Page 320 - Electrical Engineering Dictionary

covariance 6: Gaussian sphere unit sphere, with an
associated spherical coordinate system, nor-
−N/2 −1/2
f(x) = (2π) |6| mally used to represent orientations.

T
exp −(x − µ) 6 −1 (x − µ)/2 ,
gaussmeter an instrument to measure the
flux density due to a magnetic field.
where |6| represents the determinant of 6
and N represents the dimensionality of x.If
Ge See germanium.
x is scalar then the above function simplifies
considerably to its more familiar form: geared robot an arbitrary robot equipped
with gears is called a geared robot. See direct
2
1 1 (x − µ)
f(x) = √ exp − 2 . drive robot.
2πσ 2 σ
genco a contraction of "generating com-
The Gaussian distribution is tremendously
pany," which is a company which generates
important in modeling signals, images, and
electric power but does not engage in trans-
noise, due to its convenient analytic prop-
mission or distribution activities.
erties and due to the central limit theorem.
See also probability density function, mean,
gender an adapter presenting two male or
covariance. See also Cauchy distribution,
two female connectors for reversing the type
exponential distribution.
of cable connector. Connectors can be of the
same type or not.
Gaussian elimination the standard direct
method for solving a set of linear equations.
general response formula for 2-D Roesser
It is termed direct because it does not involve
model the solution to the 2-D Roesser
iterative solutions. Variations of this scheme
model
are used in most circuit simulators.
" h #
x
i+1,j
Gaussian mirror mirror in which the re- x v i,j+1 =
flection profile is a Gaussian function of ra- " #
h
dius. A 1 A 2 x ij + B 1 u ij (1a)
A 3 A 4 x v B 2
ij
Gaussian noise a noise process that has a
Gaussian distribution for the measured value i, j ∈ Z + (the set of nonnegative integers)
at any time instant. " #
x h
ij
y ij = [C 1 ,C 2 ] v + Du ij (1b)
Gaussian process (1) a random process x ij
where the joint distribution of a set of random
h
variables X 1 ,X 2 ,...,X n determined as val- with boundary conditions x ,j ∈ Z + and
0j
v
x ,i ∈ Z + is given by
ues of the process at the points t 1 ,t 2 ,...,t n
i0
is an n-variate Gaussian distribution for all
" # i
sets of points t 1 ,t 2 ,...,t n , and all values of x h X 0
ij
v
v
the integer n. x ij = T i−p,j x p0
(2) a random (stochastic) process x(t) is p=1
j
Gaussianiftherandomvariablesx(t 1 ), x(t 2 ), X x h
...,x(t n ) are jointly Gaussian for any n. + T i,j−q 0q (2)
0
q=1
Gaussian pulse pulse in which the field i j
X X
is a Gaussian function of time from the pulse + T i−p−1,j−q B 1
maximum. p=0 q=0 0
c
2000 by CRC Press LLC