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Articles 1  10 of 10
FullText Articles in Engineering
Dark Current RtsNoise In Silicon Image Sensors, Benjamin William Hendrickson
Dark Current RtsNoise In Silicon Image Sensors, Benjamin William Hendrickson
Dissertations and Theses
Random Telegraph Signal (RTS) noise is a random noise source defined by discrete and metastable changes in the magnitude of a signal. Though observed in a variety of physical processes, RTS is of particular interest to image sensor fabrication where progress in the suppression of other noise sources has elevated its noise contribution to the point of approaching the limiting noise source in scientific applications.
There have been two basic physical sources of RTS noise reported in image sensors. The first involves a charge trap in the oxide layer of the source follower in a CMOS image sensor. The capture ...
A Spline Framework For Optimal Representation Of Semiperiodic Signals, Farzin G. Guilak
A Spline Framework For Optimal Representation Of Semiperiodic Signals, Farzin G. Guilak
Dissertations and Theses
Semiperiodic signals possess an underlying periodicity, but their constituent spectral components include stochastic elements which make it impossible to analytically determine locations of the signal's critical points. Mathematically, a signal's critical points are those at which it is not differentiable or where its derivative is zero. In some domains they represent characteristic points, which are locations indicating important changes in the underlying process reflected by the signal.
For many applications in healthcare, knowledge of precise locations of these points provides key insight for analytic, diagnostic, and therapeutic purposes. For example, given an appropriate signal they might indicate the ...
Performance Metrics For DepthBased Signal Separation Using Deep Vertical Line Arrays, John K. Boyle
Performance Metrics For DepthBased Signal Separation Using Deep Vertical Line Arrays, John K. Boyle
Dissertations and Theses
Vertical line arrays (VLAs) deployed below the critical depth in the deep ocean can exploit reliable acoustic path (RAP) propagation, which provides low transmission loss (TL) for targets at moderate ranges, and increased TL for distant interferers. However, sound from nearby surface interferers also undergoes RAP propagation, and without horizontal aperture, a VLA cannot separate these interferers from submerged targets. A recent publication by McCargar and Zurk (2013) addressed this issue, presenting a transformbased method for passive, depthbased separation of signals received on deep VLAs based on the depthdependent modulation caused by the interference between the direct and surfacereflected acoustic ...
Enhanced Sonar Array Target Localization Using TimeFrequency Interference Phenomena, Jordan Almon Shibley
Enhanced Sonar Array Target Localization Using TimeFrequency Interference Phenomena, Jordan Almon Shibley
Dissertations and Theses
The ability of traditional active sonar processing methods to detect targets is often limited by clutter and reverberation from ocean environments. Similarly, multipath arrivals from radiating sources such as ships and submarines are received at sensors in passive sonar systems. Reverberation and multipath signals introduce constructive and destructive interference patterns in received spectrograms in both active and passive sonar applications that vary with target range and frequency. The characterization and use of interference phenomena can provide insights into environmental parameters and target movement in conjunction with standard processing methods including spectrograms and array beamforming.
This thesis focuses on utilizing the ...
Automated Channel Assessment For Single Chip Medradio Transceivers, Mark Alexander Hillig
Automated Channel Assessment For Single Chip Medradio Transceivers, Mark Alexander Hillig
Dissertations and Theses
Modern implantable and body worn medical devices leverage wireless telemetry to improve patient experience and expand therapeutic options. Wireless medical devices are subject to a unique set of regulations in which monitoring of the available frequency spectrum is a requirement. To this end, implants use software protocols to assess the inband activity to determine which channel should be used. These software protocols take valuable processing time and possibly degrade the operational lifetime of the battery. Implantable medical devices often take advantage of a single chip transceiver as the physical layer for wireless communications. Embedding the channel assessment task in the ...
Detecting Chaotic Signals With Nonlinear Models, Qin Cai
Detecting Chaotic Signals With Nonlinear Models, Qin Cai
Dissertations and Theses
In this thesis we apply chaotic dynamic data analysis to the area of discrete time signal processing. A newly developed Hidden Filter Hidden Markov Model is introduced in detection of chaotic signals. Numerical experiments have verified that this novel nonlinear model outperforms linear AR model in detecting chaotic signals buried by noise having similar power spectra. A simple Histogram Model is proposed which can also be used to do detection on the data sets with chaotic behavior. Receiver Operating Characteristics for a variety of noise levels and model classes are reported.
A New Approach To The Optimal Filtering Of Differential Phase Measurements Of Gps Signal In The Precision Survey, Shengan Wang
A New Approach To The Optimal Filtering Of Differential Phase Measurements Of Gps Signal In The Precision Survey, Shengan Wang
Dissertations and Theses
The Global Positioning System (GPS) has become popular research and application interests in surveying and many other areas. Nowadays, the accuracy of the Differential GPS can easily reach the order of a few meters. Yet, there are still many ways to exploit the GPS system signal carrier to improve the accuracy to less than meter level. In this thesis, a new approach to improve the accuracy to less than meter level is presented while the observer is in the dynamic situation. In order to reach the submeter accuracy, we measure on the carrier phase difference (The L1 carrier frequency is ...
Applications Of Digital Signal Processing With Cardiac Pacemakers, Merry Thi Tran
Applications Of Digital Signal Processing With Cardiac Pacemakers, Merry Thi Tran
Dissertations and Theses
Because the voltage amplitude of a heart beat is small compared to the amplitude of exponential noise, pacemakers have difficulty registering the responding heart beat immediately after a pacing pulse. This thesis investigates use of digital filters, an inverse filter and a lowpass filter, to eliminate the effects of exponential noise following a pace pulse. The goal was to create a filter which makes recognition of a haversine wave less dependent on natural subsidence of exponential noise. Research included the design of heart system, pacemaker, pulse generation, and D sensor system simulations. The simulation model includes the following components: \ • Signal ...
Characterization Of Quantization Noise In Oversampled Analog To Digital Converters, Eric W. Multanen
Characterization Of Quantization Noise In Oversampled Analog To Digital Converters, Eric W. Multanen
Dissertations and Theses
The analog to digital converter (ADC) samples a continuous analog signal and produces a stream of digital words which approximate the analog signal. The conversion process introduces noise into the digital signal. In the case of an ideal ADC, where all noise sources are ignored, the noise due to the quantization process remains. The resolution of the ADC is defined by how many bits are in the digital output word. The amount of quantization noise is clearly related to the resolution of the ADC. Reducing the quantization noise results in higher effective resolution.
Two New Parallel Processors For Real Time Classification Of 3D Moving Objects And Quad Tree Generation, Farjam Majd
Two New Parallel Processors For Real Time Classification Of 3D Moving Objects And Quad Tree Generation, Farjam Majd
Dissertations and Theses
Two related image processing problems are addressed in this thesis. First, the problem of identification of 3D objects in real time is explored. An algorithm to solve this problem and a hardware system for parallel implementation of this algorithm are proposed. The classification scheme is based on the "Invariant Numerical Shape Modeling" (INSM) algorithm originally developed for 2D pattern recognition such as alphanumeric characters. This algorithm is then extended to 3D and is used for general 3D object identification. The hardware system is an SIMD parallel processor, designed in bit slice fashion for expandability. It consists of a library of ...