Compression Technology
Lecture 2: Greedy Algorithms II Shang-Hua Teng Optimization Problems A problem that may have many feasible solutions. Each solution has a value In maximization.
Chapter 6 Entropy and Shannon’s First Theorem. Information Existence: I(p) = log_( 1 / p ) units of information: in base 2 = a bit in basee = a nat in.
Lecture 6: Greedy Algorithms I Shang-Hua Teng. Optimization Problems A problem that may have many feasible solutions. Each solution has a value In maximization.
INFORMATION THEORY
Group No 5 1.Muhammad Talha Islam 2.Karim Akhter 3.Muhammad Arif 4.Muhammad Umer Khalid.
Compression. Compression ratio: how much is the size reduced? Symmetric/asymmetric: time difference to compress, decompress? Lossless; lossy: any.
2IS80 Fundamentals of Informatics Quartile 2, 2015–2016 Lecture 10: Information, Errors Lecturer: Tom Verhoeff.
Lossless Compression(2)
Group No 5
