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A function. May be unary or n-ary (or always unary for languages without n-ary functions). func1, func2, etc. functions of specific arity. func (with no number) is the same as func1, also known as a projection in many languages. pred Unary function returning a Boolean value. (ML type: 'a -> bool) (C-like type: bool pred < T > (T t)). list The ...
The Heaviside function H(x), which is 0 for negative numbers and 1 for positive numbers, is equivalent to the sign function, up to a shift and scale of range (= (+) /). It is the mathematical concept behind some test signals , such as those used to determine the step response of a dynamical system .
Python does not contain the classical for loop, rather a foreach loop is used to iterate over the output of the built-in range() function which returns an iterable sequence of integers. for i in range ( 1 , 6 ): # gives i values from 1 to 5 inclusive (but not 6) # statements print ( i ) # if we want 6 we must do the following for i in range ( 1 ...
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}.
In the case of an integer, the variable definition is restricted to whole numbers only, and the range will cover every number within its range (including the maximum and minimum). For example, the range of a signed 16-bit integer variable is all the integers from −32,768 to +32,767.
The Heaviside step function, or the unit step function, usually denoted by H or θ (but sometimes u, 1 or 𝟙), is a step function named after Oliver Heaviside, the value of which is zero for negative arguments and one for positive arguments. Different conventions concerning the value H(0) are in use.
Python supports normal floating point numbers, which are created when a dot is used in a literal (e.g. 1.1), when an integer and a floating point number are used in an expression, or as a result of some mathematical operations ("true division" via the / operator, or exponentiation with a negative exponent).
The activation function of a node in an artificial neural network is a function that calculates the output of the node based on its individual inputs and their weights. Nontrivial problems can be solved using only a few nodes if the activation function is nonlinear .