# Jacob Ziv

Jacob Ziv (Hebrew יעקב זיו, also Yaakov Ziv; born November 27, 1931 in Tiberias, Palestine ) is an Israeli electrical engineer and has made significant fundamental research in the field of information theory. Along with Abraham Lempel, he developed the LZ77 and LZ78 the algorithm, later published on the basis of Terry Welch LZW algorithm.

Ziv first studied electrical engineering at the Technion (Israel Institute of Technology) in Haifa and later at the Massachusetts Institute of Technology (MIT ), where he also received his doctorate in 1962.

He worked for the Israeli Ministry of Defense and for the Bell Laboratories.

In 1970 he became a professor at the Technion. Since 1981 he is member of the Israel Academy of Sciences and was its president from 1995 to 2004.

In 1997 he received the Paris Kanellakis Award and the 1997 Claude E. Shannon Award.

## Publications (selection)

- Lempel, A. & Ziv, J., On the complexity of finite sequences, 1976, IEEE Trans Inf Theory
- Lempel, A. & Ziv, J., A universal algorithm for sequential data compression, 1977, IEEE Trans Inf Theory
- Ziv, J. and Lempel, A., Compression of individual sequences via variable - rate coding, 1978, IEEE Trans Inf Theory
- Ziv, J., The Impact of Data Processing Techniques on Communications, 1983,
- Lempel, A. & Ziv, J., Compression of two dimensional data, 1986, IEEE Trans IT
- Ziv, J., On classification with empirically -observed statistics and universal data compression, 1988, IEEE Trans IT
- Merhav, N. & Ziv, J., On universally efficient estimation of the first order autoregressive parameters and universal data compression, 1990, IEEE Trans Inform Theory
- Wyner, A. & Ziv, J., Some asymptotic properties of the entropy of a stationary ergodic data source with applications to data compression, 1989, IEEE Trans Inform Theory
- Wyner, A. & Ziv, J., Lempel Ziv algorithm The sliding window is asymptotically optimal, 1994, Proc IEEE
- Ziv, A., Converting approximate error bounds into exact ones, 1995, Math Comp
- Ziv, J., variable to fixed length codes are better than fixed to variable length codes for Markov sources, 1990, IEEE Trans Inform Theory