Thomas A. Baran (Massachusetts Institute of Technology), “Conservation in signal processing systems” (2012)

You are here

Inside Signal Processing Newsletter Home Page

Top Reasons to Join SPS Today!

1. IEEE Signal Processing Magazine
2. Signal Processing Digital Library*
3. Inside Signal Processing Newsletter
4. SPS Resource Center
5. Career advancement & recognition
6. Discounts on conferences and publications
7. Professional networking
8. Communities for students, young professionals, and women
9. Volunteer opportunities
10. Coming soon! PDH/CEU credits
Click here to learn more.

10 years of news and resources for members of the IEEE Signal Processing Society

Thomas A. Baran (Massachusetts Institute of Technology), “Conservation in signal processing systems” (2012)

Thomas A. Baran (Massachusetts Institute of Technology), “Conservation in signal processing systems” (2012), Advisor: Prof. Alan V. Oppenheim

Conservation principles have played a key role in the development and analysis of many existing engineering systems and algorithms. In electrical network theory for example, many of the useful theorems regarding the stability, robustness, and variational properties of circuits can be derived in terms of Tellegen's theorem, which states that a wide range of quantities, including power, are conserved. Conservation principles also lay the groundwork for a number of results related to control theory, algorithms for optimization, and efficient filter implementations, suggesting potential opportunity in developing a cohesive signal processing framework within which to view these principles. This thesis makes progress toward that goal, providing a unified treatment of a class of conservation principles that occur in signal processing systems. The main contributions in the thesis can be broadly categorized as pertaining to a mathematical formulation of a class of conservation principles, the synthesis and identification of these principles in signal processing systems, a variational interpretation of these principles, and the use of these principles in designing and gaining insight into various algorithms. In illustrating the use of the framework, examples related to linear and nonlinear signal-flow graph analysis, robust filter architectures, and algorithms for distributed control are provided.

For details, please view the full thesis here.

SPS on Twitter

  • now accepting submissions for special sessions, tutorials, and papers! The conference is set for June 2…
  • DEADLINE EXTENDED: The IEEE Journal of Selected Topics in Signal Processing is now accepting papers for a Special I…
  • NEW WEBINAR: Join us on Friday, 14 August at 11:00 AM ET for the 2021 SPS Membership Preview! Society leadership wi…
  • CALL FOR PAPERS: The 2020 IEEE Workshop on Spoken Language Technology is now accepting papers for its January 2021…
  • CALL FOR PAPERS: The 2020 IEEE International Workshop on Information Forensics and Security is now accepting submis…

SPS Videos

Signal Processing in Home Assistants


Multimedia Forensics

Careers in Signal Processing             


Under the Radar