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21: 33.5 Limiting Forms for Small ρ , Small | η | , or Large
§33.5 Limiting Forms for Small ρ , Small | η | , or Large
§33.5(i) Small ρ
33.5.6 C ( 0 ) = 2 ! ( 2 + 1 ) ! = 1 ( 2 + 1 ) !! .
§33.5(iii) Small | η |
§33.5(iv) Large
22: 28.14 Fourier Series
28.14.1 me ν ( z , q ) = m = c 2 m ν ( q ) e i ( ν + 2 m ) z ,
and the normalization relation
28.14.5 m = ( c 2 m ν ( q ) ) 2 = 1 ;
23: 19.31 Probability Distributions
R G ( x , y , z ) and R F ( x , y , z ) occur as the expectation values, relative to a normal probability distribution in 2 or 3 , of the square root or reciprocal square root of a quadratic form. …
24: 28.12 Definitions and Basic Properties
As in §28.7 values of q for which (28.2.16) has simple roots λ are called normal values with respect to ν . For real values of ν and q all the λ ν ( q ) are real, and q is normal. … If q is a normal value of the corresponding equation (28.2.16), then these functions are uniquely determined as analytic functions of z and q by the normalization
25: 33.10 Limiting Forms for Large ρ or Large | η |
§33.10 Limiting Forms for Large ρ or Large | η |
§33.10(i) Large ρ
§33.10(ii) Large Positive η
§33.10(iii) Large Negative η
26: 1.6 Vectors and Vector-Valued Functions
Suppose S is a piecewise smooth surface which forms the complete boundary of a bounded closed point set V , and S is oriented by its normal being outwards from V . …
27: 31.11 Expansions in Series of Hypergeometric Functions
Series of Type II (§31.11(iv)) are expansions in orthogonal polynomials, which are useful in calculations of normalization integrals for Heun functions; see Erdélyi (1944) and §31.9(i). …
§31.11(ii) General Form
28: 30.16 Methods of Computation
Form the eigenvector [ e 1 , d , e 2 , d , , e d , d ] T of 𝐀 associated with the eigenvalue α p , d , p = 1 2 ( n m ) + 1 , normalized according to …
29: 7.20 Mathematical Applications
See accompanying text
Figure 7.20.1: Cornu’s spiral, formed from Fresnel integrals, is defined parametrically by x = C ( t ) , y = S ( t ) , t [ 0 , ) . Magnify
The normal distribution function with mean m and standard deviation σ is given by …For applications in statistics and probability theory, also for the role of the normal distribution functions (the error functions and probability integrals) in the asymptotics of arbitrary probability density functions, see Johnson et al. (1994, Chapter 13) and Patel and Read (1982, Chapters 2 and 3).
30: Bibliography C
  • B. C. Carlson (1964) Normal elliptic integrals of the first and second kinds. Duke Math. J. 31 (3), pp. 405–419.
  • B. C. Carlson (1972b) Intégrandes à deux formes quadratiques. C. R. Acad. Sci. Paris Sér. A–B 274 (15 May, 1972, Sér. A), pp. 1458–1461 (French).
  • M. A. Chaudhry, N. M. Temme, and E. J. M. Veling (1996) Asymptotics and closed form of a generalized incomplete gamma function. J. Comput. Appl. Math. 67 (2), pp. 371–379.
  • G. Cornell, J. H. Silverman, and G. Stevens (Eds.) (1997) Modular Forms and Fermat’s Last Theorem. Springer-Verlag, New York.
  • S. W. Cunningham (1969) Algorithm AS 24: From normal integral to deviate. Appl. Statist. 18 (3), pp. 290–293.