Variable-length quantity These are non-universal ones: Unary coding, which is used in Elias codes Rice coding, which is used in the FLAC audio codec and which has unary coding as a special case Golomb coding, which has Rice coding and unary coding as special cases. Their nonuniversality can be observed by noticing that, if any of these are used to code the Gauss–Kuzmin distribution or the Zeta distribution with parameter s=2, expected codeword length is infinite. For example, using unary coding on the Zeta distribution yields an expected length of On the other hand, using the universal Elias gamma coding for the Gauss–Kuzmin distribution results in an expected codeword length (about 3.51 bits) near entropy (about 3.43 bits)- Академия Google. Relationship to practical compression Huffman coding and arithmetic coding (when they can be used) give at least as good, and often better compression than any universal code. However, universal codes are useful when Huffman coding cannot be used — for example, when one does not know the exact probability of each message, but only knows the rankings of their probabilities. Universal codes are also useful when Huffman codes are inconvenient. For example, when the transmitter but not the receiver knows the probabilities of the messages, Huffman coding requires an overhead of transmitting those probabilities to the receiver. Using a universal code does not have that overhead. Each universal code, like each other self-delimiting (prefix) binary code, has its own "implied probability distribution" given by where is the length of the ith codeword and P(i) is the corresponding symbol's probability. If the actual message probabilities are Q(i) and Kullback–Leibler divergence is minimized by the code with , then the optimal Huffman code for that set of messages will be equivalent to that code. Likewise, how close a code is to optimal can be measured by this divergence. Since universal codes are simpler and faster to encode and decode than Huffman codes (which is, in turn, simpler and faster than arithmetic encoding), the universal code would be preferable in cases where is sufficiently small. Lossless Data Compression Program: Hybrid LZ77 RLE For any geometric distribution (an exponential distribution on integers), a Golomb code is optimal. With universal codes, the implicit distribution is approximately a power law such as (more precisely, a Zipf distribution). For the Fibonacci code, the implicit distribution is approximately , with where is the golden ratio. For the ternary