Karen L. Payton

Karen Payton, PhD

Professor

Electrical & Computer Engineering

508-999-8434

508-999-8489

kpayton@umassd.edu

Science & Engineering 214A


Education

1986Johns Hopkins UniversityPhD in Electrical Engineering
1981Johns Hopkins UniversityMS in Electrical Engineering
1977Carnegie Mellon UniversityBS in Electrical & Biomedical Engineering

Teaching

Programs

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.

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.

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 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.

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.

Methods and techniques for digital signal processing, covering the basic principles governing the design and use of digital systems as signal processing devices. Review of discrete-time linear systems, Fourier transforms and z-transforms. Topics include allpass and minimum-phase systems, linear phase systems and group delay, sampling, decimation, interpolation, discrete-time filter design and implementation, discrete Fourier series, discrete Fourier transform, the fast Fourier transform, and basic spectral estimation. Applications to digital processing of real data are included.

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.

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