The most common unit of information is the bit, based on the binary logarithm.

The binary logarithm also frequently appears in the analysis of algorithms.

Furthermore, we want and to be natural numbers, where denote the binary logarithm.

The key size is the binary logarithm of the number of possible keys.

For a general positive real number, the binary logarithm may be computed in two parts:

This definition affords a first approximation of the binary logarithm.

For integer domain and range, the binary logarithm can be computed rounding up or down.

These two forms of integer binary logarithm are related by this formula:

The article find first set contains more information on algorithms, architecture support, and applications for the integer binary logarithm.

In mathematics, the binary logarithm (log n) is the logarithm to the base 2.

The integer binary logarithm can be interpreted as the zero-based index of the most significant 1 bit in the input.

See Binary logarithm for details.

See binary logarithm.

In Hick's experiment, the reaction time is found to be a function of the binary logarithm of the number of available choices (n).

The binary logarithm is often used in computer science and information theory because it is closely connected to the binary numeral system.

The binary logarithm is the inverse function of and makes the multiplied terms in the floating point numbers x and y reduce to addition.

The dynamic range can be measured in "stops", which is the binary logarithm of the ratio of highest and lowest distinguishable exposures.

A frequency ratio expressed in octaves is the base-2 logarithm (binary logarithm) of the ratio:

As established above, the minimum necessary dimensionality of the USM state space is set by the binary logarithm of the number of unique units.

For instance, the binary logarithm is just the natural logarithm divided by ln(2), the natural logarithm of 2.

The complementary operation that finds the index or position of the most significant set bit is log base 2, so called because it computes the binary logarithm .

Here o(n) is the multiplicative order of n modulo r, log is the binary logarithm, and is Euler's totient function of r.

German linguists define the 'häufigkeitsklasse' (frequency class) N of an item in the list using the binary logarithm of the ratio between its frequency and the frequency of the most frequent item.

Assuming no drawn games, determining a clear winner (and, incidentally, a clear loser) would require the same number of rounds as a knockout tournament, that is the binary logarithm of the number of players rounded up.

The nondeterministic communication complexity is the binary logarithm of the rectangle covering number of the matrix: the minimum number of combinatorial 1-rectangles required to cover all 1-entries of the matrix, without covering any 0-entries.