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Sinc function
Special mathematical function defined as sin(x)/x

In mathematics, physics, and engineering, the sinc function, denoted sinc(x), exists in unnormalized and normalized forms. The unnormalized version, also called the sampling function, is defined as sinc(x) = sin(x)/x, while the normalized form common in digital signal processing is sinc(x) = sin(πx)/(πx). Both define sinc(0) by limit as 1, proven via the squeeze theorem. The normalized sinc's integral over all real numbers equals 1 and its zeros are the nonzero integers. It serves as the Fourier transform of the rectangular function and is fundamental in signal reconstruction from samples per the Nyquist–Shannon sampling theorem. Originally studied by Lord Rayleigh and named by Philip M. Woodward, it is an entire function analytic everywhere.

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Properties

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: d d x sinc ⁡ ( x ) = { cos ⁡ ( x ) − sinc ⁡ ( x ) x , x ≠ 0 0 , x = 0 . {\displaystyle {\frac {d}{dx}}\operatorname {sinc} (x)={\begin{cases}{\dfrac {\cos(x)-\operatorname {sinc} (x)}{x}},&x\neq 0\\0,&x=0\end{cases}}.}

The first few terms of the infinite series for the x coordinate of the n-th extremum with positive x coordinate are x n = q − q − 1 − 2 3 q − 3 − 13 15 q − 5 − 146 105 q − 7 − ⋯ , {\displaystyle x_{n}=q-q^{-1}-{\frac {2}{3}}q^{-3}-{\frac {13}{15}}q^{-5}-{\frac {146}{105}}q^{-7}-\cdots ,} where q = ( n + 1 2 ) π , {\displaystyle q=\left(n+{\frac {1}{2}}\right)\pi ,} 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: sin ⁡ ( π x ) π x = ∏ n = 1 ∞ ( 1 − x 2 n 2 ) {\displaystyle {\frac {\sin(\pi x)}{\pi x}}=\prod _{n=1}^{\infty }\left(1-{\frac {x^{2}}{n^{2}}}\right)}

and is related to the gamma function Γ(x) through Euler's reflection formula: sin ⁡ ( π x ) π x = 1 Γ ( 1 + x ) Γ ( 1 − x ) . {\displaystyle {\frac {\sin(\pi x)}{\pi x}}={\frac {1}{\Gamma (1+x)\Gamma (1-x)}}.}

Euler discovered9 that sin ⁡ ( x ) x = ∏ n = 1 ∞ cos ⁡ ( x 2 n ) , {\displaystyle {\frac {\sin(x)}{x}}=\prod _{n=1}^{\infty }\cos \left({\frac {x}{2^{n}}}\right),} and because of the product-to-sum identity10

∏ n = 1 k cos ⁡ ( x 2 n ) = 1 2 k − 1 ∑ n = 1 2 k − 1 cos ⁡ ( n − 1 / 2 2 k − 1 x ) , ∀ k ≥ 1 , {\displaystyle \prod _{n=1}^{k}\cos \left({\frac {x}{2^{n}}}\right)={\frac {1}{2^{k-1}}}\sum _{n=1}^{2^{k-1}}\cos \left({\frac {n-1/2}{2^{k-1}}}x\right),\quad \forall k\geq 1,} Euler's product can be recast as a sum sin ⁡ ( x ) x = lim N → ∞ 1 N ∑ n = 1 N cos ⁡ ( n − 1 / 2 N x ) . {\displaystyle {\frac {\sin(x)}{x}}=\lim _{N\to \infty }{\frac {1}{N}}\sum _{n=1}^{N}\cos \left({\frac {n-1/2}{N}}x\right).}

The continuous Fourier transform of the normalized sinc (to ordinary frequency) is rect(f): ∫ − ∞ ∞ sinc ⁡ ( t ) e − i 2 π f t d t = rect ⁡ ( f ) , {\displaystyle \int _{-\infty }^{\infty }\operatorname {sinc} (t)\,e^{-i2\pi ft}\,dt=\operatorname {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 ∫ − ∞ ∞ sin ⁡ ( π x ) π x d x = rect ⁡ ( 0 ) = 1 {\displaystyle \int _{-\infty }^{\infty }{\frac {\sin(\pi x)}{\pi x}}\,dx=\operatorname {rect} (0)=1} is an improper integral (see Dirichlet integral) and not a convergent Lebesgue integral, as ∫ − ∞ ∞ | sin ⁡ ( π x ) π x | d x = + ∞ . {\displaystyle \int _{-\infty }^{\infty }\left|{\frac {\sin(\pi x)}{\pi x}}\right|\,dx=+\infty .}

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

  • It is an interpolating function, i.e., sinc(0) = 1, and sinc(k) = 0 for nonzero integer k.
  • The functions xk(t) = sinc(tk) (k integer) form an orthonormal basis for bandlimited functions in the function space L2(R), with highest angular frequency ωH = π (that is, highest cycle frequency fH = ⁠1/2⁠).

Other properties of the two sinc functions include:

  • The unnormalized sinc is the zeroth-order spherical Bessel function of the first kind, j0(x). The normalized sinc is j0(πx).
  • where Si(x) is the sine integral, ∫ 0 x sin ⁡ ( θ ) θ d θ = Si ⁡ ( x ) . {\displaystyle \int _{0}^{x}{\frac {\sin(\theta )}{\theta }}\,d\theta =\operatorname {Si} (x).}
  • λ sinc(λx) (not normalized) is one of two linearly independent solutions to the linear ordinary differential equation x d 2 y d x 2 + 2 d y d x + λ 2 x y = 0. {\displaystyle x{\frac {d^{2}y}{dx^{2}}}+2{\frac {dy}{dx}}+\lambda ^{2}xy=0.} The other is ⁠cos(λx)/x⁠, which is not bounded at x = 0, unlike its sinc function counterpart.
  • Using normalized sinc, ∫ − ∞ ∞ sin 2 ⁡ ( θ ) θ 2 d θ = π ⇒ ∫ − ∞ ∞ sinc 2 ⁡ ( x ) d x = 1 , {\displaystyle \int _{-\infty }^{\infty }{\frac {\sin ^{2}(\theta )}{\theta ^{2}}}\,d\theta =\pi \quad \Rightarrow \quad \int _{-\infty }^{\infty }\operatorname {sinc} ^{2}(x)\,dx=1,}
  • ∫ − ∞ ∞ sin ⁡ ( θ ) θ d θ = ∫ − ∞ ∞ ( sin ⁡ ( θ ) θ ) 2 d θ = π . {\displaystyle \int _{-\infty }^{\infty }{\frac {\sin(\theta )}{\theta }}\,d\theta =\int _{-\infty }^{\infty }\left({\frac {\sin(\theta )}{\theta }}\right)^{2}\,d\theta =\pi .}
  • ∫ − ∞ ∞ sin 3 ⁡ ( θ ) θ 3 d θ = 3 π 4 . {\displaystyle \int _{-\infty }^{\infty }{\frac {\sin ^{3}(\theta )}{\theta ^{3}}}\,d\theta ={\frac {3\pi }{4}}.}
  • ∫ − ∞ ∞ sin 4 ⁡ ( θ ) θ 4 d θ = 2 π 3 . {\displaystyle \int _{-\infty }^{\infty }{\frac {\sin ^{4}(\theta )}{\theta ^{4}}}\,d\theta ={\frac {2\pi }{3}}.}
  • The following improper integral involves the (not normalized) sinc function: ∫ 0 ∞ d x x n + 1 = 1 + 2 ∑ k = 1 ∞ ( − 1 ) k + 1 ( k n ) 2 − 1 = 1 sinc ⁡ ( π n ) . {\displaystyle \int _{0}^{\infty }{\frac {dx}{x^{n}+1}}=1+2\sum _{k=1}^{\infty }{\frac {(-1)^{k+1}}{(kn)^{2}-1}}={\frac {1}{\operatorname {sinc} ({\frac {\pi }{n}})}}.}

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:

lim a → 0 sin ⁡ ( π x a ) π x = lim a → 0 1 a sinc ⁡ ( x a ) = δ ( x ) . {\displaystyle \lim _{a\to 0}{\frac {\sin \left({\frac {\pi x}{a}}\right)}{\pi x}}=\lim _{a\to 0}{\frac {1}{a}}\operatorname {sinc} \left({\frac {x}{a}}\right)=\delta (x).}

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

lim a → 0 ∫ − ∞ ∞ 1 a sinc ⁡ ( x a ) φ ( x ) d x = φ ( 0 ) {\displaystyle \lim _{a\to 0}\int _{-\infty }^{\infty }{\frac {1}{a}}\operatorname {sinc} \left({\frac {x}{a}}\right)\varphi (x)\,dx=\varphi (0)}

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.

We can also make an immediate connection with the standard Dirac representation of δ ( x ) {\displaystyle \delta (x)} by writing b = 1 / a {\displaystyle b=1/a} and

lim b → ∞ sin ⁡ ( b π x ) π x = lim b → ∞ 1 2 π ∫ − b π b π e i k x d k = 1 2 π ∫ − ∞ ∞ e i k x d k = δ ( x ) , {\displaystyle \lim _{b\to \infty }{\frac {\sin \left(b\pi x\right)}{\pi x}}=\lim _{b\to \infty }{\frac {1}{2\pi }}\int _{-b\pi }^{b\pi }e^{ikx}dk={\frac {1}{2\pi }}\int _{-\infty }^{\infty }e^{ikx}dk=\delta (x),}

which makes clear the recovery of the delta as an infinite bandwidth limit of the integral.

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:

∑ n = 1 ∞ sinc ⁡ ( n ) = sinc ⁡ ( 1 ) + sinc ⁡ ( 2 ) + sinc ⁡ ( 3 ) + sinc ⁡ ( 4 ) + ⋯ = π − 1 2 . {\displaystyle \sum _{n=1}^{\infty }\operatorname {sinc} (n)=\operatorname {sinc} (1)+\operatorname {sinc} (2)+\operatorname {sinc} (3)+\operatorname {sinc} (4)+\cdots ={\frac {\pi -1}{2}}.}

The sum of the squares also equals ⁠π − 1/2⁠:1112

∑ n = 1 ∞ sinc 2 ⁡ ( n ) = sinc 2 ⁡ ( 1 ) + sinc 2 ⁡ ( 2 ) + sinc 2 ⁡ ( 3 ) + sinc 2 ⁡ ( 4 ) + ⋯ = π − 1 2 . {\displaystyle \sum _{n=1}^{\infty }\operatorname {sinc} ^{2}(n)=\operatorname {sinc} ^{2}(1)+\operatorname {sinc} ^{2}(2)+\operatorname {sinc} ^{2}(3)+\operatorname {sinc} ^{2}(4)+\cdots ={\frac {\pi -1}{2}}.}

When the signs of the addends alternate and begin with +, the sum equals ⁠1/2⁠: ∑ n = 1 ∞ ( − 1 ) n + 1 sinc ⁡ ( n ) = sinc ⁡ ( 1 ) − sinc ⁡ ( 2 ) + sinc ⁡ ( 3 ) − sinc ⁡ ( 4 ) + ⋯ = 1 2 . {\displaystyle \sum _{n=1}^{\infty }(-1)^{n+1}\,\operatorname {sinc} (n)=\operatorname {sinc} (1)-\operatorname {sinc} (2)+\operatorname {sinc} (3)-\operatorname {sinc} (4)+\cdots ={\frac {1}{2}}.}

The alternating sums of the squares and cubes also equal ⁠1/2⁠:13 ∑ n = 1 ∞ ( − 1 ) n + 1 sinc 2 ⁡ ( n ) = sinc 2 ⁡ ( 1 ) − sinc 2 ⁡ ( 2 ) + sinc 2 ⁡ ( 3 ) − sinc 2 ⁡ ( 4 ) + ⋯ = 1 2 , {\displaystyle \sum _{n=1}^{\infty }(-1)^{n+1}\,\operatorname {sinc} ^{2}(n)=\operatorname {sinc} ^{2}(1)-\operatorname {sinc} ^{2}(2)+\operatorname {sinc} ^{2}(3)-\operatorname {sinc} ^{2}(4)+\cdots ={\frac {1}{2}},}

∑ n = 1 ∞ ( − 1 ) n + 1 sinc 3 ⁡ ( n ) = sinc 3 ⁡ ( 1 ) − sinc 3 ⁡ ( 2 ) + sinc 3 ⁡ ( 3 ) − sinc 3 ⁡ ( 4 ) + ⋯ = 1 2 . {\displaystyle \sum _{n=1}^{\infty }(-1)^{n+1}\,\operatorname {sinc} ^{3}(n)=\operatorname {sinc} ^{3}(1)-\operatorname {sinc} ^{3}(2)+\operatorname {sinc} ^{3}(3)-\operatorname {sinc} ^{3}(4)+\cdots ={\frac {1}{2}}.}

Series expansion

The Taylor series of the unnormalized sinc function can be obtained from that of the sine (which also yields its value of 1 at x = 0): sin ⁡ x x = ∑ n = 0 ∞ ( − 1 ) n x 2 n ( 2 n + 1 ) ! = 1 − x 2 3 ! + x 4 5 ! − x 6 7 ! + ⋯ {\displaystyle {\frac {\sin x}{x}}=\sum _{n=0}^{\infty }{\frac {(-1)^{n}x^{2n}}{(2n+1)!}}=1-{\frac {x^{2}}{3!}}+{\frac {x^{4}}{5!}}-{\frac {x^{6}}{7!}}+\cdots }

The series converges for all x. The normalized version follows easily: sin ⁡ π x π x = 1 − π 2 x 2 3 ! + π 4 x 4 5 ! − π 6 x 6 7 ! + ⋯ {\displaystyle {\frac {\sin \pi x}{\pi x}}=1-{\frac {\pi ^{2}x^{2}}{3!}}+{\frac {\pi ^{4}x^{4}}{5!}}-{\frac {\pi ^{6}x^{6}}{7!}}+\cdots }

Euler famously compared this series to the expansion of the infinite product form to solve the Basel problem.

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 derived14 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 u 1 = [ 1 2 3 2 ] and u 2 = [ 1 2 − 3 2 ] . {\displaystyle \mathbf {u} _{1}={\begin{bmatrix}{\frac {1}{2}}\\{\frac {\sqrt {3}}{2}}\end{bmatrix}}\quad {\text{and}}\quad \mathbf {u} _{2}={\begin{bmatrix}{\frac {1}{2}}\\-{\frac {\sqrt {3}}{2}}\end{bmatrix}}.}

Denoting ξ 1 = 2 3 u 1 , ξ 2 = 2 3 u 2 , ξ 3 = − 2 3 ( u 1 + u 2 ) , x = [ x y ] , {\displaystyle {\boldsymbol {\xi }}_{1}={\tfrac {2}{3}}\mathbf {u} _{1},\quad {\boldsymbol {\xi }}_{2}={\tfrac {2}{3}}\mathbf {u} _{2},\quad {\boldsymbol {\xi }}_{3}=-{\tfrac {2}{3}}(\mathbf {u} _{1}+\mathbf {u} _{2}),\quad \mathbf {x} ={\begin{bmatrix}x\\y\end{bmatrix}},} one can derive15 the sinc function for this hexagonal lattice as sinc H ⁡ ( x ) = 1 3 ( cos ⁡ ( π ξ 1 ⋅ x ) sinc ⁡ ( ξ 2 ⋅ x ) sinc ⁡ ( ξ 3 ⋅ x ) + cos ⁡ ( π ξ 2 ⋅ x ) sinc ⁡ ( ξ 3 ⋅ x ) sinc ⁡ ( ξ 1 ⋅ x ) + cos ⁡ ( π ξ 3 ⋅ x ) sinc ⁡ ( ξ 1 ⋅ x ) sinc ⁡ ( ξ 2 ⋅ x ) ) . {\displaystyle {\begin{aligned}\operatorname {sinc} _{\text{H}}(\mathbf {x} )={\tfrac {1}{3}}{\big (}&\cos \left(\pi {\boldsymbol {\xi }}_{1}\cdot \mathbf {x} \right)\operatorname {sinc} \left({\boldsymbol {\xi }}_{2}\cdot \mathbf {x} \right)\operatorname {sinc} \left({\boldsymbol {\xi }}_{3}\cdot \mathbf {x} \right)\\&{}+\cos \left(\pi {\boldsymbol {\xi }}_{2}\cdot \mathbf {x} \right)\operatorname {sinc} \left({\boldsymbol {\xi }}_{3}\cdot \mathbf {x} \right)\operatorname {sinc} \left({\boldsymbol {\xi }}_{1}\cdot \mathbf {x} \right)\\&{}+\cos \left(\pi {\boldsymbol {\xi }}_{3}\cdot \mathbf {x} \right)\operatorname {sinc} \left({\boldsymbol {\xi }}_{1}\cdot \mathbf {x} \right)\operatorname {sinc} \left({\boldsymbol {\xi }}_{2}\cdot \mathbf {x} \right){\big )}.\end{aligned}}}

This construction can be used to design Lanczos window for general multidimensional lattices.16

Sinhc

Some authors, by analogy, define the hyperbolic sine cardinal function.171819

s i n h c ( x ) = { sinh ⁡ ( x ) x , if  x ≠ 0 1 , if  x = 0 {\displaystyle \mathrm {sinhc} (x)={\begin{cases}{\displaystyle {\frac {\sinh(x)}{x}},}&{\text{if }}x\neq 0\\{\displaystyle 1,}&{\text{if }}x=0\end{cases}}}

See also

Further reading

  • Stenger, Frank (1993). Numerical Methods Based on Sinc and Analytic Functions. Springer Series on Computational Mathematics. Vol. 20. Springer-Verlag New York, Inc. doi:10.1007/978-1-4612-2706-9. ISBN 9781461276371.

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.. 978-0-521-19225-5

  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 15 978-0-07-063454-1

  3. Weisstein, Eric W. "Sinc Function". mathworld.wolfram.com. Retrieved 2023-06-07. https://mathworld.wolfram.com/

  4. Merca, Mircea (2016-03-01). "The cardinal sine function and the Chebyshev–Stirling numbers". Journal of Number Theory. 160: 19–31. doi:10.1016/j.jnt.2015.08.018. ISSN 0022-314X. S2CID 124388262. https://www.sciencedirect.com/science/article/pii/S0022314X15002863

  5. Poynton, Charles A. (2003). Digital video and HDTV. Morgan Kaufmann Publishers. p. 147. ISBN 978-1-55860-792-7. 978-1-55860-792-7

  6. 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. http://www.norbertwiener.umd.edu/crowds/documents/Woodward52.pdf

  7. Poynton, Charles A. (2003). Digital video and HDTV. Morgan Kaufmann Publishers. p. 147. ISBN 978-1-55860-792-7. 978-1-55860-792-7

  8. 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. {{cite book}}: ISBN / Date incompatibility (help) 978-0-89006-103-9

  9. Euler, Leonhard (1735). "On the sums of series of reciprocals". arXiv:math/0506415. /wiki/ArXiv_(identifier)

  10. Sanjar M. Abrarov; Brendan M. Quine (2015). "Sampling by incomplete cosine expansion of the sinc function: Application to the Voigt/complex error function". Appl. Math. Comput. 258: 425–435. arXiv:1407.0533. doi:10.1016/j.amc.2015.01.072. https://www.sciencedirect.com/science/article/pii/S0096300315001046

  11. "Advanced Problem 6241". American Mathematical Monthly. 87 (6). Washington, DC: Mathematical Association of America: 496–498. June–July 1980. doi:10.1080/00029890.1980.11995075. /wiki/Mathematical_Association_of_America

  12. 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. S2CID 496934. /wiki/David_Borwein

  13. Baillie, Robert (2008). "Fun with Fourier series". arXiv:0806.0150v2 [math.CA]. /wiki/ArXiv_(identifier)

  14. 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. S2CID 15313688. /wiki/Bibcode_(identifier)

  15. 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. S2CID 15313688. /wiki/Bibcode_(identifier)

  16. 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. S2CID 15313688. /wiki/Bibcode_(identifier)

  17. Ainslie, Michael (2010). Principles of Sonar Performance Modelling. Springer. p. 636. ISBN 9783540876625. 9783540876625

  18. Günter, Peter (2012). Nonlinear Optical Effects and Materials. Springer. p. 258. ISBN 9783540497134. 9783540497134

  19. Schächter, Levi (2013). Beam-Wave Interaction in Periodic and Quasi-Periodic Structures. Springer. p. 241. ISBN 9783662033982. 9783662033982