Signal Processing Commons^™

Technologies For Wearable Seizure Detection: A Systematic Review, Rhema Losli

University Honors Theses

Knowing when a seizure occurred is helpful because this information can be used to evaluate the effectiveness of seizure interventions and possibly alert caregivers to emergency situations. The current practice for recording seizures outside of a hospital and without sensors is through keeping a self-reported seizure diary. This practice may be unreliable if the diary is not updated or the person having the seizure does not realize it is happening. Wearable seizure detectors aim to solve this problem by reliably recording when a seizure happened and either sending out an alert or storing the data for later analysis. In this …

Comparison Of Conventional And Adaptive Acoustic Beamforming Algorithms Using A Tetrahedral Microphone Array In Noisy Environments, Megan Brittany Ewers

Dissertations and Theses

In situ acoustic measurements are often plagued by interfering sound sources that occur within the measurement environment. Both adaptive and conventional beamforming algorithms, when applied to the outputs of a microphone array arranged in a tetrahedral geometry, are able to capture sound sources in desired directions and reject sound from unwanted directions. Adaptive algorithms may be able to measure a desired sound source with greater spatial precision, but require more calculations and, therefore, computational power. A conventional frequency-domain phase-shift algorithm and a modified adaptive frequency-domain Minimum Variance Distortionless Response (MVDR) algorithm were applied to simulated and recorded signals from a …

A Simplified Accuracy Enhancement To The Saleh Am/Am Modeling And Linearization Of Solid-State Rf Power Amplifiers, Haider Al-Kanan, Fu Li

Electrical and Computer Engineering Faculty Publications and Presentations

The Saleh behavioral model exhibits high prediction accuracy for nonlinearity of traveling-wave tube power amplifiers (TWT-PAs). However, the accuracy of the Saleh model degrades when modeling solid-state power amplifiers (SSPAs) technology. In addition, the polynomial expansion of the Saleh model consists of only odd-order terms as analyzed in this work. This paper proposes a novel model accuracy enhancement for the Saleh amplitude-to-amplitude (AM/AM) model when applied to radio frequency (RF) SSPAs. The proposed model enhancement accounts for the second-order intermodulation distortion, which is an important nonlinearity challenge in wideband wireless communications. The proposed static AM/AM model is a three-parameter rational …

Improved Estimation For Saleh Model And Predistortion Of Power Amplifiers Using 1-Db Compression Point, Haider Al Kanan, Xianzhen Yang, Fu Li

Electrical and Computer Engineering Faculty Publications and Presentations

This paper proposes an improved estimation approach for modelling RF power amplifiers (PAs) using the Saleh behavioural model. The proposed approach is appropriate for solid-state PA technologies. The 1-dB compression point of the PA is included in the estimation approach to improve the estimation of the Saleh coefficients. Thus, expressions are derived to describe the relationship between the parameters of the Saleh model and the manufacturing specifications of PAs: gain (G), third-order intercept point (IP₃) and 1-dB compression point (P_1dB). This method is a simple estimation of a memoryless amplitude-to-amplitude (AM/AM) nonlinearity to benefit RF designers …

Dark Current Rts-Noise 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 …

On Dual-Band Amplifications Using Dual Two-Tones: Clarifications And Discussion, Siyuan Yan, Xianzhen Yang, Xiao Li, Fu Lo

Electrical and Computer Engineering Faculty Publications and Presentations

A significant development of recent research in nonlinear distortion is the expansion of the conventional two-tone test for power amplifiers to the concurrent dual-band transmitters, by Amin et al. A general framework using dual two-tones is developed, which shows that the output signal is affected not only by intermodulation (IM) products but also by cross-modulation (CM) products. In this paper, we will make a number of clarifications to Amin et al.'s paper. The effects of IM and CM in passband will be discussed, IM represents a reduction for compressive devices, and CM reflects an interference caused by the signal from …

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 start or …

Performance Metrics For Depth-Based 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 transform-based method for passive, depth-based separation of signals received on deep VLAs based on the depth-dependent modulation caused by the interference between the direct and surface-reflected acoustic …

An Eigenvector-Based Test For Local Stationarity Applied To Array Processing, Jorge Quijano, Lisa M. Zurk

Electrical and Computer Engineering Faculty Publications and Presentations

In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer.

A Comparative Study Of Reservoir Computing For Temporal Signal Processing, Alireza Goudarzi, Peter Banda, Matthew R. Lakin, Christof Teuscher, Darko Stefanovic

Computer Science Faculty Publications and Presentations

Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir's state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who study the task-solving performance and computational power of RC. In addition, in contrast to traditional computation models, the reservoir is a dynamical system in which computation and memory are inseparable, and therefore hard to analyze. Here, we compare …

Enhanced Sonar Array Target Localization Using Time-Frequency 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

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 in-band 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 …

Automated Extraction And Classification Of Time-Frequency Contours In Humpback Vocalizations, Hui Ou, Whitlow W.L. Au, Lisa M. Zurk, Marc O. Lammers

Electrical and Computer Engineering Faculty Publications and Presentations

A time-frequency contour extraction and classification algorithm was created to analyze humpback whale vocalizations. The algorithm automatically extracted contours of whale vocalization units by searching for gray-level discontinuities in the spectrogram images. The unit-to-unit similarity was quantified by cross-correlating the contour lines. A library of distinctive humpback units was then generated by applying an unsupervised, cluster-based learning algorithm. The purpose of this study was to provide a fast and automated feature selection tool to describe the vocal signatures of animal groups. This approach could benefit a variety of applications such as species description, identification, and evolution of song structures. The …

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

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 sub-meter accuracy, we measure on the carrier phase difference (The L1 carrier frequency is …

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 sensor system simulations. The simulation model includes the following components:

• Signal source, …

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 3-D 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 3-D 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 2-D pattern recognition such as alphanumeric characters. This algorithm is then extended to 3-D and is used for general 3-D object identification. The hardware system is an SIMD parallel processor, designed in bit slice fashion for expandability. It consists of a library of …