, (1). -, [9], [1]. 1.. T =[ a] R: _(t)=f((t)) _ L(t) () = x f, L(t) T., L(t), L() = L(a ; ) = L(a). (2) - : L n (t) =(L n )(t) = 1=n R supp [ 1], 1R

Size: px
Start display at page:

Download ", (1). -, [9], [1]. 1.. T =[ a] R: _(t)=f((t)) _ L(t) () = x f, L(t) T., L(t), L() = L(a ; ) = L(a). (2) - : L n (t) =(L n )(t) = 1=n R supp [ 1], 1R"

Transcription

1 25 3(514) ,..,.. -.,.., -, -. : _x(t) =f(t x(t)) _ L(t) (1) L(t) _.. - -, f(t x(t)) L(t). _ ([1],. 1, x 8,. 41),. [2]{[4],., [2]{[4],, [1]. - x(t) =x f( x())dl() t {, {.. [5]{[7]. L(t),. [8] (1), L(t). ([1],. 4,. 143) : x(t) =x t f( x())dl c () i<t S( i x( i ; ) L( i )) S( p x( p ; ) L( p ))(t ; p ) L c (t) L(t), i L(t), L( i ) = L d ( i ); L d ( i ; ), (t), S( i x( i ; ) L( i )).,, - [1],. 23

2 , (1). -, [9], [1]. 1.. T =[ a] R: _(t)=f((t)) _ L(t) () = x f, L(t) T., L(t), L() = L(a ; ) = L(a). (2) - : L n (t) =(L n )(t) = 1=n R supp [ 1], 1R (s)ds =1. n (t h n ) ; n (t) =f n ( n (t))[l n (t h n ) ; L n (t)] n (t)j [ hn) = n (t): L(t s) n (s)ds, f n = f n, n (t) =n(nt), (t) 2 C 1 (R), (t), t T. t t = t m t h n, t 2 [ h n ), m t 2 N., (3) n (t) = n ( t ) f n ( n ( t kh n ))[L n ( t (k 1)h n ) ; L n ( t kh n )]: 1. f 2 CB(R). 1 n! 1, h n!, h n = o(1=n) t 2 T, n (t) (3) Y (L(t)), Y (v) Y (v) =x Z v t 2 T j n ( t ) ; x j!. (2) (3) f(y (u))du (4) 1., Y (L(t)) - x(t) =x f(x())dl c () S(x( i ; ) L( i )) t it R S(x u)='(1 x u);'( x u), '(t x u) '(t x u)=xu t f('(s x u))ds., 1, n!1, h n!, h n = o(1=n), - (3) [1] (2). 2. f 2 CB(R). 1 n!1, h n!, 1=n = o(h n ), t 2 T n (t) (3) (t) =x t 2 T j n ( t ) ; x j!. f((s ; ))dl(s) (5) 24

3 2., (3) - (2), [5]{[7] n Z n1 A n A k n B k Z k (6) A, A k, B k Z k > k = n. - n n Z n1 A A k exp B k :. (6), Z n1 A n B k Z k n A k B k Z k B n Z n A B k Z k = A n n A k B n A A k A k B n A A k (B n 1) B k Z k A A k B n A A k B (B n 1) B 1 (1 B 2 (1 (1B (1 B n )))) A n ln Z n1 ln A A k. n A n ln(1 B n ) ln A S 2 L n (t) = mt [L n ( t kh n ) ; L n ( t (k ; 1)h n )] 2. n;2 A k ny n A k A k (1 B n ): 2. L(t). S 2 L n (t)! t 2 T, n!1, h n! h n = o(1=n).. L(t) n B n : L(t)=L c (t)l d (t) (7) L c () L d () L(). L(), S 2 L n (t) max jl n ( t kh n ) ; L n ( t (k ; 1)h n )j 1km t m t L(t) max jl n ( t kh n ) ; L n ( t (k ; 1)h n )j: 1km t 25 jl n ( t kh n ) ; L n ( t (k ; 1)h n )j

4 L n. L n n, (7), = jl n ( t kh n ) ; L n ( t (k ; 1)h n )j = [L( t kh n s) ; L( t (k ; 1)h n s)] n (s)ds max s1=n jlc ( t kh n s) ; ;L c ( t (k ; 1)h n s)j max jt 1;t 2j1=n jl c (t 1 ) ; L c (t 2 )j [L d ( t kh n s) ; L d ( t (k ; 1)h n s)] n (s)ds [L d ( t kh n s) ; L d ( t (k ; 1)h n s)] n (s)ds : n!1 L c () T.. L(), 1 jl( i )j < 1. " > n 2 N, 1 jl( i )j <": i=n L d () L d (t) =L d n (t)l d <n (t) (8) L d n () L d <n () i, n,..i n, n,..i<n,.,, h n < 1=n n, n h [L d ( t kh n s) ; L d ( t (k ; 1)h n s)] n (s)ds ;L d n ( t (k ; 1)h n s)] n (s)ds s)] n (s)ds 1 i=n jl d ( i )j 1 Z 1=n i=n jl d ( i )j n (s)ds L(t) [L d n ( t kh n s) ; [L d <n ( t kh n s) ; L d <n ( t (k ; 1)h n Z i; t;(i;1)h n i; t;ih n nh n " L(t) L d ( i ) n (s)ds nh n :, ". 1. (2) n (t) = n ( t ) f n ( n ( t kh n ))[L n ( t (k 1)h n ) ; L n ( t kh n )]:, Y (u) (4), j n (t) ; Y (L n (t))j = n( t ) ;L n ( t kh n )] ; x ; m Z Ln(t) m f n ( n ( t kh n ))[L n ( t (k 1)h n ) ; f(y (s))ds j n( t ) ; x j Z Ln( t) ; fn ( n ( t kh n )) ; f( n ( t kh n )) [L n ( t (k 1)h n ) ; 26 f(y (s))ds

5 ;L n ( t kh n )] ;L n ( t kh n )] m ; f(n ( t kh n )) ; f(y (L n ( t kh n )) [L n ( t (k 1)h n ) ; m Z Ln( t(k1)h n) [f(y (L n ( t kh n ))) ; f(y (s))] ds = L n( tkh n) = I 1 (t)i 2 (t)i 3 (t)i 4 (t)i 5 (t): M = max x2r jf(x)j, M 1 =max x2r jf (x)j. f 2 C 1 B(R), MM 1 < 1. I 2 (t) MjL n ( t )j:, L, L n f n, : I 3 (t) m ; fn ( n ( t kh n ));f( n ( t kh n )) [L n ( t (k 1)h n );L n ( t kh n )] I 4 (t) = ;L n ( t kh n )] M 1 m ; f(n ( t kh n )) ; f(y (L n ( t kh n ))) [L n ( t (k 1)h n ) ; M 1 L(t)=n: j n ( t kh n ) ; Y (L n ( t kh n ))jjl n ( t (k 1)h n ) ; L n ( t kh n )j: (4) m MM 1 I 5 (t) = Z Ln( t(k1)h n) L n( tkh n) Z Ln( t(k1)h n) L n( tkh n) jl n ( t kh n ) ; sjds = MM 1 2, [f(y (L n ( t kh n ))) ; f(y (s))]ds [L n ( t (k 1)h n ) ; L n ( t kh n )] 2 : j n (t) ; Y (L n (t))j j n ( t ) ; x j MjL n ( t )j M 1 L(t)=n M 1 j n ( t kh n ) ; Y (L n ( t kh n ))jjl n ( t (k 1)h n ) ; L n ( t kh n )j MM 1 2 [L n ( t (k 1)h n ) ; L n ( t kh n )] 2 : 1, j n (t) ; Y (L n (t))j j n ( t ) ; x j MjL n ( t )j M 1 L(t)=n MM 1 2 [L n ( t (k 1)h n ) ; L n ( t kh n )] 2 exp ; M 1 L(t) : n! 1, h n!, h n = o(1=n), (5) (t) =x f((s)) dl c (s) it f(( i ; ))L d ( i ),, i, L d ( i ) L(t). 27

6 : j n (t) ; (t)j = n( t ) ; x ;L n ( t kh n )] ; j n ( t ) ; x j m f n ( n ( t kh n ))[L n ( t (k 1)h n ) ; f((s))dl c (s) ; f(( i ; ))L d ( i ) it f((s)) dl c (s) kh n )))[L n ( t (k 1)h n ) ; L n ( t kh n )] kh n )))[L n ( t (k 1)h n ) ; L n ( t kh n )] m m m (f n ( n ( t kh n )) ; f( n ( t (f( n ( t kh n )) ; f(( t f(( t kh n ))[L c n( t (k 1)h n ) ; L c n( t kh n )] ; f(( t kh n ))[L c ( t (k 1)h n ) ; L c ( t kh n )] m m f(( t kh n ))[L c ( t (k 1)h n ) ; L c ( t kh n )] ; f((s)) dl c (s) t f(( t kh n ))[L d n( t (k 1)h n ) ; L d n( t kh n )] ; f(( i ; ))L d ( i ) = it = I 1 (t)i 2 (t)i 3 (t)i 4 (t)i 5 (t)i 6 (t)i 7 (t): f 2 C 1 B(R) L(t), I 2 (t) M f n L n, I 3 (t) (M 1 =n) jl n ( t kh n ) ; L n ( t (k 1)h n )jm 1 L(t)=n:, f 2 C 1 B(R), m I 4 (t) M 1 j n ( t kh n ) ; ( t kh n )jjl n ( t (k 1)h n ) ; L n ( t kh n )j: L c (t). t2[ h n) I 5 (t),, (t): = m t I 5 (t) = m ; f(( t kh n ))[L c n( t (k 1)h n ) ; L c ( t (k 1)h n )] ; f(( t kh n ))[L c n( t kh n ) ; L c ( t kh n )] = f(( t (k ; 1)h n ))[L c n( t kh n ) ; L c ( t kh n )] ; ;L c ( t kh n )] m = f(( t kh n ))[L c n( t kh n ) ; [f(( t (k ; 1)h n )) ; f(( t kh n ))][L c n( t kh n ) ; L c ( t kh n )] f(( t (m t ; 1)h n ))(L c n( t m t h n ) ; L c ( t m t h n )) ; 28

7 ;f(( t ))(L c n( t ) ; L c ( t )) M 1 ;( t kh n )j M M 1 (t) M 1 M L(t) m t2[ tkh n t(k1)h n] max t2[ tkh n tkh n1=n] L c (t)m t2[t 1 t 2] L c (t)2m max t2[t 1 t 2] L c (t)2m M 1 m M 1 I 6 (t)= ; max t f ; (bs(s)) ; f ; (s) dlc (s) t2[ tkh n t(k1)h n] (t) L c (t)j( t (k ; 1)h n ) ; L c (t) t2[ tm th n tm th n1=n] max L c (t) t2[t 1 t 2] max L c (t): t2[t 1 t 2] t2[ tkh n t(k1)h n] L c (t) (t) MM 1 L(t) t2[t 1 t 2] L c (t) max t2[t 1 t 2] L c (t) bs(s) = t kh n, s 2 [ t kh n t (k 1)h n ). I 7 (t). (8), I 7 (t) m f(( t kh n ))[L d <n n ( t kh n ) ; L d <n n ( t (k 1)h n )] ; ; it f(( i ; ))L d <n ( i ) ;L d n m f(( t kh n ))[L d n n ( t kh n ) ; n ( t (k 1)h n )] ; f(( i ; ))L d n ( i ) = I 7(t)I 1 7(t): 2 it L d <n (t) n ; 1 T, k i, i 2 [ t k i h n t (k i 1)h n ],, h n < 1=2 min j i1 ; i j, R 1in ;1 k i 6= k j i 6= j.,, 1=n = o(h n ), i;(ki;1)hn;t n (s)ds =1.O i;(k i1)h n; t, L n : Z i;(k i;1)h n; t I7(t)= 1 f(( t (k i ; 1)h n )) n (s)ds i;k ih n; t it f(( t k i h n )) max jl d ( i )j 1in ;1 Z i;k ih n; t i;(k i1)h n; t n (s)ds ; f(( i ; )) n ;1 Z i;(k i;1)h n; t L d <n ( i ) i;k ih n; t n (s)ds(f(( t (k i ; 1)h n )) ; ;f(( t k i h n ))) f(( t k i h n )) ; f(( i ; )) L(t) jf(( t (k i ; 1)h n ) ; n ;1 ;f(( t k i h n ))j jf(( t k i h n )) ; f(( i ; ))j M 1 L(t) n ;1 j( t (k i ; 1)h n ) ; ( t k i h n )j 29 j( t k i h n ) ; ( i ; )j

8 MM 1 L(t) t2[ t(k i;1)h n tk ih n] MM 1 L(t) n ;1 L(t) t2[ i;2h n i] L c (t)" t2[ tk ih n i) : L(t), [ i ; 2h n i ) [ t (k i ; 1)h n i ) L(t) L c (t) ", L(t) L c (t)"., [ i;2h n i) I 2 7(t) = m [ i;2h n i] j n (t) ; (t)j j n ( t ) ; x j M f(( t kh n ))[L d n ( t kh n ) ; L d n ( t (k 1)h n )] ; ; f(( i ; ))L d n ( i ) 2M": it ;( t kh n )jjl n ( t kh n ) ; L n ( t (k 1)h n )j M 1 2M max L c (t)mm 1 t2[t 1 t 2] MM 1 L(t) L c (t)m 1 L(t)=n M 1 j n ( t kh n ) ; t2[ h n) t2[ i;2h n i] max max L c (t)m L(t) t2[t 1 t 2] L c (t) L(t) t2[t 1 t 2] L c (t)" 2M": 1, j n (t) ; (t)j j n ( t ) ; x j M L c (t)m 1 L(t)=n t2[ h n) MM 1 M 1 max L c (t)m L(t)2M t2[t 1 t 2] max max L c (t) L(t)MM 1 L(t) t2[t 1 t 2] 2M" exp ; M 1 L(t) : t2[t 1 t 2] L c (t) t2[ i;2h n i] L c (t)" n!1, h n!, 1=n = o(h n ), "!, L c (t) T,,, j n (t) ; (t)j! t 2 T. 3. (5) : x(t)=x t f(x()) dl c () it S(x( i ; ) L( i )) S(x u) ='(1 x u) ; '( x u), '(t x u) '(t x u) =x u Z [ t) 3 f('(s x u)) d(s)

9 ( 1 s> (s) = s : 1 3, (2) x(t)=x f(x()) dl c () S(x( i ; ) L( i )) (9) t it S(x u) = '(1 x u) ; '( x u) '(t x u) -. \ " n, - (3),, (9), - '(t x u)., n - (2), [2]{[4].,, L(t), (3), -, " " n (9). 1...,... M. {.:, { Antosik., Ligeza J. roducts of measures and functions of nite iations // Generalized functions and operational calculus: roc. Conf. { Varna, { Soa, {. 2{ Ligeza J. On generalized solutions of some dierential non-linear equations of order n // Ann. ol. math. { {V.31.{ 2.{. 115{ Ligeza J. The existence and uniqueness of some systems of non-linear dierential equations // Cas. pestov. math. { { V. 12. { 1. {. 218{ //. { :.. -, {. 63{ Das.C., Sharma R.R. Existence and stability of measure dierential equations // Czech. Math. J. { { V. 22. { 1. {. 145{ andit S.G., Deo S.G. Dierential systems involving impulses // Lect. Notes Math. { { V { 12 p. 8. Kurzweil J. Generalized ordinary dierential equations // Czech. Math. J. { { V. 8. { 1. {. 36{ ,..,.. //... { {. 43. { 2. {. 272{ ,.. //... { 21. {. 42. { 1. {. 87{

Colby College Catalogue

Colby College Catalogue Colby College Digital Commons @ Colby Colby Catalogues College Archives: Colbiana Collection 1866 Colby College Catalogue 1866-1867 Colby College Follow this and additional works at: http://digitalcommons.colby.edu/catalogs

More information

PR D NT N n TR T F R 6 pr l 8 Th Pr d nt Th h t H h n t n, D D r r. Pr d nt: n J n r f th r d t r v th tr t d rn z t n pr r f th n t d t t. n

PR D NT N n TR T F R 6 pr l 8 Th Pr d nt Th h t H h n t n, D D r r. Pr d nt: n J n r f th r d t r v th tr t d rn z t n pr r f th n t d t t. n R P RT F TH PR D NT N N TR T F R N V R T F NN T V D 0 0 : R PR P R JT..P.. D 2 PR L 8 8 J PR D NT N n TR T F R 6 pr l 8 Th Pr d nt Th h t H h n t n, D.. 20 00 D r r. Pr d nt: n J n r f th r d t r v th

More information

n

n p l p bl t n t t f Fl r d, D p rt nt f N t r l R r, D v n f nt r r R r, B r f l. n.24 80 T ll h, Fl. : Fl r d D p rt nt f N t r l R r, B r f l, 86. http://hdl.handle.net/2027/mdp.39015007497111 r t v n

More information

,.*Hffi;;* SONAI, IUERCANTII,N I,IMITDII REGD- 0FFICE: 105/33, VARDHMAN GotD[N PLNLA,R0AD No.44, pitampura, DELHI *ffigfk"

,.*Hffi;;* SONAI, IUERCANTII,N I,IMITDII REGD- 0FFICE: 105/33, VARDHMAN GotD[N PLNLA,R0AD No.44, pitampura, DELHI *ffigfk $ S, URCT,,MTD RGD 0C: 10/, VRDM G[ LL,R0D.44, ptmpur, DL114 C: l22ldll98l,c0224gb, eb:.nlmernte.m T, Dte: 17h tber, 201 BS Lmted hre ]eejeebhy Ter Dll Street Mumb 41 The Mnger (Ltng) Delh Stk xhnge /1,

More information

Colby College Catalogue

Colby College Catalogue Colby College Digital Commons @ Colby Colby Catalogues College Archives: Colbiana Collection 1871 Colby College Catalogue 1871-1872 Colby College Follow this and additional works at: http://digitalcommonscolbyedu/catalogs

More information

H NT Z N RT L 0 4 n f lt r h v d lt n r n, h p l," "Fl d nd fl d " ( n l d n l tr l t nt r t t n t nt t nt n fr n nl, th t l n r tr t nt. r d n f d rd n t th nd r nt r d t n th t th n r lth h v b n f

More information

Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v

Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v Th n nt T p n n th V ll f x Th r h l l r r h nd xpl r t n rr d nt ff t b Pr f r ll N v n d r n th r 8 l t p t, n z n l n n th n rth t rn p rt n f th v ll f x, h v nd d pr v n t fr tf l t th f nt r n r

More information

Časopis pro pěstování matematiky

Časopis pro pěstování matematiky Časopis pro pěstování matematiky Jan Ligȩza On distributional solutions of some systems of linear differential equations Časopis pro pěstování matematiky, Vol. 102 (1977), No. 1, 37--41 Persistent URL:

More information

z E z *" I»! HI UJ LU Q t i G < Q UJ > UJ >- C/J o> o C/) X X UJ 5 UJ 0) te : < C/) < 2 H CD O O) </> UJ Ü QC < 4* P? K ll I I <% "fei 'Q f

z E z * I»! HI UJ LU Q t i G < Q UJ > UJ >- C/J o> o C/) X X UJ 5 UJ 0) te : < C/) < 2 H CD O O) </> UJ Ü QC < 4* P? K ll I I <% fei 'Q f I % 4*? ll I - ü z /) I J (5 /) 2 - / J z Q. J X X J 5 G Q J s J J /J z *" J - LL L Q t-i ' '," ; i-'i S": t : i ) Q "fi 'Q f I»! t i TIS NT IS BST QALITY AVAILABL. T Y FRNIS T TI NTAIN A SIGNIFIANT NBR

More information

n r t d n :4 T P bl D n, l d t z d th tr t. r pd l

n r t d n :4 T P bl D n, l d t z d   th tr t. r pd l n r t d n 20 20 :4 T P bl D n, l d t z d http:.h th tr t. r pd l 2 0 x pt n f t v t, f f d, b th n nd th P r n h h, th r h v n t b n p d f r nt r. Th t v v d pr n, h v r, p n th pl v t r, d b p t r b R

More information

Humanistic, and Particularly Classical, Studies as a Preparation for the Law

Humanistic, and Particularly Classical, Studies as a Preparation for the Law University of Michigan Law School University of Michigan Law School Scholarship Repository Articles Faculty Scholarship 1907 Humanistic, and Particularly Classical, Studies as a Preparation for the Law

More information

Th pr nt n f r n th f ft nth nt r b R b rt Pr t r. Pr t r, R b rt, b. 868. xf rd : Pr nt d f r th B bl r ph l t t th xf rd n v r t Pr, 00. http://hdl.handle.net/2027/nyp.33433006349173 P bl D n n th n

More information

l f t n nd bj t nd x f r t l n nd rr n n th b nd p phl t f l br r. D, lv l, 8. h r t,., 8 6. http://hdl.handle.net/2027/miun.aey7382.0001.001 P bl D n http://www.hathitrust.org/access_use#pd Th r n th

More information

The concentration of a drug in blood. Exponential decay. Different realizations. Exponential decay with noise. dc(t) dt.

The concentration of a drug in blood. Exponential decay. Different realizations. Exponential decay with noise. dc(t) dt. The concentration of a drug in blood Exponential decay C12 concentration 2 4 6 8 1 C12 concentration 2 4 6 8 1 dc(t) dt = µc(t) C(t) = C()e µt 2 4 6 8 1 12 time in minutes 2 4 6 8 1 12 time in minutes

More information

4 8 N v btr 20, 20 th r l f ff nt f l t. r t pl n f r th n tr t n f h h v lr d b n r d t, rd n t h h th t b t f l rd n t f th rld ll b n tr t d n R th

4 8 N v btr 20, 20 th r l f ff nt f l t. r t pl n f r th n tr t n f h h v lr d b n r d t, rd n t h h th t b t f l rd n t f th rld ll b n tr t d n R th n r t d n 20 2 :24 T P bl D n, l d t z d http:.h th tr t. r pd l 4 8 N v btr 20, 20 th r l f ff nt f l t. r t pl n f r th n tr t n f h h v lr d b n r d t, rd n t h h th t b t f l rd n t f th rld ll b n

More information

Ordinary Differential Equation Theory

Ordinary Differential Equation Theory Part I Ordinary Differential Equation Theory 1 Introductory Theory An n th order ODE for y = y(t) has the form Usually it can be written F (t, y, y,.., y (n) ) = y (n) = f(t, y, y,.., y (n 1) ) (Implicit

More information

,. *â â > V>V. â ND * 828.

,. *â â > V>V. â ND * 828. BL D,. *â â > V>V Z V L. XX. J N R â J N, 828. LL BL D, D NB R H â ND T. D LL, TR ND, L ND N. * 828. n r t d n 20 2 2 0 : 0 T http: hdl.h ndl.n t 202 dp. 0 02802 68 Th N : l nd r.. N > R, L X. Fn r f,

More information

Colby College Catalogue

Colby College Catalogue Colby College Digital Commons @ Colby Colby Catalogues College Archives: Colbiana Collection 1870 Colby College Catalogue 1870-1871 Colby College Follow this and additional works at: http://digitalcommonscolbyedu/catalogs

More information

N V R T F L F RN P BL T N B ll t n f th D p rt nt f l V l., N., pp NDR. L N, d t r T N P F F L T RTL FR R N. B. P. H. Th t t d n t r n h r d r

N V R T F L F RN P BL T N B ll t n f th D p rt nt f l V l., N., pp NDR. L N, d t r T N P F F L T RTL FR R N. B. P. H. Th t t d n t r n h r d r n r t d n 20 2 04 2 :0 T http: hdl.h ndl.n t 202 dp. 0 02 000 N V R T F L F RN P BL T N B ll t n f th D p rt nt f l V l., N., pp. 2 24. NDR. L N, d t r T N P F F L T RTL FR R N. B. P. H. Th t t d n t r

More information

D t r l f r th n t d t t pr p r d b th t ff f th l t tt n N tr t n nd H n N d, n t d t t n t. n t d t t. h n t n :.. vt. Pr nt. ff.,. http://hdl.handle.net/2027/uiug.30112023368936 P bl D n, l d t z d

More information

Colby College Catalogue

Colby College Catalogue Colby College Digital Commons @ Colby Colby Catalogues College Archives: Colbiana Collection 1872 Colby College Catalogue 1872-1873 Colby College Follow this and additional works at: http://digitalcommonscolbyedu/catalogs

More information

0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n. R v n n th r

0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n. R v n n th r n r t d n 20 22 0: T P bl D n, l d t z d http:.h th tr t. r pd l 0 t b r 6, 20 t l nf r nt f th l t th t v t f th th lv, ntr t n t th l l l nd d p rt nt th t f ttr t n th p nt t th r f l nd d tr b t n.

More information

Exhibit 2-9/30/15 Invoice Filing Page 1841 of Page 3660 Docket No

Exhibit 2-9/30/15 Invoice Filing Page 1841 of Page 3660 Docket No xhibit 2-9/3/15 Invie Filing Pge 1841 f Pge 366 Dket. 44498 F u v 7? u ' 1 L ffi s xs L. s 91 S'.e q ; t w W yn S. s t = p '1 F? 5! 4 ` p V -', {} f6 3 j v > ; gl. li -. " F LL tfi = g us J 3 y 4 @" V)

More information

l [ L&U DOK. SENTER Denne rapport tilhører Returneres etter bruk Dokument: Arkiv: Arkivstykke/Ref: ARKAS OO.S Merknad: CP0205V Plassering:

l [ L&U DOK. SENTER Denne rapport tilhører Returneres etter bruk Dokument: Arkiv: Arkivstykke/Ref: ARKAS OO.S Merknad: CP0205V Plassering: I Denne rapport thører L&U DOK. SENTER Returneres etter bruk UTLÅN FRA FJERNARKIVET. UTLÅN ID: 02-0752 MASKINVN 4, FORUS - ADRESSE ST-MA LANETAKER ER ANSVARLIG FOR RETUR AV DETTE DOKUMENTET. VENNLIGST

More information

EDRP lecture 7. Poisson process. Pawe J. Szab owski

EDRP lecture 7. Poisson process. Pawe J. Szab owski EDRP lecture 7. Poisson process. Pawe J. Szab owski 2007 Counting process Random process fn t ; t 0g is called a counting process, if N t is equal total number of events that have happened up to moment

More information

BRANCHING PROCESSES AND THEIR APPLICATIONS: Lecture 15: Crump-Mode-Jagers processes and queueing systems with processor sharing

BRANCHING PROCESSES AND THEIR APPLICATIONS: Lecture 15: Crump-Mode-Jagers processes and queueing systems with processor sharing BRANCHING PROCESSES AND THEIR APPLICATIONS: Lecture 5: Crump-Mode-Jagers processes and queueing systems with processor sharing June 7, 5 Crump-Mode-Jagers process counted by random characteristics We give

More information

4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n, h r th ff r d nd

4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n, h r th ff r d nd n r t d n 20 20 0 : 0 T P bl D n, l d t z d http:.h th tr t. r pd l 4 4 N v b r t, 20 xpr n f th ll f th p p l t n p pr d. H ndr d nd th nd f t v L th n n f th pr v n f V ln, r dn nd l r thr n nt pr n,

More information

88 N L Lö. r : n, d p t. B, DBB 644 6, RD., D z. 0, DBB 4 8 z h. D z : b n, v tt, b t b n r, p d, t n t. B, BB z. 0, DBB 4 8 z D. t n F hl r ff, nn R,

88 N L Lö. r : n, d p t. B, DBB 644 6, RD., D z. 0, DBB 4 8 z h. D z : b n, v tt, b t b n r, p d, t n t. B, BB z. 0, DBB 4 8 z D. t n F hl r ff, nn R, L x l h z ll n. V n n l Lö.. nn.. L RD h t t 40 für n r ( n r. B r 22, bb b 8 h r t llt. D nd t n rd d r h L länz nd b tät t: r b r ht t, d L x x n ht n r h nd hr ftl h b z t, nd rn h d r h ündl h h ltr

More information

! J*UC4j u<s.< U l*4 3) U /r b A a ti ex Ou rta + s U fa* V. H lu< Y ^i«iy /( c * i U O rti^ ^ fx /i«w

! J*UC4j u<s.< U l*4 3) U /r b A a ti ex Ou rta + s U fa* V. H lu< Y ^i«iy /( c * i U O rti^ ^ fx /i«w p ) X 6 @ / [ j t [ l C ^ h u M q f» -» - * / ---- ---------------- ------ - Muuuka y Um tq/z/h*. Ik M tu ^ t j a s ^ #/ Jjfif*.! J*UC4j u

More information

EXAM 2, MATH 132 WEDNESDAY, OCTOBER 23, 2002

EXAM 2, MATH 132 WEDNESDAY, OCTOBER 23, 2002 EXAM 2, MATH 132 WEDNESDAY, OCTOBER 23, 2002 This examination has 20 multiple choice questions, and two essay questions. Please check it over and if you find it to be incomplete, notify the proctor. Do

More information

Housing Market Monitor

Housing Market Monitor M O O D Y È S A N A L Y T I C S H o u s i n g M a r k e t M o n i t o r I N C O R P O R A T I N G D A T A A S O F N O V E M B E R İ Ī Ĭ Ĭ E x e c u t i v e S u m m a r y E x e c u t i v e S u m m a r y

More information

Last 4 Digits of USC ID:

Last 4 Digits of USC ID: Chemistry 05 B Practice Exam Dr. Jessica Parr First Letter of last Name PLEASE PRINT YOUR NAME IN BLOCK LETTERS Name: Last 4 Digits of USC ID: Lab TA s Name: Question Points Score Grader 8 2 4 3 9 4 0

More information

J2 e-*= (27T)- 1 / 2 f V* 1 '»' 1 *»

J2 e-*= (27T)- 1 / 2 f V* 1 '»' 1 *» THE NORMAL APPROXIMATION TO THE POISSON DISTRIBUTION AND A PROOF OF A CONJECTURE OF RAMANUJAN 1 TSENG TUNG CHENG 1. Summary. The Poisson distribution with parameter X is given by (1.1) F(x) = 23 p r where

More information

22 t b r 2, 20 h r, th xp t d bl n nd t fr th b rd r t t. f r r z r t l n l th h r t rl T l t n b rd n n l h d, nd n nh rd f pp t t f r n. H v v d n f

22 t b r 2, 20 h r, th xp t d bl n nd t fr th b rd r t t. f r r z r t l n l th h r t rl T l t n b rd n n l h d, nd n nh rd f pp t t f r n. H v v d n f n r t d n 20 2 : 6 T P bl D n, l d t z d http:.h th tr t. r pd l 22 t b r 2, 20 h r, th xp t d bl n nd t fr th b rd r t t. f r r z r t l n l th h r t rl T l t n b rd n n l h d, nd n nh rd f pp t t f r

More information

46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l pp n nt n th

46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l pp n nt n th n r t d n 20 0 : T P bl D n, l d t z d http:.h th tr t. r pd l 46 D b r 4, 20 : p t n f r n b P l h tr p, pl t z r f r n. nd n th t n t d f t n th tr ht r t b f l n t, nd th ff r n b ttl t th r p rf l

More information

RELATIVE CONTROLLABILITY OF NONLINEAR SYSTEMS WITH TIME VARYING DELAYS IN CONTROL

RELATIVE CONTROLLABILITY OF NONLINEAR SYSTEMS WITH TIME VARYING DELAYS IN CONTROL KYBERNETIKA- VOLUME 21 (1985), NUMBER 1 RELATIVE CONTROLLABILITY OF NONLINEAR SYSTEMS WITH TIME VARYING DELAYS IN CONTROL K. BALACHANDRAN, D. SOMASUNDARAM Using the measure of noncompactness of a set and

More information

A Quantum Particle Undergoing Continuous Observation

A Quantum Particle Undergoing Continuous Observation A Quantum Particle Undergoing Continuous Observation V.P. Belavkin and P. Staszewski y December 1988 Published in: Physics Letters A, 140 (1989) No 7,8, pp 359 {362 Abstract A stochastic model for the

More information

3.2 Complex Sinusoids and Frequency Response of LTI Systems

3.2 Complex Sinusoids and Frequency Response of LTI Systems 3. Introduction. A signal can be represented as a weighted superposition of complex sinusoids. x(t) or x[n]. LTI system: LTI System Output = A weighted superposition of the system response to each complex

More information

Interpolation. Chapter Interpolation. 7.2 Existence, Uniqueness and conditioning

Interpolation. Chapter Interpolation. 7.2 Existence, Uniqueness and conditioning 76 Chapter 7 Interpolation 7.1 Interpolation Definition 7.1.1. Interpolation of a given function f defined on an interval [a,b] by a polynomial p: Given a set of specified points {(t i,y i } n with {t

More information

MPM 2D Final Exam Prep 2, June b) Y = 2(x + 1)2-18. ~..: 2. (xl- 1:'}")( t J') -' ( B. vi::: 2 ~ 1-'+ 4 1<. -t-:2 -( 6! '.

MPM 2D Final Exam Prep 2, June b) Y = 2(x + 1)2-18. ~..: 2. (xl- 1:'})( t J') -' ( B. vi::: 2 ~ 1-'+ 4 1<. -t-:2 -( 6! '. MPM 2D Final Exam Prep 2 June 2017 1. Express each equation in standard form and factored form: ~ ~ +et's 'leu t W (.. ".>tak( a) y = (x + 5)2 + 1 on ::t~'t.{1'" ~heeh v 1' K 1 C'. T.) '. (J. lr lov J

More information

SPACES OF MATRICES WITH SEVERAL ZERO EIGENVALUES

SPACES OF MATRICES WITH SEVERAL ZERO EIGENVALUES SPACES OF MATRICES WITH SEVERAL ZERO EIGENVALUES M. D. ATKINSON Let V be an w-dimensional vector space over some field F, \F\ ^ n, and let SC be a space of linear mappings from V into itself {SC ^ Horn

More information

IMPROVEMENT OF AN APPROXIMATE SET OF LATENT ROOTS AND MODAL COLUMNS OF A MATRIX BY METHODS AKIN TO THOSE OF CLASSICAL PERTURBATION THEORY

IMPROVEMENT OF AN APPROXIMATE SET OF LATENT ROOTS AND MODAL COLUMNS OF A MATRIX BY METHODS AKIN TO THOSE OF CLASSICAL PERTURBATION THEORY IMPROVEMENT OF AN APPROXIMATE SET OF LATENT ROOTS AND MODAL COLUMNS OF A MATRIX BY METHODS AKIN TO THOSE OF CLASSICAL PERTURBATION THEORY By H. A. JAHN {University of Birmingham) [Received 7 October 947]

More information

02/05/09 Last 4 Digits of USC ID: Dr. Jessica Parr

02/05/09 Last 4 Digits of USC ID: Dr. Jessica Parr Chemistry 05 B First Letter of PLEASE PRINT YOUR NAME IN BLOCK LETTERS Exam last Name Name: 02/05/09 Last 4 Digits of USC ID: Dr. Jessica Parr Lab TA s Name: Question Points Score Grader 2 2 9 3 9 4 2

More information

Properties of the Autocorrelation Function

Properties of the Autocorrelation Function Properties of the Autocorrelation Function I The autocorrelation function of a (real-valued) random process satisfies the following properties: 1. R X (t, t) 0 2. R X (t, u) =R X (u, t) (symmetry) 3. R

More information

Solutions to the recurrence relation u n+1 = v n+1 + u n v n in terms of Bell polynomials

Solutions to the recurrence relation u n+1 = v n+1 + u n v n in terms of Bell polynomials Volume 31, N. 2, pp. 245 258, 2012 Copyright 2012 SBMAC ISSN 0101-8205 / ISSN 1807-0302 (Online) www.scielo.br/cam Solutions to the recurrence relation u n+1 = v n+1 + u n v n in terms of Bell polynomials

More information

ON RESTRICTED SYSTEMS OF HIGHER INDETERMINATE EQUATIONS * E. T. BELL

ON RESTRICTED SYSTEMS OF HIGHER INDETERMINATE EQUATIONS * E. T. BELL ON RESTRICTED SYSTEMS OF HIGHER INDETERMINATE EQUATIONS * BY E. T. BELL By two examples we shall illustrate a means for deriving arithmetical properties of certain restricted forms. So little being known

More information

ON THE DIVERGENCE OF FOURIER SERIES

ON THE DIVERGENCE OF FOURIER SERIES ON THE DIVERGENCE OF FOURIER SERIES RICHARD P. GOSSELIN1 1. By a well known theorem of Kolmogoroff there is a function whose Fourier series diverges almost everywhere. Actually, Kolmogoroff's proof was

More information

MA CALCULUS. Marking Scheme

MA CALCULUS. Marking Scheme MA 05 - CALCULUS Midsemester Examination (Autumn 06-07) Marking Scheme Department of Mathematics, I.I.T. Bombay. Max. Marks: 30 Time: 5:00 to 7:00 PM Date: 06/09/06 Q. (i) Show that lim n n /n exists and

More information

MATH 251 Examination II April 3, 2017 FORM A. Name: Student Number: Section:

MATH 251 Examination II April 3, 2017 FORM A. Name: Student Number: Section: MATH 251 Examination II April 3, 2017 FORM A Name: Student Number: Section: This exam has 12 questions for a total of 100 points. In order to obtain full credit for partial credit problems, all work must

More information

< < or a. * or c w u. "* \, w * r? ««m * * Z * < -4 * if # * « * W * <r? # *» */>* - 2r 2 * j j. # w O <» x <» V X * M <2 * * * *

< < or a. * or c w u. * \, w * r? ««m * * Z * < -4 * if # * « * W * <r? # *» */>* - 2r 2 * j j. # w O <» x <» V X * M <2 * * * * - W # a a 2T. mj 5 a a s " V l UJ a > M tf U > n &. at M- ~ a f ^ 3 T N - H f Ml fn -> M - M. a w ma a Z a ~ - «2-5 - J «a -J -J Uk. D tm -5. U U # f # -J «vfl \ \ Q f\ \ y; - z «w W ^ z ~ ~ / 5 - - ^

More information

828.^ 2 F r, Br n, nd t h. n, v n lth h th n l nd h d n r d t n v l l n th f v r x t p th l ft. n ll n n n f lt ll th t p n nt r f d pp nt nt nd, th t

828.^ 2 F r, Br n, nd t h. n, v n lth h th n l nd h d n r d t n v l l n th f v r x t p th l ft. n ll n n n f lt ll th t p n nt r f d pp nt nt nd, th t 2Â F b. Th h ph rd l nd r. l X. TH H PH RD L ND R. L X. F r, Br n, nd t h. B th ttr h ph rd. n th l f p t r l l nd, t t d t, n n t n, nt r rl r th n th n r l t f th f th th r l, nd d r b t t f nn r r pr

More information

Stochastic Processes

Stochastic Processes Introduction and Techniques Lecture 4 in Financial Mathematics UiO-STK4510 Autumn 2015 Teacher: S. Ortiz-Latorre Stochastic Processes 1 Stochastic Processes De nition 1 Let (E; E) be a measurable space

More information

MATH 241 Practice Second Midterm Exam - Fall 2012

MATH 241 Practice Second Midterm Exam - Fall 2012 MATH 41 Practice Second Midterm Exam - Fall 1 1. Let f(x = { 1 x for x 1 for 1 x (a Compute the Fourier sine series of f(x. The Fourier sine series is b n sin where b n = f(x sin dx = 1 = (1 x cos = 4

More information

h : sh +i F J a n W i m +i F D eh, 1 ; 5 i A cl m i n i sh» si N «q a : 1? ek ser P t r \. e a & im a n alaa p ( M Scanned by CamScanner

h : sh +i F J a n W i m +i F D eh, 1 ; 5 i A cl m i n i sh» si N «q a : 1? ek ser P t r \. e a & im a n alaa p ( M Scanned by CamScanner m m i s t r * j i ega>x I Bi 5 n ì r s w «s m I L nk r n A F o n n l 5 o 5 i n l D eh 1 ; 5 i A cl m i n i sh» si N «q a : 1? { D v i H R o s c q \ l o o m ( t 9 8 6) im a n alaa p ( M n h k Em l A ma

More information

ENGIN 211, Engineering Math. Laplace Transforms

ENGIN 211, Engineering Math. Laplace Transforms ENGIN 211, Engineering Math Laplace Transforms 1 Why Laplace Transform? Laplace transform converts a function in the time domain to its frequency domain. It is a powerful, systematic method in solving

More information

*^ irart ^r" -^irt" n'"" 8 "!^' 'if* 4 "^1* 0 f^* *>(""!.'»' *? 1? *}' ';' *l g r. (p 'n't inn*? ^ iff*"* 0 (2) (f) Jf5n**" in?*'*?

*^ irart ^r -^irt n' 8 !^' 'if* 4 ^1* 0 f^* *>(!.'»' *? 1? *}' ';' *l g r. (p 'n't inn*? ^ iff** 0 (2) (f) Jf5n** in?*'*? I Jf5n**" in?*'*? rr^-rf rrr *r (f) (2) (p 'n't inn*? ^ iff*"* 0 1? *}' ';' *l g r *^ irart ^r" -^irt" n'"" 8 "!^' 'if* 4 "^1* 0 f^* *>(""!.'»' *? 32 3JU1 J.» JJI ^^ Jl Uil^ilft!*_* ju.1 35 JL..a^bf t^m^f

More information

ON THE HARMONIC SUMMABILITY OF DOUBLE FOURIER SERIES P. L. SHARMA

ON THE HARMONIC SUMMABILITY OF DOUBLE FOURIER SERIES P. L. SHARMA ON THE HARMONIC SUMMABILITY OF DOUBLE FOURIER SERIES P. L. SHARMA 1. Suppose that the function f(u, v) is integrable in the sense of Lebesgue, over the square ( ir, ir; it, it) and is periodic with period

More information

Large Deviations for Perturbed Reflected Diffusion Processes

Large Deviations for Perturbed Reflected Diffusion Processes Large Deviations for Perturbed Reflected Diffusion Processes Lijun Bo & Tusheng Zhang First version: 31 January 28 Research Report No. 4, 28, Probability and Statistics Group School of Mathematics, The

More information

Oscillation by Impulses for a Second-Order Delay Differential Equation

Oscillation by Impulses for a Second-Order Delay Differential Equation PERGAMON Computers and Mathematics with Applications 0 (2006 0 www.elsevier.com/locate/camwa Oscillation by Impulses for a Second-Order Delay Differential Equation L. P. Gimenes and M. Federson Departamento

More information

n»i \ v f(x + h)-f(x-h)

n»i \ v f(x + h)-f(x-h) PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 72, Number 2, November 1978 SYMMETRIC AND ORDINARY DIFFERENTIATION C. L. BELNA, M. J. EVANS AND P. D. HUMKE Abstract. In 1927, A. Khintchine proved

More information

2 2 + x =

2 2 + x = Lecture 30: Power series A Power Series is a series of the form c n = c 0 + c 1 x + c x + c 3 x 3 +... where x is a variable, the c n s are constants called the coefficients of the series. n = 1 + x +

More information

41903: Introduction to Nonparametrics

41903: Introduction to Nonparametrics 41903: Notes 5 Introduction Nonparametrics fundamentally about fitting flexible models: want model that is flexible enough to accommodate important patterns but not so flexible it overspecializes to specific

More information

THE MAXIMUM OF SUMS OF STABLE RANDOM VARIABLES

THE MAXIMUM OF SUMS OF STABLE RANDOM VARIABLES THE MAXIMUM OF SUMS OF STABLE RANDOM VARIABLES BY D. A. DARLING(') 1. Introduction. Let Xu X2, be identically distributed independent random variables and set Sn=Xi+ +X. In this paper we obtain the limiting

More information

Oil'll. 't Or) [xdl^i^, CtJiMr^ ~t x. tbu to#*a) rf. 3*^^1IlSr>' r e u <i^-^j O. , y r v u \ r t o < x * ^ v t a ^ c? ] % & y^lcji-*'**'* (» &>~r~

Oil'll. 't Or) [xdl^i^, CtJiMr^ ~t x. tbu to#*a) rf. 3*^^1IlSr>' r e u <i^-^j O. , y r v u \ r t o < x * ^ v t a ^ c? ] % & y^lcji-*'**'* (» &>~r~ Oil'll A l r x a t i i i r a B r a l l t f ( E m m t t t t t w. / P.O. Box 2, B e r g v l e i. D i s t r i c t J o h a n n e s b u r g. Ph o n e 4 5-2 4 6 9. R e f. N o. A I ( * J - i i ^ c J,,, JOHANNESBURG.

More information

P(I -ni < an for all n > in) = 1 - Pm# 1

P(I -ni < an for all n > in) = 1 - Pm# 1 ITERATED LOGARITHM INEQUALITIES* By D. A. DARLING AND HERBERT ROBBINS UNIVERSITY OF CALIFORNIA, BERKELEY Communicated by J. Neyman, March 10, 1967 1. Introduction.-Let x,x1,x2,... be a sequence of independent,

More information

ON EQUIVALENCE OF ANALYTIC FUNCTIONS TO RATIONAL REGULAR FUNCTIONS

ON EQUIVALENCE OF ANALYTIC FUNCTIONS TO RATIONAL REGULAR FUNCTIONS J. Austral. Math. Soc. (Series A) 43 (1987), 279-286 ON EQUIVALENCE OF ANALYTIC FUNCTIONS TO RATIONAL REGULAR FUNCTIONS WOJC3ECH KUCHARZ (Received 15 April 1986) Communicated by J. H. Rubinstein Abstract

More information

Multiple points of the Brownian sheet in critical dimensions

Multiple points of the Brownian sheet in critical dimensions Multiple points of the Brownian sheet in critical dimensions Robert C. Dalang Ecole Polytechnique Fédérale de Lausanne Based on joint work with: Carl Mueller Multiple points of the Brownian sheet in critical

More information

Unconstrained minimization of smooth functions

Unconstrained minimization of smooth functions Unconstrained minimization of smooth functions We want to solve min x R N f(x), where f is convex. In this section, we will assume that f is differentiable (so its gradient exists at every point), and

More information

Some Integrals Involving Associated Legendre Functions

Some Integrals Involving Associated Legendre Functions MATHEMATICS OF COMPUTATION, VOLUME 28, NUMBER 125, JANUARY, 1974 Some Integrals Involving Associated Legendre Functions By S. N. Samaddar Abstract. Calculations of some uncommon integrals involving Legendre

More information

ON THE OSCILLATION OF DIFFERENTIAL EQUATIONS WITH PERIODIC COEFFICIENTS

ON THE OSCILLATION OF DIFFERENTIAL EQUATIONS WITH PERIODIC COEFFICIENTS proceedings of the aerican atheatical society Volue 111, Nuber 2, February 1991 ON THE OSCILLATION OF DIFFERENTIAL EQUATIONS WITH PERIODIC COEFFICIENTS CH. G. PHILOS (Counicated by Kenneth R. Meyer) Abstract.

More information

MAC 1147 Final Exam Review

MAC 1147 Final Exam Review MAC 1147 Final Exam Review nstructions: The final exam will consist of 15 questions plu::; a bonus problem. Some questions will have multiple parts and others will not. Some questions will be multiple

More information

Calculations of Integrals of Products of Bessel Functions

Calculations of Integrals of Products of Bessel Functions Calculations of Integrals of Products of Bessel Functions By J. E. Kilpatrick,1 Shigetoshi Katsura2 and Yuji Inoue3 I. Introduction. Integrals of products of Bessel functions are of general interest. Define

More information

Lecture 2: Review of Prerequisites. Table of contents

Lecture 2: Review of Prerequisites. Table of contents Math 348 Fall 217 Lecture 2: Review of Prerequisites Disclaimer. As we have a textbook, this lecture note is for guidance and supplement only. It should not be relied on when preparing for exams. In this

More information

ADVANCED PROBLEMS AND SOLUTIONS Edited by RAYMOND E.WHITNEY Lock Haven State College, Lock Haven, Pennsylvania

ADVANCED PROBLEMS AND SOLUTIONS Edited by RAYMOND E.WHITNEY Lock Haven State College, Lock Haven, Pennsylvania ADVANCED PROBLEMS AND SOLUTIONS Edited by RAYMOND E.WHITNEY Lock Haven State College, Lock Haven, Pennsylvania Send all communications concerning Advanced Problems and Solutions to Raymond E. Whitney,

More information

We are already familiar with the concept of a scalar and vector. are unit vectors in the x and y directions respectively with

We are already familiar with the concept of a scalar and vector. are unit vectors in the x and y directions respectively with Math Review We are already familiar with the concept of a scalar and vector. Example: Position (x, y) in two dimensions 1 2 2 2 s ( x y ) where s is the length of x ( xy, ) xi yj And i, j ii 1 j j 1 i

More information

Warm-up: What is the Laplace transform of f(t) = e^{-t} cos(3t)? We could do this by writing it as (1/2)( e^{(-1+3i)t} + e^{(-1-3i)t} )

Warm-up: What is the Laplace transform of f(t) = e^{-t} cos(3t)? We could do this by writing it as (1/2)( e^{(-1+3i)t} + e^{(-1-3i)t} ) 18.03 Class 27, April 12, 2010 Laplace Transform II 1. Delta signal 2. t-derivative rule 3. Inverse transform 4. Unit impulse response 5. Partial fractions 6. L[f'_r] Laplace Transform: F(s) = int_0^\infty

More information

~,. :'lr. H ~ j. l' ", ...,~l. 0 '" ~ bl '!; 1'1. :<! f'~.., I,," r: t,... r':l G. t r,. 1'1 [<, ."" f'" 1n. t.1 ~- n I'>' 1:1 , I. <1 ~'..

~,. :'lr. H ~ j. l' , ...,~l. 0 ' ~ bl '!; 1'1. :<! f'~.., I,, r: t,... r':l G. t r,. 1'1 [<, . f' 1n. t.1 ~- n I'>' 1:1 , I. <1 ~'.. ,, 'l t (.) :;,/.I I n ri' ' r l ' rt ( n :' (I : d! n t, :?rj I),.. fl.),. f!..,,., til, ID f-i... j I. 't' r' t II!:t () (l r El,, (fl lj J4 ([) f., () :. -,,.,.I :i l:'!, :I J.A.. t,.. p, - ' I I I

More information

5 questions, 3 points each, 15 points total possible. 26 Fe Cu Ni Co Pd Ag Ru 101.

5 questions, 3 points each, 15 points total possible. 26 Fe Cu Ni Co Pd Ag Ru 101. Physical Chemistry II Lab CHEM 4644 spring 2017 final exam KEY 5 questions, 3 points each, 15 points total possible h = 6.626 10-34 J s c = 3.00 10 8 m/s 1 GHz = 10 9 s -1. B= h 8π 2 I ν= 1 2 π k μ 6 P

More information

1 Continuation of solutions

1 Continuation of solutions Math 175 Honors ODE I Spring 13 Notes 4 1 Continuation of solutions Theorem 1 in the previous notes states that a solution to y = f (t; y) (1) y () = () exists on a closed interval [ h; h] ; under certain

More information

arxiv: v1 [math.ds] 24 Jul 2011

arxiv: v1 [math.ds] 24 Jul 2011 Simple Spectrum for Tensor Products of Mixing Map Powers V.V. Ryzhikov arxiv:1107.4745v1 [math.ds] 24 Jul 2011 1 Introduction June 28, 2018 In this note we consider measure-preserving transformations of

More information

UCLA Math 135, Winter 2015 Ordinary Differential Equations

UCLA Math 135, Winter 2015 Ordinary Differential Equations UCLA Math 135, Winter 2015 Ordinary Differential Equations C. David Levermore Department of Mathematics University of Maryland January 5, 2015 Contents 1.1. Normal Forms and Solutions 1.2. Initial-Value

More information

Trade Patterns, Production networks, and Trade and employment in the Asia-US region

Trade Patterns, Production networks, and Trade and employment in the Asia-US region Trade Patterns, Production networks, and Trade and employment in the Asia-U region atoshi Inomata Institute of Developing Economies ETRO Development of cross-national production linkages, 1985-2005 1985

More information

SQUARE FUNCTIONS IN BANACH SPACES

SQUARE FUNCTIONS IN BANACH SPACES 177 SQUARE FUNCTIONS IN BANACH SPACES Michael Cowling 1. INTRODUCTION ( JR+) Suppose that T t : t E is a bounded semigroup of operators on the Banach space X, of type c 0, with infinitesimal generator

More information

Integrated II: Unit 2 Study Guide 2. Find the value of s. (s - 2) 2 = 200. ~ :-!:[Uost. ~-~::~~n. '!JJori. s: ~ &:Ll()J~

Integrated II: Unit 2 Study Guide 2. Find the value of s. (s - 2) 2 = 200. ~ :-!:[Uost. ~-~::~~n. '!JJori. s: ~ &:Ll()J~ Name: 1. Find the value of r., (r + 4) 2 = 48 4_ {1 1:. r l f 11i),_ == :r (t~ : t %J3 (t:; KL\J5 ~ ~ v~~f3] ntegrated : Unit 2 Study Guide 2. Find the value of s. (s 2) 2 = 200 ~ :!:[Uost ~~::~~n '!JJori

More information

Practice Problems for Exam 3 (Solutions) 1. Let F(x, y) = xyi+(y 3x)j, and let C be the curve r(t) = ti+(3t t 2 )j for 0 t 2. Compute F dr.

Practice Problems for Exam 3 (Solutions) 1. Let F(x, y) = xyi+(y 3x)j, and let C be the curve r(t) = ti+(3t t 2 )j for 0 t 2. Compute F dr. 1. Let F(x, y) xyi+(y 3x)j, and let be the curve r(t) ti+(3t t 2 )j for t 2. ompute F dr. Solution. F dr b a 2 2 F(r(t)) r (t) dt t(3t t 2 ), 3t t 2 3t 1, 3 2t dt t 3 dt 1 2 4 t4 4. 2. Evaluate the line

More information

Labor and Capital Before the Law

Labor and Capital Before the Law University of Michigan Law School University of Michigan Law School Scholarship Repository Articles Faculty Scholarship 1884 Labor and Capital Before the Law Thomas M. Cooley University of Michigan Law

More information

ON THE NUMBER OF POSITIVE SUMS OF INDEPENDENT RANDOM VARIABLES

ON THE NUMBER OF POSITIVE SUMS OF INDEPENDENT RANDOM VARIABLES ON THE NUMBER OF POSITIVE SUMS OF INDEPENDENT RANDOM VARIABLES P. ERDÖS AND M. KAC 1 1. Introduction. In a recent paper 2 the authors have introduced a method for proving certain limit theorems of the

More information

Ulam Quaterly { Volume 2, Number 4, with Convergence Rate for Bilinear. Omar Zane. University of Kansas. Department of Mathematics

Ulam Quaterly { Volume 2, Number 4, with Convergence Rate for Bilinear. Omar Zane. University of Kansas. Department of Mathematics Ulam Quaterly { Volume 2, Number 4, 1994 Identication of Parameters with Convergence Rate for Bilinear Stochastic Dierential Equations Omar Zane University of Kansas Department of Mathematics Lawrence,

More information

THE POISSON TRANSFORM^)

THE POISSON TRANSFORM^) THE POISSON TRANSFORM^) BY HARRY POLLARD The Poisson transform is defined by the equation (1) /(*)=- /" / MO- T J _M 1 + (X t)2 It is assumed that a is of bounded variation in each finite interval, and

More information

Maximum Likelihood Drift Estimation for Gaussian Process with Stationary Increments

Maximum Likelihood Drift Estimation for Gaussian Process with Stationary Increments Austrian Journal of Statistics April 27, Volume 46, 67 78. AJS http://www.ajs.or.at/ doi:.773/ajs.v46i3-4.672 Maximum Likelihood Drift Estimation for Gaussian Process with Stationary Increments Yuliya

More information

F. R. K. CHUNG AND R. L. GRAHAM. Bell Laboratories, Mupray Hill, New Jersey Communicated by the Managing Editors

F. R. K. CHUNG AND R. L. GRAHAM. Bell Laboratories, Mupray Hill, New Jersey Communicated by the Managing Editors JOURNAL OF COMBINATORIAL THEORY, Series B 24, 14-23 (1978) On Graphs which Contain Ail Small Trees F. R. K. CHUNG AND R. L. GRAHAM Bell Laboratories, Mupray Hill, New Jersey 07974 Communicated by the Managing

More information

ON MIXING AND PARTIAL MIXING

ON MIXING AND PARTIAL MIXING ON MIXING AND PARTIAL MIXING BY N. A. XRIEDMAN AND D. S. ORNSTEIN 1. Introduction Let (X, a, m) denote the unit interwl with Lebesgue mesure, nd let r be n invertible ergodie mesure preserving transformation

More information

W I T H M i A. L I O E T O W A R D ISTOlNrE ^ I S T D C H A. n i T Y F O R - A L L. "

W I T H M i A. L I O E T O W A R D ISTOlNrE ^ I S T D C H A. n i T Y F O R - A L L. J/ H L D N D H Y F L L L N LLL KN NY H Y 2 95 HL N NG F L G NG F LNDD H H J F NH D K GN L _ L L :? H F K b H Y L DD Y N? N L L LD H LL LLL LNNG LL J K N 3 ND DL6 N Lb L F KF FH D LD3 D ND ND F ND LKKN

More information

MATH 251 Examination II April 4, 2016 FORM A. Name: Student Number: Section:

MATH 251 Examination II April 4, 2016 FORM A. Name: Student Number: Section: MATH 251 Examination II April 4, 2016 FORM A Name: Student Number: Section: This exam has 12 questions for a total of 100 points. In order to obtain full credit for partial credit problems, all work must

More information

Sequential Investment, Universal Portfolio Algos and Log-loss

Sequential Investment, Universal Portfolio Algos and Log-loss 1/37 Sequential Investment, Universal Portfolio Algos and Log-loss Chaitanya Ryali, ECE UCSD March 3, 2014 Table of contents 2/37 1 2 3 4 Definitions and Notations 3/37 A market vector x = {x 1,x 2,...,x

More information

I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o

I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o I M P O R T A N T S A F E T Y I N S T R U C T I O N S W h e n u s i n g t h i s e l e c t r o n i c d e v i c e, b a s i c p r e c a u t i o n s s h o u l d a l w a y s b e t a k e n, i n c l u d f o l

More information

Chemistry 2 Exam Roane State Academic Festival. Name (print neatly) School

Chemistry 2 Exam Roane State Academic Festival. Name (print neatly) School Name (print neatly) School There are fifteen question on this exam. Each question is weighted equally. n the answer sheet, write your name in the space provided and your answers in the blanks provided.

More information

Laplace Transform Problems

Laplace Transform Problems AP Calculus BC Name: Laplace Transformation Day 3 2 January 206 Laplace Transform Problems Example problems using the Laplace Transform.. Solve the differential equation y! y = e t, with the initial value

More information

Oi ir\ o CM CM ! * - CM T. c *" H - VO - a CM - t - T - j. Vv VO r t- CO on *- t- «- - ** <* - CM CM CM b- f - on on. on CM CVJ t - o.

Oi ir\ o CM CM ! * - CM T. c * H - VO - a CM - t - T - j. Vv VO r t- CO on *- t- «- - ** <* - CM CM CM b- f - on on. on CM CVJ t - o. 292 b» CJ «n :T * v j U n n C l * n t l f VL. n n W n V ' n Ln fv C ), C n e. t f *" T V n! * t t T j t Vv V t l / n * t «** n Pk Q * Ph t * b T~! ^ v n f n n N n T n l f P n t. n pn «n =f LPv j t t n

More information