Faculty Profile
David Delchamps
Department: ECE
Title: Associate Professor, Advising Coordinator
Personal Web Site:
http://people.ece.cornell.edu/dave/
Degrees earned:
B.S. Princeton 1976
M.S. Harvard 1977
Ph.D. Harvard 1982
Address:
Office:
329 Rhodes Hall
Ithaca, NY, 14853
Office Phone: (607) 255-6447
Biography:
David F. Delchamps is originally from Morristown, NJ. Since receiving the doctoral degree, he has been on the faculty of the School of Electrical Engineering and a member of the Center for Applied Mathematics at Cornell, where he is currently Associate Professor. He has received several department- and college-level teaching awards, and was the recipient of an NSF Presidential Young Investigator Award in 1984. He is a member of the IEEE, the American Mathematical Society, Phi Beta Kappa, and Tau Beta Pi, and is also the author of several technical articles and the book State Space and Input-Output Linear Systems (Springer-Verlag, 1988). He does research in the area of control and systems theory, with special emphasis on the theory of estimation and control of nonlinear systems.
Research interests:
The behavior of a large class of processes in engineering and the physical sciences can be described fairly accurately in terms of mathematical models that take the form of linear and nonlinear dynamical systems. Our current research focuses on applying new mathematical techniques to the solution of certain fundamental problems that arise in the theory of such models. Of special interest to us are problems involving feedback control systems that have complicated dynamical properties such as chaotic state evolution or pseudorandom asymptotics. Such systems arise in many important applications; we have found numerous examples of chaotic and pseudorandom asymptotic behavior in dynamic analog-to-digital converters such as delta-sigma modulators and in practical implementations of feedback control systems with continuous-variable dynamics using digital controllers. The roundoff error that one incurs because of quantized measurements of real numbers and finiteprecision arithmetic are to blame for the complicated dynamical phenomena; we have modeled these phenomena using techniques from the ergodic theory of dynarnical systems that have heretofore had minimal impact in signal processing and control systems contexts. We are also pursuing some new approaches to the "intelligent" design of feedback control systems that are subject to finite-precision effects such as those described in the foregoing.
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