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The Boolean derivative of the function to one of the arguments is a (k-1)-ary function that is true when the output of the function is sensitive to the chosen input variable; it is the XOR of the two corresponding cofactors.
Boolean values still behave as integers, can be stored in integer variables, and used anywhere integers would be valid, including in indexing, arithmetic, parsing, and formatting. This approach ( Boolean values are just integers ) has been retained in all later versions of C. Note, that this does not mean that any integer value can be stored in ...
Mathematical biology draws on discrete mathematics, topology (also useful for computational modeling), Bayesian statistics, linear algebra and Boolean algebra. [ 14 ] These mathematical approaches have enabled the creation of databases and other methods for storing, retrieving, and analyzing biological data, a field known as bioinformatics .
Boolean network, a certain network consisting of a set of Boolean variables whose state is determined by other variables in the network; Boolean processor, a 1-bit variable computing unit; Boolean ring, a mathematical ring for which x 2 = x for every element x; Boolean satisfiability problem, the problem of determining if there exists an ...
In statistics, the phi coefficient (or mean square contingency coefficient and denoted by φ or r φ) is a measure of association for two binary variables.. In machine learning, it is known as the Matthews correlation coefficient (MCC) and used as a measure of the quality of binary (two-class) classifications, introduced by biochemist Brian W. Matthews in 1975.
Usually, the dynamics of the system is taken as a discrete time series where the state of the entire network at time t+1 is determined by evaluating each variable's function on the state of the network at time t. This may be done synchronously or asynchronously. [1] Boolean networks have been used in biology to model regulatory networks.
In addition, the derivatives of a bent function are balanced Boolean functions, so for any change in the input variables there is a 50 percent chance that the output value will change. The maximal nonlinearity means approximating a bent function by an affine (linear) function is hard, a useful property in the defence against linear cryptanalysis.
The initial object in the category of bounded lattices is a Boolean domain. In computer science, a Boolean variable is a variable that takes values in some Boolean domain. Some programming languages feature reserved words or symbols for the elements of the Boolean domain, for example false and true.