In computing, bit numbering is the convention used to identify the bit positions in a binary number.
150dec | LSb | |||||||
Bit Content | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 |
In computing, the least significant bit (LSb) is the bit position in a binary integer representing the binary 1s place of the integer. Similarly, the most significant bit (MSb) represents the highest-order place of the binary integer. The LSb is sometimes referred to as the low-order bit or right-most bit, due to the convention in positional notation of writing less significant digits further to the right. The MSb is similarly referred to as the high-order bit or left-most bit. In both cases, the LSb and MSb correlate directly to the least significant digit and most significant digit of a decimal integer.
Bit indexing correlates to the positional notation of the value in base 2. For this reason, bit index is not affected by how the value is stored on the device, such as the value's byte order. Rather, it is a property of the numeric value in binary itself. This is often utilized in programming via bit shifting: A value of 1 <<n
corresponds to the nth bit of a binary integer (with a value of 2n
).
In digital steganography, sensitive messages may be concealed by manipulating and storing information in the least significant bits of an image or a sound file. The user may later recover this information by extracting the least significant bits of the manipulated pixels to recover the original message. This allows the storage or transfer of digital information to remain concealed.
A diagram showing how manipulating the least significant bits of a color can have a very subtle and generally unnoticeable effect on the color. In this diagram, green is represented by its RGB value, both in decimal and in binary. The red box surrounding the last two bits illustrates the least significant bits changed in the binary representation.
This table illustrates an example of decimal value of 149 and the location of LSb. In this particular example, the position of unit value (decimal 1 or 0) is located in bit position 0 (n = 0). MSb stands for most significant bit, while LSb stands for least significant bit.
149dec in LSb0 | LSb | |||||||
Bit Weight | 128 | 64 | 32 | 16 | 8 | 4 | 2 | 1 |
Bit Content | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 |
This table illustrates an example of an 8 bit signed decimal value using the two's complement method. The MSb most significant bit has a negative weight in signed integers, in this case -27 = -128. The other bits have positive weights. The lsb (least significant bit) has weight 20=1. The signed value is in this case -128+2 = -126.
-126dec in LSb0 | LSb | |||||||
Bit Weight | -128 | 64 | 32 | 16 | 8 | 4 | 2 | 1 |
Bit Content | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
The expressions most significant bit first and least significant bit at last are indications on the ordering of the sequence of the bits in the bytes sent over a wire in a serial transmission protocol or in a stream (e.g. an audio stream).
Most significant bit first means that the most significant bit will arrive first: hence e.g. the hexadecimal number 0x12
, 00010010
in binary representation, will arrive as the sequence 0 0 0 1 0 0 1 0
.
Least significant bit first means that the least significant bit will arrive first: hence e.g. the same hexadecimal number 0x12
, again 00010010
in binary representation, will arrive as the (reversed) sequence 0 1 0 0 1 0 0 0
.
150dec in LSb0 | LSb | |||||||
Bit Number | 0 | |||||||
Bit Weight | 128 | 64 | 32 | 16 | 8 | 4 | 2 | 1 |
Bit Content | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 |
When the bit numbering starts at zero for the least significant bit (LSb) the numbering scheme is called LSb 0. [1] This bit numbering method has the advantage that for any unsigned number the value of the number can be calculated by using exponentiation with the bit number and a base of 2. [2] The value of an unsigned binary integer is therefore
where bi denotes the value of the bit with number i, and N denotes the number of bits in total.
150dev in MSb0 | LSb | |||||||
Bit Number | 7 | |||||||
Bit Weight | 128 | 64 | 32 | 16 | 8 | 4 | 2 | 1 |
Bit Content | 1 | 0 | 0 | 1 | 0 | 1 | 1 | 0 |
When the bit numbering starts at zero for the most significant bit (MSb) the numbering scheme is called MSb 0.
The value of an unsigned binary integer is therefore
LSb of a number can be calculated with time complexity of with formula , where means bitwise operation AND and means bitwise operation NOT on.
For MSb 1 numbering, the value of an unsigned binary integer is
PL/I numbers BIT strings starting with 1 for the leftmost bit.
The Fortran BTEST function uses LSb 0 numbering.
In computing, floating-point arithmetic (FP) is arithmetic on subsets of real numbers formed by a signed sequence of a fixed number of digits in some base, called a significand, scaled by an integer exponent of that base. Numbers of this form are called floating-point numbers.
Hexadecimal is a positional numeral system that represents numbers using a radix (base) of sixteen. Unlike the decimal system representing numbers using ten symbols, hexadecimal uses sixteen distinct symbols, most often the symbols "0"–"9" to represent values 0 to 9 and "A"–"F" to represent values from ten to fifteen.
In computer science, an integer is a datum of integral data type, a data type that represents some range of mathematical integers. Integral data types may be of different sizes and may or may not be allowed to contain negative values. Integers are commonly represented in a computer as a group of binary digits (bits). The size of the grouping varies so the set of integer sizes available varies between different types of computers. Computer hardware nearly always provides a way to represent a processor register or memory address as an integer.
A numeral system is a writing system for expressing numbers; that is, a mathematical notation for representing numbers of a given set, using digits or other symbols in a consistent manner.
Octal is a numeral system with eight as the base.
A computer number format is the internal representation of numeric values in digital device hardware and software, such as in programmable computers and calculators. Numerical values are stored as groupings of bits, such as bytes and words. The encoding between numerical values and bit patterns is chosen for convenience of the operation of the computer; the encoding used by the computer's instruction set generally requires conversion for external use, such as for printing and display. Different types of processors may have different internal representations of numerical values and different conventions are used for integer and real numbers. Most calculations are carried out with number formats that fit into a processor register, but some software systems allow representation of arbitrarily large numbers using multiple words of memory.
Double-precision floating-point format is a floating-point number format, usually occupying 64 bits in computer memory; it represents a wide range of numeric values by using a floating radix point.
A binary number is a number expressed in the base-2 numeral system or binary numeral system, a method for representing numbers that uses only two symbols for the natural numbers: typically "0" (zero) and "1" (one). A binary number may also refer to a rational number that has a finite representation in the binary numeral system, that is, the quotient of an integer by a power of two.
In computer programming, a bitwise operation operates on a bit string, a bit array or a binary numeral at the level of its individual bits. It is a fast and simple action, basic to the higher-level arithmetic operations and directly supported by the processor. Most bitwise operations are presented as two-operand instructions where the result replaces one of the input operands.
Two's complement is the most common method of representing signed integers on computers, and more generally, fixed point binary values. Two's complement uses the binary digit with the greatest value as the sign to indicate whether the binary number is positive or negative; when the most significant bit is 1 the number is signed as negative and when the most significant bit is 0 the number is signed as positive. As a result, non-negative numbers are represented as themselves: 6 is 0110, zero is 0000, and -6 is 1010. Note that while the number of binary bits is fixed throughout a computation it is otherwise arbitrary.
A power of two is a number of the form 2n where n is an integer, that is, the result of exponentiation with number two as the base and integer n as the exponent.
Positional notation, also known as place-value notation, positional numeral system, or simply place value, usually denotes the extension to any base of the Hindu–Arabic numeral system. More generally, a positional system is a numeral system in which the contribution of a digit to the value of a number is the value of the digit multiplied by a factor determined by the position of the digit. In early numeral systems, such as Roman numerals, a digit has only one value: I means one, X means ten and C a hundred. In modern positional systems, such as the decimal system, the position of the digit means that its value must be multiplied by some value: in 555, the three identical symbols represent five hundreds, five tens, and five units, respectively, due to their different positions in the digit string.
An organizationally unique identifier (OUI) is a 24-bit number that uniquely identifies a vendor, manufacturer, or other organization.
In computer science, a logical shift is a bitwise operation that shifts all the bits of its operand. The two base variants are the logical left shift and the logical right shift. This is further modulated by the number of bit positions a given value shall be shifted, such as shift left by 1 or shift right by n. Unlike an arithmetic shift, a logical shift does not preserve a number's sign bit or distinguish a number's exponent from its significand (mantissa); every bit in the operand is simply moved a given number of bit positions, and the vacant bit-positions are filled, usually with zeros, and possibly ones.
Methods of computing square roots are algorithms for approximating the non-negative square root of a positive real number . Since all square roots of natural numbers, other than of perfect squares, are irrational, square roots can usually only be computed to some finite precision: these methods typically construct a series of increasingly accurate approximations.
Non-standard positional numeral systems here designates numeral systems that may loosely be described as positional systems, but that do not entirely comply with the following description of standard positional systems:
A negative base may be used to construct a non-standard positional numeral system. Like other place-value systems, each position holds multiples of the appropriate power of the system's base; but that base is negative—that is to say, the base b is equal to −r for some natural number r.
Single-precision floating-point format is a computer number format, usually occupying 32 bits in computer memory; it represents a wide dynamic range of numeric values by using a floating radix point.
LEB128 or Little Endian Base 128 is a variable-length code compression used to store arbitrarily large integers in a small number of bytes. LEB128 is used in the DWARF debug file format and the WebAssembly binary encoding for all integer literals.
The skew binary number system is a non-standard positional numeral system in which the nth digit contributes a value of times the digit instead of times as they do in binary. Each digit has a value of 0, 1, or 2. A number can have many skew binary representations. For example, a decimal number 15 can be written as 1000, 201 and 122. Each number can be written uniquely in skew binary canonical form where there is only at most one instance of the digit 2, which must be the least significant nonzero digit. In this case 15 is written canonically as 1000.