Eric Lehman. Approximation Algorithms for Grammar-based Data Compression. PhD thesis, Massachusetts Institute of Technology, In preparation.  Home/Search   Document Details and Download   Summary   Related Articles

....exploit the grammar model. In particular, a good grammar compressor exhibits a small ratio between the size of the grammar it produces and the smallest grammar for that given input. Whereas this work focuses on just analyzing the Sequential family of algorithms, Eric Lehman s forthcoming thesis [7] contains a thorough treatment of this area. Chapter 2 introduces our notation and grammar model, much of which is borrowed from Lehman s thesis [7] The chapter ends with a few general lemmas used in subsequent chapters. Chapter 3 shows that no polynomial time algorithm can gener11 ate a grammar ....

....grammar for that given input. Whereas this work focuses on just analyzing the Sequential family of algorithms, Eric Lehman s forthcoming thesis [7] contains a thorough treatment of this area. Chapter 2 introduces our notation and grammar model, much of which is borrowed from Lehman s thesis [7]. The chapter ends with a few general lemmas used in subsequent chapters. Chapter 3 shows that no polynomial time algorithm can gener11 ate a grammar to within a factor of 5671 5670 of the minimal grammar unless P = NP . In Chapter 4, we describe the Sequitur and Sequential algorithms and prove ....

[Article contains additional citation context not shown here]

Eric Lehman. Approximation Algorithms for Grammar-based Data Compression. PhD thesis, Massachusetts Institute of Technology, In preparation.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC