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  2. Heaviside step function - Wikipedia

    en.wikipedia.org/wiki/Heaviside_step_function

    The Heaviside step function, or the unit step function, usually denoted by H or θ (but sometimes u, 1 or 饾煓), 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.

  3. Analog signal processing - Wikipedia

    en.wikipedia.org/wiki/Analog_signal_processing

    By calculating the convolution, we determine how much a reversed function g must be shifted along the x-axis to become identical to function f. The convolution function essentially reverses and slides function g along the axis, and calculates the integral of their (f and the reversed and shifted g) product for each possible amount of sliding.

  4. Convolution - Wikipedia

    en.wikipedia.org/wiki/Convolution

    If f is a Schwartz function, then τ x f is the convolution with a translated Dirac delta function τ x f = f ∗ τ x δ. So translation invariance of the convolution of Schwartz functions is a consequence of the associativity of convolution. Furthermore, under certain conditions, convolution is the most general translation invariant operation.

  5. Step response - Wikipedia

    en.wikipedia.org/wiki/Step_response

    The step response of a system in a given initial state consists of the time evolution of its outputs when its control inputs are Heaviside step functions. In electronic engineering and control theory , step response is the time behaviour of the outputs of a general system when its inputs change from zero to one in a very short time.

  6. Multidimensional discrete convolution - Wikipedia

    en.wikipedia.org/wiki/Multidimensional_discrete...

    In signal processing, multidimensional discrete convolution refers to the mathematical operation between two functions f and g on an n-dimensional lattice that produces a third function, also of n-dimensions. Multidimensional discrete convolution is the discrete analog of the multidimensional convolution of functions on Euclidean space.

  7. Fundamental solution - Wikipedia

    en.wikipedia.org/wiki/Fundamental_solution

    Denote the convolution of functions F and g as F ∗ g. Say we are trying to find the solution of Lf = g(x). We want to prove that F ∗ g is a solution of the previous equation, i.e. we want to prove that L(F ∗ g) = g.

  8. Step function - Wikipedia

    en.wikipedia.org/wiki/Step_function

    The product of a step function with a number is also a step function. As such, the step functions form an algebra over the real numbers. A step function takes only a finite number of values. If the intervals , for =,, …, in the above definition of the step function are disjoint and their union is the real line, then () = for all .

  9. Indicator function - Wikipedia

    en.wikipedia.org/wiki/Indicator_function

    What appears to the modern reader as the representing function's logical inversion, i.e. the representing function is 0 when the function R is "true" or satisfied", plays a useful role in Kleene's definition of the logical functions OR, AND, and IMPLY, [2]: 228 the bounded-[2]: 228 and unbounded-[2]: 279 ff mu operators and the CASE function.

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