COE - Depts - ECE - Faculty - Gendron

faculty

Paul Gendron, PhD

Associate Professor

Electrical & Computer Engineering

508-999-8510

508-999-8489

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Science & Engineering 214D

Education

1999Worcester Polytechnic InstitutePhD in Electrical Engineering
1993Virginia TechMS in Electrical Engineering
1985University of MassachusettsBS in Electrical Engineering

Teaching

Programs

Teaching

Courses

Concepts of probability and statistics as they apply to random signals and their effect on system analysis and design. Topics covered include basic probability, random variables, probability density and distribution functions, joint distributions, conditional distributions, functions of a random variable, mean, variance, covariance, characteristic functions, random processes, correlation functions, power spectral density, linear systems, linear filters, systems that maximize signal-to-noise ratio, and selected applications and designs from communication theory, sonar and radar, and control theory.

Probability theory, signals and linear networks, Fourier transforms, random processes and noise are reviewed. Analog communications including amplitude and frequency modulation with and without noise are studied. Digital communications including baseband pulse modulation, quantization, sampling theory, digital pulse shaping, matched filter, Nyquist criterion and error rates due to noise are covered.

Investigations of a fundamental and/or applied nature intended to develop design techniques, research techniques, initiative and independent inquiry. A written project report has to be completed by the student's advisor. Admission is based on a formal proposal endorsed by an advisor and approved by the ECE Graduate Program Director.

Random variables and probabilistic description of signals and systems. The course provides the analytical tools for studying random phenomena in engineering systems and provides graduate students with an extensive treatment of probability theory, Bayes theorem, random variables, distribution and density functions, conditional distributions, moments, functions of random variables, characteristic functions, stochastic processes, Gaussian processes, stationary processes, correlation functions, power spectral density, response of systems to random inputs, mean square error estimation, filtering and prediction, and noise analysis. The course prepares students for a wide range of courses in communications, signal processing, acoustics, control, and other areas of engineering in which random signals and systems have an important role.

Investigations of a fundamental and/or applied nature, intended to develop design techniques,research techniques, initiative, and independent inquiry. A written thesis must be completed in accordance with the rules of the Graduate School and the College of Engineering. Completion of the course requires a successful oral defense open to the public and a written thesis approved by the student's thesis committee unanimously and the ECE Graduate Program Director. Admission to the course is based on a formal thesis proposal endorsed by the student's graduate committee and submitted to the ECE Graduate Program Director.

Investigations of a fundamental and/or applied nature, intended to develop design techniques,research techniques, initiative, and independent inquiry. A written thesis must be completed in accordance with the rules of the Graduate School and the College of Engineering. Completion of the course requires a successful oral defense open to the public and a written thesis approved by the student's thesis committee unanimously and the ECE Graduate Program Director. Admission to the course is based on a formal thesis proposal endorsed by the student's graduate committee and submitted to the ECE Graduate Program Director.

For PhD students who plan to take the PhD Comprehensive exam within the next 3 months. Up to 6 credits may be applied to either doctoral dissertation or MS thesis (should student not pass Comprehensive exam). Graded P/F.

For PhD students who plan to take the PhD Comprehensive exam within the next 3 months. Up to 6 credits may be applied to either doctoral dissertation or MS thesis (should student not pass Comprehensive exam). Graded P/F.

For PhD students who plan to take the PhD Comprehensive exam within the next 3 months. Up to 6 credits may be applied to either doctoral dissertation or MS thesis (should student not pass Comprehensive exam). Graded P/F.

For PhD students who plan to take the PhD Comprehensive exam within the next 3 months. Up to 6 credits may be applied to either doctoral dissertation or MS thesis (should student not pass Comprehensive exam). Graded P/F.

Research

Research awards

  • $ 269,704 awarded by Office of Naval Research for UMassD MUST I: Incremental Learning with Human-in-the-Loop for Underwater Anomaly Detection
  • $ 325,747 awarded by Office of Naval Research for UMassD MUST III: Underwater Signal Processing for Remote Sensing and Communications
  • $ 476,926 awarded by Office of Naval Research for UMassD MUST I: Deep Learning-Enabled Detection and Classification of Acoustic Signals in Underwater Channels

Research

Research interests

  • Adaptive filtering for angle-delay-Doppler spread channels
  • Low probability of detection acoustic communications
  • Magnetic anomaly detection and tracking
  • Seismic event detection and classification

Paul J. Gendron received his PhD from Worcester Polytechnic Institute, his MS from Viginia Tech and his BS from the University of Massachusetts Amherst, all in Electrical Engineering. His work is broad in the field of statistical signal processing, detection and estimation theory. His contributions range from seismic event detection and classification to adaptive filtering and low probability of detection acoustic communications. He was with the Naval Research Laboratory from 2000 to 2007 and with the Spawar Systems Center Pacific from 2008 to 2012. In 2000, he was the recipient of an Office of Naval Research research fellowship award for his work with the Acoustic Division at the Naval Research Laboratory. In 2006, he served as an Office of Naval Research Visiting Scientist at DRDC-Atlantic, Canada. Dr. Gendron presently conducts research for the Office of Naval Research related to the discover and invention of enabling technologies for undersea surveillance.