Sinc function

Last updated

In mathematics, physics and engineering, the sinc function, denoted by sinc(x), has two forms, normalized and unnormalized. [1]

Contents

The normalized sinc (blue) and unnormalized sinc function (red) shown on the same scale Si sinc.svg
The normalized sinc (blue) and unnormalized sinc function (red) shown on the same scale
The sinc function as audio, at 2000 Hz (±1.5 seconds around zero).

In mathematics, the historical unnormalized sinc function is defined for x ≠ 0 by

Alternatively, the unnormalized sinc function is often called the sampling function, indicated as Sa(x). [2]

In digital signal processing and information theory, the normalized sinc function is commonly defined for x ≠ 0 by

In either case, the value at x = 0 is defined to be the limiting value

for all real a ≠ 0.

The normalization causes the definite integral of the function over the real numbers to equal 1 (whereas the same integral of the unnormalized sinc function has a value of π). As a further useful property, the zeros of the normalized sinc function are the nonzero integer values of x.

The normalized sinc function is the Fourier transform of the rectangular function with no scaling. It is used in the concept of reconstructing a continuous bandlimited signal from uniformly spaced samples of that signal.

The only difference between the two definitions is in the scaling of the independent variable (the x axis) by a factor of π. In both cases, the value of the function at the removable singularity at zero is understood to be the limit value 1. The sinc function is then analytic everywhere and hence an entire function.

The term sinc /ˈsɪŋk/ was introduced by Philip M. Woodward in his 1952 article "Information theory and inverse probability in telecommunication", in which he said that the function "occurs so often in Fourier analysis and its applications that it does seem to merit some notation of its own", [3] and his 1953 book Probability and Information Theory, with Applications to Radar. [4] [5] The function itself was first mathematically derived in this form by Lord Rayleigh in his expression (Rayleigh's Formula) for the zeroth-order spherical Bessel function of the first kind [6969 G. et al].

Properties

The local maxima and minima (small white dots) of the unnormalized, red sinc function correspond to its intersections with the blue cosine function. Si cos.svg
The local maxima and minima (small white dots) of the unnormalized, red sinc function correspond to its intersections with the blue cosine function.
The real part of complex sinc Re(sinc z) = Re(
.mw-parser-output .sfrac{white-space:nowrap}.mw-parser-output .sfrac.tion,.mw-parser-output .sfrac .tion{display:inline-block;vertical-align:-0.5em;font-size:85%;text-align:center}.mw-parser-output .sfrac .num,.mw-parser-output .sfrac .den{display:block;line-height:1em;margin:0 0.1em}.mw-parser-output .sfrac .den{border-top:1px solid}.mw-parser-output .sr-only{border:0;clip:rect(0,0,0,0);height:1px;margin:-1px;overflow:hidden;padding:0;position:absolute;width:1px}
sin z/z) Sinc re.svg
The real part of complex sinc Re(sinc z) = Re(sin z/z)
The imaginary part of complex sinc Im(sinc z) = Im(
sin z/z) Sinc im.svg
The imaginary part of complex sinc Im(sinc z) = Im(sin z/z)
The absolute value |sinc z| = |
sin z/z| Sinc abs.svg
The absolute value |sinc z| = |sin z/z|

The zero crossings of the unnormalized sinc are at non-zero integer multiples of π, while zero crossings of the normalized sinc occur at non-zero integers.

The local maxima and minima of the unnormalized sinc correspond to its intersections with the cosine function. That is, sin(ξ)/ξ = cos(ξ) for all points ξ where the derivative of sin(x)/x is zero and thus a local extremum is reached. This follows from the derivative of the sinc function:

The first few terms of the infinite series for the x coordinate of the n-th extremum with positive x coordinate are

where

and where odd n lead to a local minimum, and even n to a local maximum. Because of symmetry around the y axis, there exist extrema with x coordinates xn. In addition, there is an absolute maximum at ξ0 = (0, 1).

The normalized sinc function has a simple representation as the infinite product:

and is related to the gamma function Γ(x) through Euler's reflection formula:

Euler discovered [6] that

and because of the product-to-sum identity [7]

the Euler's product can be recast as a sum

The continuous Fourier transform of the normalized sinc (to ordinary frequency) is rect(f):

where the rectangular function is 1 for argument between −1/2 and 1/2, and zero otherwise. This corresponds to the fact that the sinc filter is the ideal (brick-wall, meaning rectangular frequency response) low-pass filter.

This Fourier integral, including the special case

is an improper integral (see Dirichlet integral) and not a convergent Lebesgue integral, as

The normalized sinc function has properties that make it ideal in relationship to interpolation of sampled bandlimited functions:

Other properties of the two sinc functions include:

where Si(x) is the sine integral.
The other is cos(λx)/x, which is not bounded at x = 0, unlike its sinc function counterpart.
where the normalized sinc is meant.

Relationship to the Dirac delta distribution

The normalized sinc function can be used as a nascent delta function , meaning that the following weak limit holds:

This is not an ordinary limit, since the left side does not converge. Rather, it means that

for every Schwartz function, as can be seen from the Fourier inversion theorem. In the above expression, as a → 0, the number of oscillations per unit length of the sinc function approaches infinity. Nevertheless, the expression always oscillates inside an envelope of ±1/πx, regardless of the value of a.

This complicates the informal picture of δ(x) as being zero for all x except at the point x = 0, and illustrates the problem of thinking of the delta function as a function rather than as a distribution. A similar situation is found in the Gibbs phenomenon.

Summation

All sums in this section refer to the unnormalized sinc function.

The sum of sinc(n) over integer n from 1 to equals π − 1/2:

The sum of the squares also equals π − 1/2: [8] [9]

When the signs of the addends alternate and begin with +, the sum equals 1/2:

The alternating sums of the squares and cubes also equal 1/2: [10]

Series expansion

The Taylor series of the (unnormalized) sinc function can be obtained immediately from that of the sine:

which converges for all x.

Higher dimensions

The product of 1-D sinc functions readily provides a multivariate sinc function for the square Cartesian grid (lattice): sincC(x, y) = sinc(x) sinc(y), whose Fourier transform is the indicator function of a square in the frequency space (i.e., the brick wall defined in 2-D space). The sinc function for a non-Cartesian lattice (e.g., hexagonal lattice) is a function whose Fourier transform is the indicator function of the Brillouin zone of that lattice. For example, the sinc function for the hexagonal lattice is a function whose Fourier transform is the indicator function of the unit hexagon in the frequency space. For a non-Cartesian lattice this function can not be obtained by a simple tensor product. However, the explicit formula for the sinc function for the hexagonal, body-centered cubic, face-centered cubic and other higher-dimensional lattices can be explicitly derived [11] using the geometric properties of Brillouin zones and their connection to zonotopes.

For example, a hexagonal lattice can be generated by the (integer) linear span of the vectors

Denoting

one can derive [11] the sinc function for this hexagonal lattice as

This construction can be used to design Lanczos window for general multidimensional lattices. [11]

See also

Related Research Articles

In physics, the cross section is a measure of the probability that a specific process will take place when some kind of radiant excitation intersects a localized phenomenon. For example, the Rutherford cross-section is a measure of probability that an alpha-particle will be deflected by a given angle during a collision with an atomic nucleus. Cross section is typically denoted σ (sigma) and is expressed in units of transverse area. In a way, it can be thought of as the size of the object that the excitation must hit in order for the process to occur, but more exactly, it is a parameter of a stochastic process.

Trigonometric functions Functions of an angle

In mathematics, the trigonometric functions are real functions which relate an angle of a right-angled triangle to ratios of two side lengths. They are widely used in all sciences that are related to geometry, such as navigation, solid mechanics, celestial mechanics, geodesy, and many others. They are among the simplest periodic functions, and as such are also widely used for studying periodic phenomena through Fourier analysis.

Laplaces equation Second order partial differential equation

In mathematics and physics, Laplace's equation is a second-order partial differential equation named after Pierre-Simon Laplace who first studied its properties. This is often written as

In calculus, and more generally in mathematical analysis, integration by parts or partial integration is a process that finds the integral of a product of functions in terms of the integral of the product of their derivative and antiderivative. It is frequently used to transform the antiderivative of a product of functions into an antiderivative for which a solution can be more easily found. The rule can be thought of as an integral version of the product rule of differentiation.

In mechanics and geometry, the 3D rotation group, often denoted SO(3), is the group of all rotations about the origin of three-dimensional Euclidean space under the operation of composition. By definition, a rotation about the origin is a transformation that preserves the origin, Euclidean distance, and orientation. Every non-trivial rotation is determined by its axis of rotation and its angle of rotation. Composing two rotations results in another rotation; every rotation has a unique inverse rotation; and the identity map satisfies the definition of a rotation. Owing to the above properties, the set of all rotations is a group under composition. Rotations are not commutative, making it a nonabelian group. Moreover, the rotation group has a natural structure as a manifold for which the group operations are smoothly differentiable; so it is in fact a Lie group. It is compact and has dimension 3.

Spherical harmonics Special mathematical functions defined on the surface of a sphere

In mathematics and physical science, spherical harmonics are special functions defined on the surface of a sphere. They are often employed in solving partial differential equations in many scientific fields.

In 1851, George Gabriel Stokes derived an expression, now known as Stokes law, for the frictional force – also called drag force – exerted on spherical objects with very small Reynolds numbers in a viscous fluid. Stokes' law is derived by solving the Stokes flow limit for small Reynolds numbers of the Navier–Stokes equations.

In probability and statistics, an exponential family is a parametric set of probability distributions of a certain form, specified below. This special form is chosen for mathematical convenience, based on some useful algebraic properties, as well as for generality, as exponential families are in a sense very natural sets of distributions to consider. The term exponential class is sometimes used in place of "exponential family", or the older term Koopman–Darmois family. The terms "distribution" and "family" are often used loosely: properly, an exponential family is a set of distributions, where the specific distribution varies with the parameter; however, a parametric family of distributions is often referred to as "a distribution", and the set of all exponential families is sometimes loosely referred to as "the" exponential family. They are distinct because they posses a variety of desirable properties, most importantly the existence of a sufficient statistic.

Inverse trigonometric functions

In mathematics, the inverse trigonometric functions are the inverse functions of the trigonometric functions. Specifically, they are the inverses of the sine, cosine, tangent, cotangent, secant, and cosecant functions, and are used to obtain an angle from any of the angle's trigonometric ratios. Inverse trigonometric functions are widely used in engineering, navigation, physics, and geometry.

Clausen function

In mathematics, the Clausen function, introduced by Thomas Clausen (1832), is a transcendental, special function of a single variable. It can variously be expressed in the form of a definite integral, a trigonometric series, and various other special functions. It is intimately connected with the polylogarithm, inverse tangent integral, polygamma function, Riemann zeta function, Dirichlet eta function, and Dirichlet beta function.

Theta function Special functions of several complex variables

In mathematics, theta functions are special functions of several complex variables. They are important in many areas, including the theories of Abelian varieties and moduli spaces, and of quadratic forms. They have also been applied to soliton theory. When generalized to a Grassmann algebra, they also appear in quantum field theory.

Sigma approximation

In mathematics, σ-approximation adjusts a Fourier summation to greatly reduce the Gibbs phenomenon, which would otherwise occur at discontinuities.

In probability and statistics, a circular distribution or polar distribution is a probability distribution of a random variable whose values are angles, usually taken to be in the range [0, 2π). A circular distribution is often a continuous probability distribution, and hence has a probability density, but such distributions can also be discrete, in which case they are called circular lattice distributions. Circular distributions can be used even when the variables concerned are not explicitly angles: the main consideration is that there is not usually any real distinction between events occurring at the lower or upper end of the range, and the division of the range could notionally be made at any point.

In potential theory, the Poisson kernel is an integral kernel, used for solving the two-dimensional Laplace equation, given Dirichlet boundary conditions on the unit disk. The kernel can be understood as the derivative of the Green's function for the Laplace equation. It is named for Siméon Poisson.

Axis–angle representation

In mathematics, the axis–angle representation of a rotation parameterizes a rotation in a three-dimensional Euclidean space by two quantities: a unit vector e indicating the direction of an axis of rotation, and an angle θ describing the magnitude of the rotation about the axis. Only two numbers, not three, are needed to define the direction of a unit vector e rooted at the origin because the magnitude of e is constrained. For example, the elevation and azimuth angles of e suffice to locate it in any particular Cartesian coordinate frame.

In mathematics, vector spherical harmonics (VSH) are an extension of the scalar spherical harmonics for use with vector fields. The components of the VSH are complex-valued functions expressed in the spherical coordinate basis vectors.

In fluid dynamics, the Oseen equations describe the flow of a viscous and incompressible fluid at small Reynolds numbers, as formulated by Carl Wilhelm Oseen in 1910. Oseen flow is an improved description of these flows, as compared to Stokes flow, with the (partial) inclusion of convective acceleration.

In optics, the Fraunhofer diffraction equation is used to model the diffraction of waves when the diffraction pattern is viewed at a long distance from the diffracting object, and also when it is viewed at the focal plane of an imaging lens.

References

  1. Olver, Frank W. J.; Lozier, Daniel M.; Boisvert, Ronald F.; Clark, Charles W., eds. (2010), "Numerical methods", NIST Handbook of Mathematical Functions , Cambridge University Press, ISBN   978-0-521-19225-5, MR   2723248 .
  2. Singh, R. P.; Sapre, S. D. (2008). Communication Systems, 2E (illustrated ed.). Tata McGraw-Hill Education. p. 15. ISBN   978-0-07-063454-1. Extract of page 15
  3. Woodward, P. M.; Davies, I. L. (March 1952). "Information theory and inverse probability in telecommunication" (PDF). Proceedings of the IEE - Part III: Radio and Communication Engineering. 99 (58): 37–44. doi:10.1049/pi-3.1952.0011.
  4. Poynton, Charles A. (2003). Digital video and HDTV . Morgan Kaufmann Publishers. p.  147. ISBN   978-1-55860-792-7.
  5. Woodward, Phillip M. (1953). Probability and information theory, with applications to radar . London: Pergamon Press. p.  29. ISBN   978-0-89006-103-9. OCLC   488749777.
  6. Euler, Leonhard (1735). "On the sums of series of reciprocals". arXiv: math/0506415 .
  7. Luis Ortiz-Gracia; Cornelis W. Oosterlee (2016). "A highly efficient Shannon wavelet inverse Fourier technique for pricing European options". SIAM J. Sci. Comput. 38 (1): B118–B143. doi:10.1137/15M1014164.
  8. "Advanced Problem 6241". American Mathematical Monthly. Washington, DC: Mathematical Association of America. 87 (6): 496–498. June–July 1980. doi:10.1080/00029890.1980.11995075.CS1 maint: date format (link)
  9. Robert Baillie; David Borwein; Jonathan M. Borwein (December 2008). "Surprising Sinc Sums and Integrals". American Mathematical Monthly. 115 (10): 888–901. doi:10.1080/00029890.2008.11920606. hdl: 1959.13/940062 . JSTOR   27642636.
  10. Baillie, Robert (2008). "Fun with Fourier series". arXiv: 0806.0150v2 [math.CA].
  11. 1 2 3 Ye, W.; Entezari, A. (June 2012). "A Geometric Construction of Multivariate Sinc Functions". IEEE Transactions on Image Processing. 21 (6): 2969–2979. Bibcode:2012ITIP...21.2969Y. doi:10.1109/TIP.2011.2162421. PMID   21775264.