Rectangular function

Summary

Rectangular function

The rectangular function (also known as the rectangle function, rect function, Pi function, gate function, unit pulse, or the normalized boxcar function) is defined as[1]

Alternative definitions of the function define to be 0,[2] 1,[3][4] or undefined. However, this mid-point property, as defined here, is required (see e.g. Theorem 2, p. 241 in [5]) to be consistent with Fourier transform theory, otherwise the rect function is not the Fourier transform of sinc function.

History

The rect function has been introduced by Woodward[6] in [7] as an ideal cutout operator, together with the sinc function[8][9] as an ideal interpolation operator, and their counter operations which are sampling (comb operator) and replicating (rep operator), respectively.

Relation to the boxcar function

The rectangular function is a special case of the more general boxcar function:

where is the Heaviside function; the function is centered at and has duration , from to .

Fourier transform of the rectangular function

The unitary Fourier transforms of the rectangular function are[1]

using ordinary frequency f, and

Plot of normalised sinc(x) function (i.e. sinc(πx)) with its spectral frequency components.

using angular frequency ω, where is the unnormalized form of the sinc function.

Note that as long as the definition of the pulse function is only motivated by its behavior in the time-domain experience, there is no reason to believe that the oscillatory interpretation (i.e. the Fourier transform function) should be intuitive, or directly understood by humans. However, some aspects of the theoretical result may be understood intuitively, as finiteness in time domain corresponds to an infinite frequency response. (Vice versa, a finite Fourier transform will correspond to infinite time domain response.)

Relation to the triangular function

We can define the triangular function as the convolution of two rectangular functions:

Use in probability

Viewing the rectangular function as a probability density function, it is a special case of the continuous uniform distribution with . The characteristic function is

and its moment-generating function is

where is the hyperbolic sine function.

Rational approximation

The pulse function may also be expressed as a limit of a rational function:

Demonstration of validity

First, we consider the case where . Notice that the term is always positive for integer . However, and hence approaches zero for large .

It follows that:

Second, we consider the case where . Notice that the term is always positive for integer . However, and hence grows very large for large .

It follows that:

Third, we consider the case where . We may simply substitute in our equation:

We see that it satisfies the definition of the pulse function.

See also

References

  1. ^ a b Weisstein, Eric W. "Rectangle Function". MathWorld.
  2. ^ Wang, Ruye (2012). Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis. Cambridge University Press. pp. 135–136. ISBN 9780521516884.
  3. ^ Tang, K. T. (2007). Mathematical Methods for Engineers and Scientists: Fourier analysis, partial differential equations and variational models. Springer. p. 85. ISBN 9783540446958.
  4. ^ Kumar, A. Anand (2011). Signals and Systems. PHI Learning Pvt. Ltd. pp. 258–260. ISBN 9788120343108.
  5. ^ Kaplan, Wilfred (1962). Operational Methods for Linear Systems. Addison-Wesley Pub. Co.
  6. ^ Klauder, John R (1960). The Theory and Design of Chirp Radars. Bell System Technical Journal. pp. 745–808.
  7. ^ Woodward, Philipp M (1953). Probability and Information Theory, with Applications to Radar. Pergamon Press. p. 29.
  8. ^ Higgins, John Rowland (1996). Sampling Theory in Fourier and Signal Analysis: Foundations. Oxford University Press Inc. p. 4. ISBN 0198596995.
  9. ^ Zayed, Ahmed I (1996). Handbook of Function and Generalized Function Transformations. CRC Press. p. 507. ISBN 9780849380761.