Accurate information of power network parameters is essential for performing various power system monitoring and control tasks including state estimation, economic dispatch, and contingency analysis. In this paper, we present a novel approach of power network parameter correction wherein we exploit the sparse nature of parameter errors. Parameter error correction...
Crowdsourcing is a popular paradigm to address the high demands for labeled data in big data deluge. It aims to produce accurate labels by effectively integrating noisy, non-expert labeling from crowdsourced workers (annotators). The machine learning community has been studying effective crowdsourcing methods for many years, and many models and...
In a power system, operators maintain voltage stability through adequate reactive reserves. Maintaining and accessing an efficient allocation of reactive reserves is prohibitively complex because of reactive line losses, the variety of reactive resources, and either limited or variable reactive outputs from renewable sources. By clustering the system into smaller...
Wearable sensors with an inertial measurement unit (IMU) are popular for indoor positioning and activity pattern detection. The IMUs can be connected to a wireless transmission module, allowing users to monitor and process motion-related parameters remotely. Because of the complexity and uncertainty of signals in indoor environments, a radio frequency...
This thesis deals with target localization using multiple-input multiple-output (MIMO) radars. In the field of communications, navigation, radar, and sensing networks, one of the common and most sophisticated problems is target localization. We develop a target localization scheme in distributed MIMO radar systems using bistatic range measurements. The localization approach...
We consider the problem of computing the cannonical polyadic decomposition (CPD) for large-scale dense tensors. This work is a combination of alternating least squares and fiber sampling. Data sparsity can be leveraged to handle large tensor CPD, but this route is not feasible for dense data. Inspired by stochastic optimization's...
While electrification is currently one of the largest trends in the automotive world, other related industries are also evaluating electrification opportunities as a means to reduce environmental impact, emissions, and noise pollution. One such sector is the aviation industry. While it is generally accepted that all-electric aircraft are not a...
This work demonstrates correlation of microwave signals encoded with 16-bit codes using the parametric interaction of spin waves. Signal processing correlators are devices that compare two signals, such as a reference code and a received code, where the output indicates the similarity between the signals. Correlators are used in communication...
In any biomedical signal acquisition system, a front-end amplifier is needed to amplify low amplitude bio-signals while filtering out any unwanted low-frequency artifacts. The design of low frequency poles within the sub-Hz range implies very large time-constants which goes against system integrability. In recent years, the pseudo resistor has been...
The CMOS two-stage Operational Transconductance Amplifier (OTA) has been a key enabler for mixed-signal IC design for nearly four decades . This research focuses on a modified two-stage CMOS OTA that features load-pole cancellation (LPC); i.e., the resulting architecture is essentially a two-stage CMOS OTA with no load capacitance. The...