Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Electrical and Computer Engineering (12)
- Education (4)
- Higher Education (4)
- Computer Engineering (3)
- Acoustics, Dynamics, and Controls (2)
-
- Biomedical Engineering and Bioengineering (2)
- Mechanical Engineering (2)
- Scholarship of Teaching and Learning (2)
- Science and Mathematics Education (2)
- Civil and Environmental Engineering (1)
- Computer Sciences (1)
- Computer and Systems Architecture (1)
- Controls and Control Theory (1)
- Electrical and Electronics (1)
- Engineering Education (1)
- Other Electrical and Computer Engineering (1)
- Physical Sciences and Mathematics (1)
- Power and Energy (1)
- Keyword
-
- Memristors (3)
- Academic achievement (2)
- Engineering -- Study and teaching (Higher) (2)
- Neural networks (Computer science) (2)
- Prediction models (2)
-
- Acoustic beamforming (1)
- Acoustic imaging (1)
- Acoustical engineering (1)
- Acoustics instrumentation (1)
- Asynchronous circuits (1)
- Beamforming (1)
- Coherence (1)
- Computer architecture -- Design (1)
- Computer software (1)
- Coupled -- Oscillator Arrays (1)
- Delay lines (1)
- Digital integrated circuits -- Design and construction (1)
- Drought forecasting -- Simulation methods (1)
- Eigenvectors (1)
- Electric circuits (1)
- Electric power systems -- Mathematical models -- Analysis (1)
- Electric power transmission (1)
- Electrical engineering -- Study and teaching (Higher) (1)
- Electrocardiography (1)
- Engineering -- Study and teaching (1)
- Hopfield networks (1)
- Hybrid circuits (1)
- Hydrophone -- Application to detection and localization (1)
- Inertial sensors (1)
- Kalman filtering -- Algorithms (1)
Articles 1 - 19 of 19
Full-Text Articles in Engineering
Modeling And Experimental Demonstration Of A Hopfield Network Analog-To-Digital Converter With Hybrid Cmos/Memristor Circuits, Xinjie Guo, Farnood Merrikh-Bayat, Ligang Gao, Brian D. Hoskins, Fabien Alibart, Bernabe Linares-Barranco, Luke Theogarajan, Christof Teuscher, Dmitri B. Strukov
Modeling And Experimental Demonstration Of A Hopfield Network Analog-To-Digital Converter With Hybrid Cmos/Memristor Circuits, Xinjie Guo, Farnood Merrikh-Bayat, Ligang Gao, Brian D. Hoskins, Fabien Alibart, Bernabe Linares-Barranco, Luke Theogarajan, Christof Teuscher, Dmitri B. Strukov
Electrical and Computer Engineering Faculty Publications and Presentations
The purpose of this work was to demonstrate the feasibility of building recurrent artificial neural networks with hybrid complementary metal oxide semiconductor (CMOS)/memristor circuits. To do so, we modeled a Hopfield network implementing an analog-to-digital converter (ADC) with up to 8 bits of precision. Major shortcomings affecting the ADC's precision, such as the non-ideal behavior of CMOS circuitry and the specific limitations of memristors, were investigated and an effective solution was proposed, capitalizing on the in-field programmability of memristors. The theoretical work was validated experimentally by demonstrating the successful operation of a 4-bit ADC circuit implemented with discrete Pt/TiO2− …
Computational Capacity And Energy Consumption Of Complex Resistive Switch Networks, Jens Bürger, Alireza Goudarzi, Darko Stefanovic, Christof Teuscher
Computational Capacity And Energy Consumption Of Complex Resistive Switch Networks, Jens Bürger, Alireza Goudarzi, Darko Stefanovic, Christof Teuscher
Electrical and Computer Engineering Faculty Publications and Presentations
Resistive switches are a class of emerging nanoelectronics devices that exhibit a wide variety of switching characteristics closely resembling behaviors of biological synapses. Assembled into random networks, such resistive switches produce emerging behaviors far more complex than that of individual devices. This was previously demonstrated in simulations that exploit information processing within these random networks to solve tasks that require nonlinear computation as well as memory. Physical assemblies of such networks manifest complex spatial structures and basic processing capabilities often related to biologically-inspired computing. We model and simulate random resistive switch networks and analyze their computational capacities. We provide a …
Project-Based Rf/Microwave Education, Richard L. Campbell, Branimir Pejcinovic
Project-Based Rf/Microwave Education, Richard L. Campbell, Branimir Pejcinovic
Electrical and Computer Engineering Faculty Publications and Presentations
Immediate application of learned fundamentals to laboratory work is standard practice in Electrical Engineering Education, but student explorations of basic RF/Microwave circuits at the transistor-electromagnetics level are particularly challenging. This paper describes an interconnected set of basic electromagnetic and transistor-level RF/Microwave modules that may be assembled into a short range wireless link or modulated scatterer radar system. These Analog/RF/Microwave building blocks are used across the Senior and Graduate Level curriculum.
Fast Sequence Component Analysis For Attack Detection In Synchrophasor Networks, Jordan Landford, Rich Meier, Richard Barella, Xinghui Zhao, Robert B. Bass, Scott Wallace
Fast Sequence Component Analysis For Attack Detection In Synchrophasor Networks, Jordan Landford, Rich Meier, Richard Barella, Xinghui Zhao, Robert B. Bass, Scott Wallace
Electrical and Computer Engineering Faculty Publications and Presentations
Modern power systems have begun integrating synchrophasor technologies into part of daily operations. Given the amount of solutions offered and the maturity rate of application development it is not a matter of "if" but a matter of "when" in regards to these technologies becoming ubiquitous in control centers around the world. While the benefits are numerous, the functionality of operator-level applications can easily be nullified by injection of deceptive data signals disguised as genuine measurements. Such deceptive action is a common precursor to nefarious, often malicious activity. A correlation coefficient characterization and machine learning methodology are proposed to detect and …
A Computational Method To Predict And Study Underwater Noise Due To Pile Driving, Scott Schecklman, Nathan Laws, Lisa M. Zurk, Martin Siderius
A Computational Method To Predict And Study Underwater Noise Due To Pile Driving, Scott Schecklman, Nathan Laws, Lisa M. Zurk, Martin Siderius
Electrical and Computer Engineering Faculty Publications and Presentations
A hybrid modeling approach that uses the parabolic equation (PE) with an empirical source model is presented to study and predict the underwater noise due to pile driving in shallow, inhomogeneous environments over long propagation ranges. The empirical source model uses a phased point source array to simulate the time-dependent pile source. The pile source is coupled with a broadband application of a PE wave propagation model that includes range dependent geoacoustic properties and bathymetry. Simulation results are shown to be in good agreement with several acoustic observations of pile driving in the Columbia River between Portland, OR and Vancouver, …
Enhancing Freshman Engineering Instruction With In-Class Interaction Systems And E-Books, Branimir Pejcinovic, Phillip K. Wong
Enhancing Freshman Engineering Instruction With In-Class Interaction Systems And E-Books, Branimir Pejcinovic, Phillip K. Wong
Electrical and Computer Engineering Faculty Publications and Presentations
Electrical engineering students in our department take a year-long series of courses which introduces electrical engineering as a discipline and provides good grounding in engineering problem solving and programing. We have recently attempted to make the second course in the sequence more engaging by applying active learning techniques, including assigned reading and exercises prior to lectures, in-class exercises using a classroom interaction system, and programming exercises during lectures. Our results are mixed: while we think that students have learned more than if we had not used these techniques, we have not completely won over our students. While using an e-book …
Hierarchical Composition Of Memristive Networks For Real-Time Computing, Jens Bürger, Alireza Goudarzi, Darko Stefanovic, Christof Teuscher
Hierarchical Composition Of Memristive Networks For Real-Time Computing, Jens Bürger, Alireza Goudarzi, Darko Stefanovic, Christof Teuscher
Electrical and Computer Engineering Faculty Publications and Presentations
Advances in materials science have led to physical instantiations of self-assembled networks of memristive devices and demonstrations of their computational capability through reservoir computing. Reservoir computing is an approach that takes advantage of collective system dynamics for real-time computing. A dynamical system, called a reservoir, is excited with a time-varying signal and observations of its states are used to reconstruct a desired output signal. However, such a monolithic assembly limits the computational power due to signal interdependency and the resulting correlated readouts. Here, we introduce an approach that hierarchically composes a set of interconnected memristive networks into a larger reservoir. …
Development And Uses Of Iterative Systematic Literature Reviews In Electrical Engineering Education, Branimir Pejcinovic
Development And Uses Of Iterative Systematic Literature Reviews In Electrical Engineering Education, Branimir Pejcinovic
Electrical and Computer Engineering Faculty Publications and Presentations
It is expected that most, if not all, graduate students will posses skills necessary for doing literature reviews. It is less clear how to teach these skills most effectively especially to students who are area novices and unfamiliar with review process. Systematic literature reviews offer a solid instructional framework which can be implemented across curriculum and offer an opportunity to teach course material differently so that student learn not just the literature review technique itself but also some segment of the course material. Our pilot study investigated issues related to practical implementation of systematic literature reviews in two classes, with …
Teaching Matlab And C Programming In First Year Electrical Engineering Courses Using A Data Acquisition Device, Phillip Wong, Branimir Pejcinovic
Teaching Matlab And C Programming In First Year Electrical Engineering Courses Using A Data Acquisition Device, Phillip Wong, Branimir Pejcinovic
Electrical and Computer Engineering Faculty Publications and Presentations
Our industry partners often voice a complaint that our newly graduated electrical engineering (EE) students do not have sufficient programming skills. This is not a new concern. In a traditional undergraduate EE curriculum, one or two programming courses compose the entirety of the student’s training in programming. The courses may be taught by the computer science department without significant emphasis on engineering fundamentals. While the principles of computer science may be well covered, the ability to apply the knowledge to practical engineering problems is frequently lacking. To compound the problem, teaching novices the basics of programming can be very challenging …
Using Systematic Literature Reviews To Enhance Student Learning, Branimir Pejcinovic
Using Systematic Literature Reviews To Enhance Student Learning, Branimir Pejcinovic
Electrical and Computer Engineering Faculty Publications and Presentations
Literature review is a skill assumed to be in the arsenal of all graduate students pursuing thesis options at the MS or PhD level. There are many resources on writing literature reviews, from campus writing centers to books such as Machi and McEvoy. One would also assume that this is among the very first tasks that research-oriented students would undertake. However, our brief and preliminary survey of graduate students in our electrical and computer engineering department showed that they have very little to no experience in performing literature reviews, and discussions with other faculty confirmed this observation. Unlike some other …
Tracking Of Rhythmical Biomedical Signals Using The Maximum A Posteriori Adaptive Marginalized Particle Filter, Sunghan Kim, Lars Andreas Holmstrom, James Mcnames
Tracking Of Rhythmical Biomedical Signals Using The Maximum A Posteriori Adaptive Marginalized Particle Filter, Sunghan Kim, Lars Andreas Holmstrom, James Mcnames
Electrical and Computer Engineering Faculty Publications and Presentations
Biomedical signals are often rhythmical and their morphologies change slowly over time. Arterial blood pressure and electrocardiogram signals are good examples with such property. It is of great interest to extract clinically useful information such as the instantaneous frequency (i.e. heart rate) and morphological changes (e.g. pulse pressure variation) from these signals. Conventional filtering methods such as the Kalman filter are not suitable for estimating the instantaneous frequency of quasiperiodic signals due to the non-Gaussian multi-modal property of its posterior distribution. One possible alternative is particle filters that are increasingly used for nonlinear systems and non-Gaussian posterior state distributions. However, …
A Two-Hydrophone Range And Bearing Localization With Performance Analysis, John Thomas Gebbie, Martin Siderius, John S. Allen Iii
A Two-Hydrophone Range And Bearing Localization With Performance Analysis, John Thomas Gebbie, Martin Siderius, John S. Allen Iii
Electrical and Computer Engineering Faculty Publications and Presentations
An automated, passive algorithm for detecting and localizing small boats using two hydrophones mounted on the seabed is outlined. This extends previous work by Gebbie et al. [(2013). J. Acoust. Soc. Am. 134, EL77 − EL83] in which a similar two-hydrophone approach is used to produce an ambiguity surface of likely target locations leveraging multipath analysis and knowledge of the local bathymetry. The work presented here improves upon the prior approach using particle filtering to automate detection and localization processing. A detailed analysis has also been conducted to determine the conditions and limits under which the improved approach can be …
Semi-Modular Delay Model Revisited In Context Of Relative Timing, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song
Semi-Modular Delay Model Revisited In Context Of Relative Timing, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song
Electrical and Computer Engineering Faculty Publications and Presentations
A new definition of semi-modularity to accommodate relative timing constraints in self-timed circuits is presented. While previous definitions ignore such constraints, the new definition takes them into account. The difference on a design solution for a well-known speed-independent circuit implementation of the Muller C element and a set of relative timing constraints that renders the implementation hazard free is illustrated. The old definition produces a false semi-modularity conflict that cannot exist due to the set of imposed constraints. The new definition correctly accepts the solution.
Coupled-Oscillator Associative Memory Array Operation For Pattern Recognition, Dmitri E. Nikonov, Gyorgy Csaba, Wolfgang Porod, Tadashi Shibata, Danny Voils, Dan Hammerstrom, Ian A. Young, George I. Bourianoff
Coupled-Oscillator Associative Memory Array Operation For Pattern Recognition, Dmitri E. Nikonov, Gyorgy Csaba, Wolfgang Porod, Tadashi Shibata, Danny Voils, Dan Hammerstrom, Ian A. Young, George I. Bourianoff
Electrical and Computer Engineering Faculty Publications and Presentations
Operation of the array of coupled oscillators underlying the associative memory function is demonstrated for various interconnection schemes (cross-connect, star phase keying and star frequency keying) and various physical implementation of oscillators (van der Pol, phase-locked loop, spin torque). The speed of synchronization of oscillators and the evolution of the degree of matching is studied as a function of device parameters. The dependence of errors in association on the number of the memorized patterns and the distance between the test and the memorized pattern is determined for Palm, Furber and Hopfield association algorithms.
High-Resolution Bottom-Loss Estimation Using The Ambient-Noise Vertical Coherence Function, Lanfranco Muzi, Martin Siderius, Jorge E. Quijano, Stan E. Dosso
High-Resolution Bottom-Loss Estimation Using The Ambient-Noise Vertical Coherence Function, Lanfranco Muzi, Martin Siderius, Jorge E. Quijano, Stan E. Dosso
Electrical and Computer Engineering Faculty Publications and Presentations
The seabed reflection loss (shortly "bottom loss") is an important quantity for predicting transmission loss in the ocean. A recent passive technique for estimating the bottom loss as a function of frequency and grazing angle exploits marine ambient noise (originating at the surface from breaking waves, wind, and rain) as an acoustic source. Conventional beamforming of the noise field at a vertical line array of hydrophones is a fundamental step in this technique, and the beamformer resolution in grazing angle affects the quality of the estimated bottom loss. Implementation of this technique with short arrays can be hindered by their …
Eigenvector Pruning Method For High Resolution Beamforming, Jorge E. Quijano, Lisa M. Zurk
Eigenvector Pruning Method For High Resolution Beamforming, Jorge E. Quijano, Lisa M. Zurk
Electrical and Computer Engineering Faculty Publications and Presentations
This paper introduces an eigenvector pruning algorithm for the estimation of the signal-plus-interference eigenspace, required as a preliminary step to subspace beamforming. The proposed method considers large-aperture passive array configurations operating in environments with multiple maneuvering targets in background noise, in which the available data for estimation of sample covariances and eigenvectors are limited. Based on statistical properties of scalar products between deterministic and complex random vectors, this work defines a statistically justified threshold to identify target-related features embedded in the sample eigenvectors, leading to an estimator for the signal-bearing eigenspace. It is shown that data projection into this signal …
Modular Timing Constraints For Delay-Insensitive Systems, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song, Ivan Sutherland
Modular Timing Constraints For Delay-Insensitive Systems, Hoon Park, Anping He, Marly Roncken, Xiaoyu Song, Ivan Sutherland
Electrical and Computer Engineering Faculty Publications and Presentations
This paper introduces ARCtimer, a framework for modeling, generating, verifying, and enforcing timing constraints for individual self-timed handshake components. The constraints guarantee that the component’s gate-level circuit implementation obeys the component’s handshake protocol specification. Because the handshake protocols are delayinsensitive, self-timed systems built using ARCtimer-verified components are also delay-insensitive. By carefully considering time locally, we can ignore time globally. ARCtimer comes early in the design process as part of building a library of verified components for later system use. The library also stores static timing analysis (STA) code to validate and enforce the component’s constraints in any self-timed system built …
Wavelet-Coupled Machine Learning Methods For Drought Forecast Utilizing Hybrid Meteorological And Remotely-Sensed Data, R. Tan, Marek Perkowski
Wavelet-Coupled Machine Learning Methods For Drought Forecast Utilizing Hybrid Meteorological And Remotely-Sensed Data, R. Tan, Marek Perkowski
Electrical and Computer Engineering Faculty Publications and Presentations
In this study, a statistical drought early warning method is proposed using novel machine learning algorithms, with the inclusion of multiple drought-related attributes from precipitation, satellite-derived land cover vegetation indices, and surface discharge. The forecast is made for the long-term hydrological drought in the region of Central Valley, California. The wavelet transform analysis is employed in combination with support vector regression and artificial neural network algorithms for improving the drought prediction effectiveness. The performance of the drought prediction is evaluated using three statistical metrics: Coefficient of Determination (R2 ), Root-Mean-Square Error (RMSE), and Mean-Absolute-Error (MAE). The results clearly indicate that …
Continuous Monitoring Of Movement In Patients With Parkinson's Disease Using Inertial Sensors, Mahmoud Ahmed El-Gohary, Sean Pearson, James Mcnames, Martina Mancini, Fay Horak
Continuous Monitoring Of Movement In Patients With Parkinson's Disease Using Inertial Sensors, Mahmoud Ahmed El-Gohary, Sean Pearson, James Mcnames, Martina Mancini, Fay Horak
Electrical and Computer Engineering Faculty Publications and Presentations
Gait impairment is a hallmark of Parkinson's disease (PD). The assessment of gait and balance in the clinic may not adequately reflect mobility in daily life. It is often reported that patients with PD walk better when they are examined in an outpatient clinic or in a research laboratory than at home. Continuous monitoring of mobility during spontaneous daily activities may provide clinicians and patients with objective measures of the quality of their mobility. We show that continuous monitoring of spontaneous gait with wearable inertial sensors during daily activities is feasible for patients with PD. We tested 13 patients with …