Karen Payton, PhD
Professor
Electrical & Computer Engineering
Contact
508-999-8434
508-999-8489
kpayton@umassd.edu
Science & Engineering 214A
Education
| 1986 | Johns Hopkins University | PhD in Electrical Engineering |
| 1981 | Johns Hopkins University | MS in Electrical Engineering |
| 1977 | Carnegie Mellon University | BS in Electrical & Biomedical Engineering |
Teaching
Programs
- Biomedical Engineering and Biotechnology MS, PhD
- Computer Engineering BS, BS/MS
- Computer Engineering MS
- Cyber Security Concentration
- Electrical Engineering BS, BS/MS
- Electrical Engineering MS
- Electrical Engineering PhD
Teaching
Courses
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
Biomedical signal characteristics, properties of physiological systems, and mathematical modeling of signals from biosystems and biomedical instrumentation. Applied mathematical methods for describing and analyzing biomedical signals such as ECG, EEG, EMG, heart sounds, breath sounds, blood pressure, and tomographic images are considered. Computational, modeling and simulation tools (e.g., MatLab and LabView) are introduced for biomedical signal processing and systems analysis. A group computer project in bioengineering design will be assigned to enhance the proficiency in using the modeling and simulation tools.
The second course in basic circuit theory and design. Topics include AC circuit steady-state response analysis, review of complex numbers, phasors, coupled inductors and ideal transformers, rms voltage and current, the maximum power transfer theorem, balanced 3-phase systems, and power and energy computations, applications of Laplace transforms to solutions of switched circuits and differential equations with initial conditions, stability, poles/zeros, Fourier transform, frequency response, Bode plots, network analysis, and equivalent circuits. Students are introduced to graphical convolution and Fourier series. Group classroom and project activities require design, implementation and measurement of filters and other circuits to meet design specifications.
The second course in basic circuit theory and design. Topics include AC circuit steady-state response analysis, review of complex numbers, phasors, coupled inductors and ideal transformers, rms voltage and current, the maximum power transfer theorem, balanced 3-phase systems, and power and energy computations, applications of Laplace transforms to solutions of switched circuits and differential equations with initial conditions, stability, poles/zeros, Fourier transform, frequency response, Bode plots, network analysis, and equivalent circuits. Students are introduced to graphical convolution and Fourier series. Group classroom and project activities require design, implementation and measurement of filters and other circuits to meet design specifications.
Introduction to discrete-time signal analysis and linear systems. Topics include time domain analysis of discrete-time linear time-invariant (LTI) systems, solution of difference equations, system function and digital filters, stability and causality, discrete-time Fourier series, discrete-time Fourier transform and discrete Fourier transforms, z-transforms, sampling and the sampling theorem, discrete-time state equations, and communication systems. Students use analysis tools to design systems that meet functional specifications.
Introduction to continuous-time signal analysis and linear systems. Topics include classification of signals and systems, basic signal manipulation, system properties, time domain analysis of continuous-time linear time-invariant (LTI) systems, Laplace transform and its use in LTI system analysis, transfer functions and feedback, frequency response and analog filters, Fourier series representation and properties, continuous-time Fourier transform, spectral analysis and AM modulation, and simulation. Students learn to use signal analysis tools.
Applications of digital signal processing to speech signals. Course goals are to reinforce concepts learned in prerequisite courses, to introduce new tools needed to deal with time-varying signals and to have students apply what they have learned to their own voices. A semester design project is a large component of this course. Topics include a brief introduction to articulatory and acoustic phonetics, hearing and speech perception, time-domain methods for speech processing, short-time Fourier analysis, homomorphic speech processing, linear predictive coding of speech, and applications.
Introduction to engineering and computing with emphasis on development of problem solving skills through projects. The course is designed to increase the success of first year students. It includes an overview of majors in the college, and the importance of engaged learning. Team work, written and oral communication skills are covered. Ethical issues in engineering and computing are discussed.
Introduction to engineering and computing with emphasis on development of problem solving skills through projects. The course is designed to increase the success of first year students. It includes an overview of majors in the college, and the importance of engaged learning. Team work, written and oral communication skills are covered. Ethical issues in engineering and computing are discussed.
Introduction to engineering and computing with emphasis on development of problem solving skills through projects. The course is designed to increase the success of first year students. It includes an overview of majors in the college, and the importance of engaged learning. Team work, written and oral communication skills are covered. Ethical issues in engineering and computing are discussed.
Research
Research interests
- Auditory perception
- Digital signal processing
- Speech acoustics
- Speech processing
Dr. Karen L. Payton is Professor of Electrical and Computer Engineering at the University of Massachusetts Dartmouth and holds a Visiting Scientist position with the Research Laboratory of Electronics at MIT.
She received her B.S. degree as a double major in Electrical and Biomedical Engineering from Carnegie Mellon University. She earned her M.S. and Ph.D. degrees in Electrical Engineering at the Johns Hopkins University.
Dr. Payton is actively involved in research in the area of digital signal processing, as applied to predicting the intelligibility of speech degraded by room acoustics and/or reduced capabilities of a listener. She has also investigated processing capabilities of the auditory system through comparisons of computer simulations of peripheral auditory processing with physiological data.
She is a member of the Acoustical Society of America, the Institute of Electrical and Electronic Engineers, the Society of Women Engineers, and the American Society for Engineering Education.