2026-09-19T07:24:23Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/283922022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Alan V. Oppenheim.
Dey, Sourav Raj, 1980-
Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
2005-09-26T20:12:09Z
2005-09-26T20:12:09Z
2003
2004
http://hdl.handle.net/1721.1/28392
56961723
Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, June 2004.
Includes bibliographical references (p. 71-72).
In some contexts, DACs fail in such a way that specific samples are dropped. The dropped samples lead to distortion in the analog reconstruction. We refer to this as the "missing pixel" problem. Under certain conditions, it may be possible to compensate for the dropped sample by pre-processing the digital signal, thereby reducing the analog reconstruction error. We develop three such compensation strategies in this thesis. The first strategy uses constrained minimization to calculate the optimal finite-length compensation signal. We develop a closed-form solution using the method of Lagrange multipliers. Next, we develop an approximation to the optimal solution using discrete prolate spheroidal sequences. We show that the optimal solution is a linear combination of the discrete prolates. The last compensation technique we develop is an iterative solution in class of projection-onto-convex-sets. We develop the algorithm and prove that it converges to the optimal solution found using constrained minimization. Each of the three strategies are analyzed and results from numerical simulations are presented.
by Sourav Raj Dey.
M.Eng.
72 p.
2503048 bytes
2510362 bytes
application/pdf
application/pdf
en_US
Massachusetts Institute of Technology
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http://dspace.mit.edu/handle/1721.1/7582
Electrical Engineering and Computer Science.
Digital pre-compensation for faulty D/A converters : the "missing pixel" problem
Digital pre-compensation for faulty digital-to-analog converters
Thesis
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<Abstract>In some contexts, DACs fail in such a way that specific samples are dropped. The dropped samples lead to distortion in the analog reconstruction. We refer to this as the "missing pixel" problem. Under certain conditions, it may be possible to compensate for the dropped sample by pre-processing the digital signal, thereby reducing the analog reconstruction error. We develop three such compensation strategies in this thesis. The first strategy uses constrained minimization to calculate the optimal finite-length compensation signal. We develop a closed-form solution using the method of Lagrange multipliers. Next, we develop an approximation to the optimal solution using discrete prolate spheroidal sequences. We show that the optimal solution is a linear combination of the discrete prolates. The last compensation technique we develop is an iterative solution in class of projection-onto-convex-sets. We develop the algorithm and prove that it converges to the optimal solution found using constrained minimization. Each of the three strategies are analyzed and results from numerical simulations are presented.</Abstract>
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