EE Distinguished Lecturer Series: 11/11/10 - Dr. Andrew J. Viterbi

A.A. Markov proposed and developed a statistical concept which suggests that future action should depend only on the current state of the system or process. Exploitation of the statistical properties of Markov processes has produced important results in optimum linear (Wiener) filtering, with principal applications to navigation, tracking, orbit determination and even economics; and in finite-state sequence determination, with applications to
information (Shannon) theory, digital communication, voice and optical character recognition, data recording, search engines, and DNA sequence analysis. Both areas will be discussed and compared, as well as the merits
of any societal implications of the Markov concept.

Category:

Science & Technology

Tags:

• USC
• Lectures
• Seminar
• Viterbi
• Electrical Engineering
• Markov process
• Shannon theory
• Wiener filter