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The Burrows–Wheeler transform (BWT, also called block-sorting compression) rearranges a character string into runs of similar characters. This is useful for compression, since it tends to be easy to compress a string that has runs of repeated characters by techniques such as move-to-front transform and run-length encoding.
The codewords in a linear block code are blocks of symbols that are encoded using more symbols than the original value to be sent. [2] A linear code of length n transmits blocks containing n symbols. For example, the [7,4,3] Hamming code is a linear binary code which represents 4-bit messages using 7-bit codewords. Two distinct codewords differ ...
Schematic structure of an autoencoder with 3 fully connected hidden layers. The code (z, or h for reference in the text) is the most internal layer. Autoencoders are often trained with a single-layer encoder and a single-layer decoder, but using many-layered (deep) encoders and decoders offers many advantages. [2]
As there are an odd number of digits in the middle of the string, the odd one must use a different code set, but it makes no difference whether this is the first or last; 16 symbols are required in either case: [Start B] 0 9 8 x 1 [Code C] 23 45 67 [Code B] y 2 3 [checksum] [Stop], or [Start B] 0 9 8 x [Code C] 12 34 56 [Code B] 7 y 2 3 ...
[10] (on 3 Clause BSD License for Linux/Windows/macOS, and in Development) VVenC & VVdeC – An open-source encoder and decoder released by Fraunhofer HHI based on the Versatile Video Coding (VVC/H.266) standard available on GitHub. XEVE (the eXtra-fast Essential Video Encoder) MPEG-5 Part 1: Essential Video Coding
Byte Strings are encoded as <length>:<contents>. The length is the number of bytes in the string, encoded in base 10. A colon (:) separates the length and the contents. The contents are the exact number of bytes specified by the length. Examples: An empty string is encoded as 0:. The string "bencode" is encoded as 7:bencode.
T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI introduced in 2019. [1] [2] Like the original Transformer model, [3] T5 models are encoder-decoder Transformers, where the encoder processes the input text, and the decoder generates the output text.
This LDPC code fragment represents a three-bit message encoded as six bits. Redundancy is used, here, to increase the chance of recovering from channel errors. This is a (6, 3) linear code, with n = 6 and k = 3. Again ignoring lines going out of the picture, the parity-check matrix representing this graph fragment is