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Measurement, Instrumentation, and Sensors Handbook, Second Edition, 2nd Edition
book

Measurement, Instrumentation, and Sensors Handbook, Second Edition, 2nd Edition

by John G. Webster, Halit Eren
February 2014
Intermediate to advanced content levelIntermediate to advanced
1921 pages
82h 13m
English
CRC Press
Content preview from Measurement, Instrumentation, and Sensors Handbook, Second Edition, 2nd Edition
17-1
17.1 Introduction
A neural network with basis functions that remain invariant under the Fourier transform is pro-
posed
fo
r
fa
ult
di
agnosis
of no
nlinear
sy
stems
. e co
nsidered
ne
ural
ne
twork
is of th
e
fe
edforward
ty
pe
an
d
us
es
Ga
uss–Hermite
po
lynomial
ba
sis
fu
nctions
. i
s
ne
ural
mo
del
fo
llows
th
e
co
ncept
of wa
velet
ne
tworks
[1
–3]
an
d
em
ploys
ba
sis
fu
nctions
th
at
ar
e
lo
calized
bo
th
in sp
ace
an
d
fr
e-
quency,thus
al
lowing
be
tter
ap
proximation
of th
e
mu
ltifrequency
ch
aracteristics
of mo
nitored
no
n-
linear
sy
stem
[4
–8]
. Ga
uss–Hermite
ba
sis
fu
nctions
ha
ve
so
me
in
teresting
pr
operties
[9
,10]:
(1
)
e
y
re
main
al
most
un
changed
by th
e
Fo
urier
tr
ans ...
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Publisher Resources

ISBN: 9781439848913