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BER: variable-length big-endian binary representation (up to 2 2 1024 bits); PER Unaligned: a fixed number of bits if the integer type has a finite range; a variable number of bits otherwise; PER Aligned: a fixed number of bits if the integer type has a finite range and the size of the range is less than 65536; a variable number of octets ...
Suppose we want to encode the message "AABA<EOM>", where <EOM> is the end-of-message symbol. For this example it is assumed that the decoder knows that we intend to encode exactly five symbols in the base 10 number system (allowing for 10 5 different combinations of symbols with the range [0, 100000)) using the probability distribution {A: .60; B: .20; <EOM>: .20}.
UTF-32 (32-bit Unicode Transformation Format), sometimes called UCS-4, is a fixed-length encoding used to encode Unicode code points that uses exactly 32 bits (four bytes) per code point (but a number of leading bits must be zero as there are far fewer than 2 32 Unicode code points, needing actually only 21 bits). [1]
The type and length are fixed in size (typically 1–4 bytes), and the value field is of variable size. These fields are used as follows: Type A binary code, often simply alphanumeric, which indicates the kind of field that this part of the message represents; Length The size of the value field (typically in bytes); Value
The ASCII text-encoding standard uses 7 bits to encode characters. With this it is possible to encode 128 (i.e. 2 7) unique values (0–127) to represent the alphabetic, numeric, and punctuation characters commonly used in English, plus a selection of Control characters which do not represent printable characters.
Type 4 has a count field encoding the number of following items, followed by that many items. The items need not all be the same type; some programming languages call this a "tuple" rather than an "array". Alternatively, an indefinite-length encoding with a short count of 31 may be used. This continues until a "break" marker byte of 255.
Byte pair encoding [1] [2] (also known as BPE, or digram coding) [3] is an algorithm, first described in 1994 by Philip Gage, for encoding strings of text into smaller strings by creating and using a translation table. [4] A slightly-modified version of the algorithm is used in large language model tokenizers.
To convolutionally encode data, start with k memory registers, each holding one input bit.Unless otherwise specified, all memory registers start with a value of 0. The encoder has n modulo-2 adders (a modulo 2 adder can be implemented with a single Boolean XOR gate, where the logic is: 0+0 = 0, 0+1 = 1, 1+0 = 1, 1+1 = 0), and n generator polynomials — one for each adder (see figure below).