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Named after Claude Shannon, the source coding theorem shows that, in the limit, as the length of a stream of independent and identically-distributed random variable (i.i.d.) data tends to infinity, it is impossible to compress such data such that the code rate (average number of bits per symbol) is less than the Shannon entropy of the source ...
code which is executed but has no external effect (e.g., does not change the output produced by a program; known as dead code). A NOP instruction might be considered to be redundant code that has been explicitly inserted to pad out the instruction stream or introduce a time delay, for example to create a timing loop by "wasting time".
The method was the first of its type, the technique was used to prove Shannon's noiseless coding theorem in his 1948 article "A Mathematical Theory of Communication", [1] and is therefore a centerpiece of the information age.
"Don't repeat yourself" (DRY), also known as "duplication is evil", is a principle of software development aimed at reducing repetition of information which is likely to change, replacing it with abstractions that are less likely to change, or using data normalization which avoids redundancy in the first place.
The code-rate is hence a real number. A low code-rate close to zero implies a strong code that uses many redundant bits to achieve a good performance, while a large code-rate close to 1 implies a weak code. The redundant bits that protect the information have to be transferred using the same communication resources that they are trying to protect.
In computer science and information theory, a Huffman code is a particular type of optimal prefix code that is commonly used for lossless data compression.The process of finding or using such a code is Huffman coding, an algorithm developed by David A. Huffman while he was a Sc.D. student at MIT, and published in the 1952 paper "A Method for the Construction of Minimum-Redundancy Codes".
With this division, A and B will each have a code that starts with a 0 bit, and the C, D, and E codes will all start with a 1, as shown in Figure b. Subsequently, the left half of the tree gets a new division between A and B, which puts A on a leaf with code 00 and B on a leaf with code 01. After four division procedures, a tree of codes results.
theorem and_swap (p q : Prop) : p ∧ q → q ∧ p := by intro h -- assume p ∧ q with proof h, the goal is q ∧ p apply And.intro -- the goal is split into two subgoals, one is q and the other is p · exact h.right -- the first subgoal is exactly the right part of h : p ∧ q · exact h.left -- the second subgoal is exactly the left part of ...