Signal Analysis
(2017-09-20)We consider real zero-crossing analysis of the real/imaginary parts of the spectrum, namely, spectral zero-crossings (SZCs). The two major contributions are to show that: (i) SZCs provide enable temporal localization of ... -
Spectral Efficiency Improvement in Spatial Modulation Systems
A novel energy efficient Multiple-Input-Multiple-Output (MIMO) technique is called Spatial Mod- ulation (SM). It uses only one radio frequency (RF) chain that reduces the hardware complexity and cost of the system. The ... -
Spectro-Temporal Features For Robust Automatic Speech Recognition
(2011-01-18)The speech signal is inherently characterized by its variations in time, which get reflected as variations in frequency. The specto temporal changes are due to changes in vocaltract, intonation, co-articulation and successive ... -
Spectrotemporal Processing of Speech Signals Using the Riesz Transform
Speech signals possess a rich time-varying spectral content, which makes their analysis a challenging signal processing problem. Developing methods for accurate speech analysis has a direct impact on applications such as ... -
Spectrum Sensing in Cognitive Radios using Distributed Sequential Detection
(2018-03-17)Cognitive Radios are emerging communication systems which efficiently utilize the unused licensed radio spectrum called spectral holes. They run Spectrum sensing algorithms to identify these spectral holes. These holes ... -
Spectrum Sensing Techniques For Cognitive Radio Applications
(2017-07-25)Cognitive Radio (CR) has received tremendous research attention over the past decade, both in the academia and industry, as it is envisioned as a promising solution to the problem of spectrum scarcity. ACR is a device that ... -
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 ... -
Speech Encryption Using Wavelet Packets
(Indian Institute of Science, 2005-10-07)The aim of speech scrambling algorithms is to transform clear speech into an unintelligible signal so that it is difficult to decrypt it in the absence of the key. Most of the existing speech scrambling algorithms tend ...