Various applications like wireless UWB communication, fast data acquisition systems and digital storage oscilloscopes needs ADCs with instantaneous input signal bandwidth from 0.1-40 GigaHertz range with 6-10 bits of resolution -- a challenging task and an impressive goal to achieve. Flash ADCs have been conventionally employed to achieve these goals...
Many devices and methods for radiological searches are currently being developed, including scanning using simple detectors, mapping using large-volume detectors, and Compton imaging using 3-D position sensitive detectors. However, these devices are typically expensive and the methods used require long periods of time to generate a direction or location. The...
Magnetic particle imaging (MPI) is a biomedical imaging technique which detects the presence of magnetic nanoparticles which have been introduced into the specimen prior to imaging. MPI has shown promise for real-time imaging with spatial resolution comparable to magnetic resonance imaging (MRI). MPI research has focused predominantly on the development...
The potential for electric energy generation from ocean waves is substantial and much research is being conducted on the conversion process as a renewable, grid-connected, power source. Some of the same attributes that make wave energy harvesting attractive as a grid-connected source also make it attractive as a remote, or...
Markov Decision Process (MDP) is a well-known framework for devising the optimal decision making strategies under uncertainty. Typically, the decision maker assumes a stationary environment which is characterized by a time-invariant transition probability matrix. However, in many real-world scenarios, this assumption is not justified, thus the optimal strategy might not...
Within the past several years the technology of high-throughput sequencing has transformed the study of biology by offering unprecedented access to life's fundamental building block, DNA. With this transformation's potential a host of brand-new challenges have emerged, many of which lend themselves to being solved through computational methods. From de...
In this thesis, convergence of time inhomogeneous Markov chains is studied using an adiabatic approach. The adiabatic framework considers slowly changing systems and the adiabatic time quantifies the time required for the change such that the final state of the system is close to some equilibrium state. This approach is...
Macrosomia is a medical term describing a new baby born with an excessive birth weight (greater than 4000g). Fetal macrosomia may lead to both pregnancy complications, and increased risk of mother's and baby's health problems after birth. But the potential complications may be mitigated by a cesarean delivery. As such,...
Anomaly detection has been used in variety of applications in practice, including cyber-security, fraud detection and detecting faults in safety critical systems, etc. Anomaly detectors produce a ranked list of statistical anomalies, which are typically examined by human analysts in order to extract the actual anomalies of interest. Unfortunately, most...
Many methods have been explored in the literature of multi-label learning, ranging from simple problem transformation to more complex method that capture correlation among labels. However, mostly all existing works do not address the challenge with incomplete label data. The goal of this project is to extend the work of...
Continues-Time (CT) Delta-Sigma (ΔΣ) Analog-to-Digital Converters (ADCs) have one important constrain, namely the excess loop delay. Most previous excess lop delay compensation methods need to know the exact value of the excess loop delay in advance. However, the value of the excess loop delay is a uniformly distribution random variable....
One of the key challenges in downlink multiuser multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems is the mitigation of the multi-access interference when different users share the same subcarriers. In this work, the block diagonalization (BD) algorithm for inter-user interference pre-cancelation is extended to MIMO-OFDM systems. However, in...
We consider multiple Compressive Sensing (CS) problems wherein the supports of signal vectors of CS problems are restricted to satisfy a collection of joint logical constraints, which we refer to as coupling constraints. We consider a case where the coupling constraints are encoded in a graph and present a sequential...
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...
We investigate the data collection problem in sensor networks. The network consists of a number of stationary sensors deployed at different sites for sensing and storing data locally. A mobile element moves from sites to sites to collect data from the sensors periodically. There are different costs associated with the...
Ring amplifiers (ringamps) have shown excellent power efficiency in the latest state-of-the-art analog to digital converters (ADCs). This thesis describes circuit techniques to ensure robust operation of ringamps using standard analog techniques and proportional-integral-derivative(PID) controller analogy. Large-signal and small-signal analysis of a ringamp are performed using simple RC settling and...
This dissertation presents two high-speed pipeline successive approximation analog-to-digital converters (SAR ADCs). Capacitive DACs and resistive DACs are utilized in these two pipeline SAR ADCs, respectively.
The pipeline SAR ADC with capacitive DACs can save 50% switching power compared with other time-interleaved SAR ADCs since the total capacitance of the...
Recent work in machine learning concerns the detection and identification of bird species from audio recordings of their vocalizations. Such analysis can yield valuable ecological information concerning the activity and distribution of species in the wild. Current species-identification methods require individual syllables of bird audio as input, but field-collected audio...
As the growth of renewable energy sources, such as wind, solar, and ocean wave, increases, their impact on the electrical grid has been rapidly escalating. Although renewable resources have been able to offset some traditional generation, they have also brought a need for increasing reserve capacity due to their non-dispatchable,...
Multiple-input multiple-output (MIMO) antennas can be exploited to provide high data rate using a limited bandwidth through multiplexing gain. MIMO combined with orthogonal frequency division multiplexing (OFDM) could potentially provide high data rate and high spectral efficiency in frequency-selective fading channels. MIMO-OFDM technology has been widely employed in modern communication...
Data converters are ubiquitous building blocks of a signal chain. The rapid increase in
communication and connectivity devices presents new avenues for pushing the state of
the art analog to digital converters. Techniques for improving resolution, bandwidth,
linearity and bit-error rate, while reducing the power, energy and area is the...
Traditionally, networking protocol designs have placed much emphasis on point-to-point reliability and efficiency. With the recent rise of mobile and multimedia applications, other considerations such as power consumption and/or Quality of Service (QoS) are becoming increasingly important factors in designing network protocols. As such, we present a new flexible framework...
Multiple-input multiple-output wireless systems promise significant capacity gain
and/or diversity gain over single antenna systems. If channel state information (CSI)
is available at both the transmitter and the receiver, the performance can be further
improved. In this thesis, first, we study binary index feedback problem in beamforming
systems when the...
This dissertation addresses two fundamental problems in computer vision—namely,
multitarget tracking and event recognition in videos. These problems are challenging
because uncertainty may arise from a host of sources, including motion blur,
occlusions, and dynamic cluttered backgrounds. We show that these challenges can be
successfully addressed by using a multiscale,...
Delta-sigma analog-to-digital converters traditionally have been used for low speed, high resolution applications such as measurements, sensors, voice and audio systems. Through continued device scaling in CMOS technology and architectural and circuit level design innovations, they have even become popular for wideband, high dynamic range applications such as wired and...
Trends in wireless networks are increasingly pointing towards a future with multi-hop
networks deployed in multi-channel environments. In this thesis, we present the design
for iMAC—a protocol targeted at medium access control in such environments. iMAC
uses control packets on a common control channel to faciliate a three-way handshake
between...
Structural health monitoring (SHM) systems perform automated non-destructive damage detection and characterization for a variety of large structures including civil structures such as bridges and aerospace structures such as aircrafts and space vehicles. The goals of SHM include preventing catastrophic structural failures, increasing reliability, reducing maintenance costs, and increasing the...
Among the many safety hazards facing chainsaw operators, the phenomenon known as kickback is the most dangerous. Kickback occurs when the chain at the tip of the chainsaw is caused to stop abruptly, and transfers the energy of the cutting chain to motion of the saw. The saw will rotate...
This dissertation explores algorithms for learning ranking functions to efficiently solve search problems, with application to automated planning. Specifically, we consider the frameworks of beam search, greedy search, and randomized search, which all aim to maintain tractability at the cost of not guaranteeing completeness nor optimality. Our learning objective for...
In the field of machine learning, clustering and classification are two fundamental tasks. Traditionally, clustering is an unsupervised method, where no supervision about the data is available for learning; classification is a supervised task, where fully-labeled data are collected for training a classifier. In some scenarios, however, we may not...
Data converters are essential interface circuits between the analog world that people live in and the digital processors that people live with. Linearity, which often is a tradeoff against other performance criteria, is one of the major performance demands from applications for both analog-to-digital converts (ADC) and digital-to-analog converters (DAC)....
Voltage controlled oscillator (VCO) based ADC is an important class of time-domain ADC that has gained widespread acceptance due to their several desirable properties. VCO-based ADCs behave like an open-loop continuous time ΔΣ modulator and achieve excellent resolution by first order noise shaping the quantization error. However, the SNDR of...
Maintaining the sustainability of the earth’s ecosystems has attracted much attention as these ecosystems are facing more and more pressure from human activities. Machine learning can play an important role in promoting sustainability as a large amount of data is being collected from ecosystems. There are at least three important...
Incremental ADCs (IADCs) have many advantages for low-frequency high-accuracy data conversion—they are easy to multiplex between channels, need simpler digital decimation filter, and allow extended counting with a Nyquist-rate ADC. A single-loop incremental ADC was designed and fabricated in 90 nm for a biosensor interface circuit. It incorporates one integrator,...
Frequency synthesizers are critical components of all communication systems. This thesis considers the issue of undesirable frequency spurs of a relatively recent type of frequency synthesis architecture called digital-to-time conversion (DTC). The DTC-based frequency synthesis architecture has important performance benefits over older frequency synthesizers, such as fast frequency switching, large...
Magnetic thin films have potential to improve devices such as on-chip inductors, and enable new technologies such as magnetic random access memory (MRAM).
The use of magnetic cores in on-chip inductors is typically limited to applications well under 1 GHz. At higher frequencies, the performance of the magnetic core is...
We consider the problem of supervised classification of bird species from audio recordings in a real-world acoustic monitoring scenario (i.e. audio data is collected in the field with an omnidirectional microphone, without human supervision). Obtaining better data about bird activity can assist conservation efforts, and improve our understanding of their...
In this work, we study network coding technique, its relation to random matrices, and their applications to communication systems. The dissertation consists of three main contributions. First, we propose efficient algorithms for data synchronization via a broadcast channel using random network coding. Second, we study the resiliency of network coding...
The world's demand for energy is an ongoing challenge, which has yet to be overcome.
The efforts to find clean energy alternatives to fossil fuels have been hampered by the
lack of investment in technology and research. Among these clean energy alternatives
are ocean waves and wind. Wind power is...
A distributed system is a network of multiple autonomous computational nodes designed primarily for performance scalability and robustness. The performance of a distributed system depends critically on how tasks and resources are distributed among the nodes. Thus, a main thrust in distributed system research is to design schemes for distributing...
Gibbs sampling method is an important tool used in parameter estimation for many probabilistic models. Specifically, for many scenarios, it is difficult to generate high-dimensional data samples from its joint distribution. The Gibbs sampling provides a way to draw high-dimensional data via the conditional distributions which are typically easier to...
This dissertation addresses the problem of video labeling at both the frame and pixel levels using deep learning. For pixel-level video labeling, we have studied two problems: i) Spatiotemporal video segmentation and ii) Boundary detection and boundary flow estimation. For the problem of spatiotemporal video segmentation, we have developed recurrent...
Indoor positioning systems can be used for many applications such as indoor navigation,emergence response, asset monitoring, and shopper assistance. Due to the weak received signal and multipath reflection, the global positioning system (GPS) generally does not work in indoor environments. There are a variety of radio frequency (RF) signals and...
Triangulateration uses geometric distance to estimate the location of user by employing techniques like received signal strength (RSS), time-of-arrival (TOA), time-difference-of-arrival (TDOA) and image processing.
Radio frequency (RF) signal positioning using TOA or TDOA techniques generally requires timing synchronization of the anchors and/or the anchors and targets. If the desired...
Incremental ADCs (IADCs) have found wide applications in sensor interface circuitry since, compared to ∆Σ ADCs, they provide low-latency high-accuracy conversion and easy multiplexing among multiple channels. On the other hand, continuous-time ∆Σ ADCs (CTDSM) have been receiving more and more attention as a power-efficient solution in targeting medium to...
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...
Auctions are used to solve resource allocation problem between many agents and many items in real-world settings. Unfortunately, in most cases, it is possible for selfish agents to manipulate the system for their own interest at the expense of the social welfare. Such manipulation can be prevented using the Vickrey-Clarke-Groves...
This work presents improvements to a multi-core performance/power simulator. The improvements which include updated power models, voltage scaling aware models, and an application specific benchmark, are done to increase the accuracy of power models under voltage and frequency scaling. Improvements to the simulator enable more accurate design space exploration for...
In bioacoustics, automatic animal voice detection and recognition from audio recordings is an emerging topic for animal preservation. Our research focuses on bird bioacoustics, where the goal is to segment bird syllables from the recording and predict the bird species for the syllables. Traditional methods for this task addresses the...
This thesis concerns the development of a direct torque control strategy using a sliding mode control approach to optimize the power output of an oscillating water column (OWC) wave energy converter (WEC). The OWC WEC is a device that has a submerged vertical tail tube open at both ends, which...