Harmonic Analysis on Totally Disconnected Sets
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		    The
 
 Wiener
 
 Process
 
 A.I.
 
 Probability
 
 Spaces
 
 A probability 2
 
 is
 
 a set,
 
 ~
 
 is
 
 negative
 
 countably
 
 property
 
 that
 
 whenever
 
 Ae~
 
 p(B)
 
 =
 
 0
 
 s~ace a
 
 is
 
 p(2)
 
 = i
 
 , p(A)
 
 set
 
 and
 
 of
 
 subsets
 
 that
 
 p
 
 we
 
 space
 
 of
 
 2
 
 : (~ + ~
 
 a meas'ure
 
 B~A
 
 Variables
 
 measure
 
 function
 
 ; recall
 
 = O,
 
 of R a n d o m
 
 a complete
 
 ~ - algebra
 
 additive
 
 element
 
 A to be
 
 or
 
 Expectat$on
 
 can
 
 (2,
 
 a,
 
 , and
 
 p
 
 , with
 
 the
 
 space
 
 conclude
 
 is
 
 p), is
 
 where
 
 a non-
 
 further
 
 complete
 
 that
 
 B~
 
 if and
 
 .
 
 An to
 
 and
 
 B to
 
 ~-A
 
 be
 
 AEa
 
 , the
 
 A~JB
 
 is
 
 an
 
 event
 
 e v e n t ......A
 
 We'll
 
 and we
 
 and
 
 need
 
 the
 
 define
 
 B to be following
 
 the
 
 event
 
 A~B
 
 , and
 
 easy
 
 result
 
 the on
 
 contrary event
 
 A
 
 several
 
 oc-
 
 casions.
 
 Proposition
 
 A.I
 
 Let
 
 {A.} ~ _ ~ J
 
 lira A. ~ ~ j
 
 a.
 
 b,
 
 be
 
 a sequence
 
 vt ~ A = {mgO n n>m
 
 m
 
 lim
 
 A.--- ~ ~ f | A = j ~.J, , n m n>m
 
 bet
 
 of
 
 of
 
 distinct
 
 events.
 
 : m
 
 is
 
 in
 
 infinitely
 
 : ~o
 
 is
 
 in
 
 all
 
 but
 
 all
 
 m
 
 wE
 
 ~ n>m
 
 A
 
 {~oc~
 
 Then
 
 many
 
 A,}. j
 
 a finite
 
 num-
 
 A.}
 
 J Proof.
 
 a.
 
 If
 
 ~s~
 
 ~ n>m
 
 m Thus
 
 for
 
 m=l
 
 is
 
 there
 
 such
 
 that
 
 assume
 
 then
 
 ~EA
 
 such
 
 , etc.
 
 there
 
 for
 
 n
 
 nI
 
 n
 
 Conversely
 
 A
 
 2 is
 
 {A
 
 that Hence
 
 n
 
 ~eAn
 
 ; for m=nl+l i is in i n f i n i t e l y
 
 there
 
 is
 
 w
 
 many
 
 A. J
 
 :j=l,...}
 
 such
 
 that
 
 ~eA
 
 n.
 
 b. with
 
 Let the
 
 ~
 
 for
 
 be
 
 a fixed
 
 in
 
 all
 
 property
 
 Therefore
 
 ~E~ n>m --
 
 Conversely,
 
 that
 
 let
 
 A
 
 m,
 
 but
 
 ~ n>m
 
 a finite
 
 ~eAn and
 
 n
 
 m~
 
 so
 
 each
 
 j.
 
 n.
 
 J Consequently
 
 for
 
 n2
 
 for
 
 An
 
 , and
 
 number all
 
 ~c~ m
 
 of
 
 therefore
 
 A. j
 
 ; hence
 
 O ~s~
 
 m
 
 U m n>m
 
 i
 
 An
 
 exists
 
 n> Im h n>m
 
 A
 
 n
 
 1
 
 ~eU m
 
 ~ n>m
 
 An
 
 ; then
 
 there
 
 is
 
 mI
 
 such
 
 that
 
 ~s ~ n>m
 
 -- I
 
 An.
 
 162
 
 This
 
 means
 
 that
 
 ~aA
 
 whenever
 
 n
 
 n>m -- i q.e.d.
 
 In surely
 
 a probability
 
 (a.s.)
 
 theoretic measure
 
 with
 
 respect
 
 expression p
 
 "
 
 If
 
 space to
 
 "almost S
 
 is
 
 we the
 
 frequently
 
 use
 
 2robability
 
 p
 
 everywhere
 
 a set
 
 then
 
 the
 
 instead
 
 (a.e.)
 
 a random
 
 expression
 
 with
 
 object
 
 almost
 
 of
 
 the
 
 respect
 
 to
 
 X
 
 in
 
 S
 
 measure the is
 
 a func-
 
 tion
 
 (A.1)
 
 Now
 
 X
 
 for
 
 a given
 
 random
 
 object
 
 B
 
 Since we
 
 a
 
 define
 
 is
 
 a
 
 the
 
 o -
 
 (A.I)
 
 ~
 
 {B~S
 
 algebra
 
 real-valued
 
 : ~ ÷
 
 it set
 
 is of
 
 ~x(B)
 
 - p(x-l(B))
 
 a probability
 
 space
 
 is
 
 clear
 
 that
 
 ~
 
 is
 
 a
 
 o -
 
 algebra,
 
 and
 
 function
 
 for
 
 each
 
 and
 
 we
 
 If
 
 B~
 
 the
 
 : B ~
 
 Be8
 
 refer
 
 event
 
 ~
 
 . It to
 
 is
 
 this
 
 X-I(B)
 
 {X~B}
 
 S
 
 ~
 
 tionally,
 
 (0,i)
 
 the
 
 and
 
 Aca
 
 event
 
 A
 
 A
 
 Generally in
 
 define
 
 immediate space
 
 as
 
 that the
 
 (S,
 
 8,
 
 ~X )
 
 distribution
 
 X
 
 Notation
 
 If
 
 we
 
 .
 
 : X-I(B)~a}
 
 WX
 
 as
 
 S
 
 terms
 
 for of
 
 any X
 
 S
 
 , then
 
 ~
 
 then is
 
 =
 
 and we
 
 {~
 
 XA
 
 :
 
 ~
 
 by
 
 is
 
 a
 
 random
 
 } -
 
 {X A
 
 =
 
 i}
 
 random
 
 object
 
 =
 
 : R(X(~))
 
 X
 
 , if
 
 write
 
 {R(X)}
 
 {~e2
 
 ; that
 
 is,
 
 .
 
 S
 
 ÷
 
 {X~B}
 
 object
 
 and,
 
 nota-
 
 as
 
 : XA(~)=i
 
 any
 
 denoted
 
 : X(~)eB}
 
 written
 
 {m
 
 is
 
 }
 
 •
 
 R(X)
 
 is
 
 a
 
 relation
 
 163
 
 Now, then
 
 X
 
 is
 
 algebra the
 
 S
 
 is
 
 a random
 
 E
 
 a topological
 
 variable
 
 that
 
 algebra is
 
 (resp., random
 
 S
 
 (recall
 
 Borel
 
 When
 
 if
 
 is
 
 ; note
 
 that
 
 is m e a s u r a b l e		
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