Computing the Laplace transform and the convolution for more functions adjoined
|
|
- Alexander Sims
- 5 years ago
- Views:
Transcription
1 CUBO A Mathematical Journal Vol.17, N ō 3, (71 9). October 15 Computing the Laplace transform and the convolution for more functions adjoined Takahiro Sudo Department of Mathematical Sciences, Faculty of Science, University of the Ryukyus, Senbaru 1, Nishihara, Okinawa 93-13, Japan. sudo@math.u-ryukyu.ac.jp ABSTRACT We compute explicitly the Laplace transform and the convolution for more functions on the real than the continuous functions that obtained as the inverse Laplace transforms of rational functions on the complex plane vanishing at infinity. We also consider the algebraic structure with more functions adjoined. RESUMEN Calculamos explícitamente la transformada de Laplace y la convolución para más funciones en los reales que las funciones continuas obtenidas como transformadas de Laplace inversas de funciones racionales en el plano complejo que se anulan en el infinito. También consideramos la estructura algebraica con más funciones adjuntadas. Keywords and Phrases: Laplace tranform, Gaussian function, Dirac delta function, convolution. 1 AMS Mathematics Subject Classification: 44A1, 44A35, 6C15, 6A6, 6A9.
2 7 Takahiro Sudo CUBO 1 Introduction 17, 3 (15) This paper is a continuation from the paper [3] of the author, in which we compute explicitly the inverse Laplace transform for rational functions on the complex plane vanishing at infinity and consider the algebraic structure for the corresponding algebra of continuous elementary functions on the real R for which the Laplace transform on the infinite interval [, ) is defined. In this paper, we compute explicitly the Laplace transform for more functions on the real than the continuous functions that obtained as the inverse Laplace transforms of rational functions on the complex plane vanishing at infinity. For this, we compute the convolution product with more functions adjoined, such as Gaussian functions, the Dirac delta functions, and the shifted delta functions. We also consider the algebraic structure with more functions adjoined. This paper after this introduction is organized as follows: Adjoining Gaussian functions; 3 Algebraic structure with Gaussian functions; 4 Adjoining the delta function; 5 Algebraic structure with the delta function; 6 Adjoining the shifted delta functions; 7 Algebraic structure with the shifted delta functions; 8 More with the weak derivative. Our elementary explicit computation results obtained and algebraic consideration results obtained should be useful as a reference. Refer to [4] or [] (or [1]) for some basics about the Laplace transform. Notation. We denote by A(R) the real algebra with convolution, generated by the three sets of elementary continuous functions on the real line R with t real variable: {t n n N = {, 1,, }} of monomials and {e µt µ R} of exponential functions based to e and {sin t, cos t R} of trigonometric functions and their point-wise multiples such as t n e µt sin t. The (extended in our sense) convolution product for A(R) (but the same as the usual one by restriction to [, )) is defined as the (Riemann) integral: f g =(f g)(t) = f(t τ)g(τ)dτ, (t R) for f, g A(R), which makes sense and is a commutative and associative operation as well known as the usual case on the interval [, ). Denote by C the complex plane. For f = f(t) a suitable function on R (as in A(R)), the (extended in our sense) Laplace transform of f (but the same as the usual one of f restricted to [, )) is defined by the (Riemann) integral: L(f(t)) = L(f(t))(s) = e st f(t)dt for s C (formally or in the domain of convergence).
3 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more Adjoining Gaussian functions Quite well known, but first of all we consider Gaussian functions as follows: Lemma.1. For t R, s C and R with >,wehave π L(e t )= e s 4, Proof. Check that e st e t = e (t+ s ) + s 4 and then L(e t )=e s 4 e (t+ s ) dt. Using change of variables and Cauchy s theorem, we obtain that the integral is computed to be equal to s + e u s + = 1 du with u = (t + s )) π e u du =. Lemma.. For t R, s C and, µ R positive, we have L(e t e µt )= π 4 µ e +µ 4µ s. We need to check the convolution explicitly as follows. Proposition 1. For t R and positive, ν R, 1 (e t e µt )(t) = e (1 + µ = e (1 +µ )t n= µt +µ +µ )t t +µ e u du n+1 + µ n+1 ( 1) n 1 ( + µ) n+1 n! n + 1 tn+1 Proof. We compute (e t e µt )(t) = e t t (+µ)(τ e +µ ) + t e (t τ) e µτ dτ = +µ dτ = e (1 +µ )t t (+µ)(τ e +µ ) dτ
4 74 Takahiro Sudo CUBO 17, 3 (15) with 1 +µ >, and the integral is computed by change of variables as: g(t) = t (+µ)(τ e +µ ) dτ µt 1 +µ + µ t +µ e u du with u = + µ(τ t + µ ). Using Taylor s expansion of e y we compute the integral above as: µt +µ t +µ ( 1) n n= µt e u +µ du = t +µ n! µt +µ ( 1) n u n du = n! n= u n du = t +µ ( 1) n µ n+1 + n+1 1 n! ( + µ) n+ 1 n + 1 tn+1. n= Corollary 1. The convolutions e t e µt for, µ positive reals are point-wise limits of elements of A(R). Proof. Note that any Gaussian functions are point-wise limits of elements of A(R) by Taylor series. Proposition. For R positive, n N, andt R, (1) (t n e t )= with I k τk e τ dτ given by and I k+1 = e t k l=1 I k = e t + n k= ( ) n t t n k ( 1) k τ k e τ dτ k (k)!! () l ((k l + 1))!! t(k l+1) + (k)!! () k+1 (1 ), e t k l=1 (k 1)!! () k (k 1)!! () l ((k l + 1) 1)!! t(k l+1) 1 m= Also, for µ R non-zero and R positive, () (e µt e t )=e µ 4 e µt n= ( ) m m!(m + 1) tm+1. ( 1) n n+ 1 n!(n + 1) {(t + µ )n+1 ( µ )n+1 }.
5 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more Also, for µ R non-zero and R positive, with (3) (sin µt e t )=sin µt cos µτe τ dτ = sin µτe τ dτ = cos µτe τ dτ cos µt ( ) n n= n= n! ( ) n n! τ n cos µτdτ, τ n sin µτdτ sin µτe τ dτ and each integral term is computed inductively as: and similarly, I c,n I s,n τ n cos µτdτ = 1 µ tn sin µt + n µ tn 1 cos µτ τ n sin µτdτ = 1 µ tn cos µt + n µ tn 1 sin µτ (4) (cos µt e t )=cos µt with the integrals the same as above. cos µτe τ dτ sin µt (n)(n 1) µ I c,n, (n)(n 1) µ I s,n, sin µτe τ dτ Proof. For (1) we compute (t n e t )(t) = (t τ) n e τ dτ = n k= ( ) n t t n k ( 1) k τ k e τ dτ k and the integral is computed by integration by parts as: { } 1 I k τ k e τ dτ = τ k 1 ) dτ (e τ = 1 tk 1 e t + k 1 I k
6 76 Takahiro Sudo CUBO 17, 3 (15) so that, inductively, I k+1 = 1 tk e t k(k ) 4 () k t e t + k k(k ) () tk e t () 3 t k 4 e t k(k ) () k I 1 with and with I 1 τe τ dτ = 1 (1 e t ), I k = 1 tk 1 e t k 1 () tk 3 e t (k 1)(k 3) 3 () k te t + I = m= e τ dτ = ( ) m m! m= (k 1)(k 3) () 3 (k 1)(k 3) 1 () k I ( ) m τ m dτ m! τ m dτ = m= ( ) m m!(m + 1) tm+1. t k 5 e t For () we compute e µt e t = e µ(t τ) e τ dτ = e µ 4 e µt e (τ+ µ ) dτ. By change of variables as u = (τ + µ ), the integral above is computed as = e (τ+ µ ) dτ = ( 1) n n= n! (t+ µ ) ( µ ) (t+ µ ) ( µ ) u n du = e u (t+ µ ) du = n= ( µ ) n= 1 n! ( u ) n du ( 1) n n+ 1 n!(n + 1) {(t + µ )n+1 ( µ )n+1 }. For (3) we next compute (sin µt e t )(t) = = sin µt sin µ(t τ)e t dτ cos µτe τ dτ cos µt sin µτe τ dτ,
7 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more and the first integral is computed as: cos µτe τ dτ = cos µτ n= and each integral term is computed inductively as: I c,n τ n cos µτdτ 1 n! ( τ ) n dτ = = 1 µ tn sin µt + n µ tn 1 cos µτ by using integration by parts. Similarly, we obtain and I s,n sin µτe τ dτ = τ n sin µτdτ ( ) n n= n! = 1 µ tn cos µt + n µ tn 1 sin µτ ( ) n n= n! (n)(n 1) µ I c,n τ n sin µτdτ τ n cos µτdτ (n)(n 1) µ I s,n. Remark. We omit the case of convolutions with general monomials such as multiples t n e µt sin µt, but which are certainly computable by the similar computation technique as above, with some more integration. Refer to [3]. 3 Algebraic structure with Gaussian functions We denote by A w (R) the set of all functions on R that are written as point-wise limits in R of elements of A(R). Lemma 3.1. A w (R) is an algebra over R with point-wise multiplication. algebra over R with convolution. Also, A w (R) is an Proof. Suppose that f, g A w (R) with f = lim f n, g = lim g n (n ) point-wise limits of f n,g n A w (R). Since the limits at any t R are finite, then and hence, f g A w (R). (f g)(t) =lim f n (t) lim g n (t) =lim(f n g n )(t) R,
8 78 Takahiro Sudo CUBO 17, 3 (15) Note also that we define the convolution of f, g A w (R) as f g = lim(f n g n ) A w (R), where it is shown in general ([3]) that A(R) is closed under convolution. This is well defined, because if f = lim h n and g = lim k n another limits with h n,k n A(R), and since the limits at any t R are finite, then (f n g n )(t) (h n k n )(t) =((f n f) g n )(t)+(f (g n g))(t) +((f h n ) g)(t)+(h n (g k n ))(t), and the right hand side goes to zero as n by applying the dominated convergence theorem to each convolution, and hence, lim(f n g n ) lim(h n k n ) lim(f n g n ) f n g n + f n g n h n k n + h n k n lim(h n k n ), which go to zero as n. We denote by G(R) the algebra generated by A(R) and the set {e t R, > }, with either point-wise multiplication or convolution as a product. Corollary. The algebra G(R) is contained in A w (R) and is a subalgebra of A w (R) with either point-wise multiplication or convolution. We denote by R (C) the algebra of rational functions on C vanishing at infinity with point-wise multiplication and by E(C) the algebra generated by both R (C) and the set {e s R, > } of inverse Gaussian functions on C with s complex variable. Corollary 3. The algebra G(R) with convolution is isomorphic to the algebra E(C) by the Laplace transform and by the inverse Laplace transform. Proof. Note that L(f g) =L(f) L(g) and L is injective for continuous functions on R. 4 Adjoining the delta function We consider the Dirac delta function. Define the delta function as δ(t) = lim g (t) lim π e t = { t = t with R positive. Note that the delta function has the meaning in integration only in the weak sense, i.e. as the weak limit of g (t) by taking the inner product or the convolution with test
9 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more functions, and the delta function is also viewed as a distribution, i.e., a functional (or a scalarvalued linear map) on the linear space of test functions. Also, one can take other functions of different types to define the delta function. Note that g (t)dt = but we need to have the next: Lemma 4.1. The functions g are in G(R), andfors C, which goes to 1 as. L(g )(s) =e s 4, Proof. Use Lemma.1. Lemma 4.. For s C, wehave which goes to 1 as and µ. L(g g µ )(s) =e (+µ)s 4µ, Proof. Use Lemma 4.1 and L(g g µ )=L(g ) L(g µ ). Proposition 3. For positive µ, R, (1) lim (e µt g )(t) = e µt if t>, if t =, e µt if t<; and for n N and >, and for µ R and >, () lim (tn g )(t) = (3) lim (eµt g )(t) = t n if t>, if t =, t n if t<; e µt if t>, if t =, if t<; e µt and for µ R and >, (4) lim (sin µt g )(t) = sin µt if t>, if t =, sin µt if t<;
10 8 Takahiro Sudo CUBO 17, 3 (15) and (5) lim (cos µt g )(t) = cos µt if t>, if t =, cos µt if t<. Proof. The first equation (1) follows from the first equation in Proposition 1 by taking the limit with respect to. For () we next use Proposition. It follows that lim (tn g )(t) = lim tn g (τ)dτ, namely, other terms in the convolution go to zero as,andthen which goes to g (τ)dτ = t 1 if t>, if t =, 1 if t<, π e u du as. (u = τ), For (3), it also follows as in parts of the proof of Proposition that (e µt g )(t) =e µ 4 e µt µ ) dτ = e µ 4 e µt π e (τ+ (t+ µ ) µ π e u du (u = (τ + µ )), which goes to e µt if t>, if t =, if t<, e µt as. For (4) we next compute by allowing complex coefficients for this case and using the Euler formula as: (sin µt g )(t) =( eµti e µti g )(t) i = 1 e µ(t τ)i g (τ)dτ 1 e µ(t τ)i g (τ)dτ i i = eµti i e µτi g (τ)dτ e µti i e µτi g (τ)dτ
11 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more and the first integral is converted to which goes to = e µ 4 µi π e (τ+ ) µ 4 dτ (t+ µi ) iµ e u du (u = (τ + µi π )) 1 if t>, if t =, 1 if t< as via Cauchy integral theorem. Similarly, the second integral above is converted to 4 dτ which goes to = e µ 4 µi π e (τ ) µ (t µi ) iµ e u du (u = (τ µi π )) 1 if t>, if t =, 1 if t< as. Therefore, we obtain one of the last two equations in the statement. The other case (5) is obtained similarly, by cos µt = eµti +e µti. 5 Algebraic structure with the delta function We denote by G δ (R) the algebra generated by G(R) and the delta function δ(t) with convolution, where we assume that f δ = f on [, ) for any f G(R) and δ δ = δ on [, ), which follows from our definition of the delta function in the weak sense, so that G δ (R) restricted to [, ) is isomorphic to the unitization of G(R) by R, restricted to [, ), as a real algebra. We define the Laplace transform for δ as the unit function on C. L(δ(t))(s) =1(s) Note that G δ (R) is also viewed as the generated by G(R) and the point-wise limit function of Gaussian functions on R. We denote by E 1 (C) the algebra generated by E(C) and the unit function 1 on C with pointwise multiplication.
12 8 Takahiro Sudo CUBO 17, 3 (15) Corollary 4. The algebra G δ (R) with convolution, restricted to [, ), is isomorphic to the algebra E 1 (C) by the Laplace transform and by the inverse Laplace transform. Remark. Our Proposition 3 says that the convolution f δ on R for f G δ (R) is defined as f(t) if t>, (f δ)(t) = if t =, f(t) if t<. 6 Adjoining the shifted delta functions It is also defined as that for t R and s C, L(δ(t µ)) = e µs for µ>. We extend this definition for µ R. Indeed,checkthat Lemma 6.1. We have for any µ R. lim L(g (t µ))(s) =e µs Proof. We compute L(g (t µ))(s) = e st π e (t µ) dt = e µs e s 4 e (t+ s µ) π dt and changing variables as u = (t + s u) and using Cauchy integral theorem and taking the limit as we obtain the result in the statement. Lemma 6.. We have lim L(g (t µ) g (t ρ))(s) =e (µ+ρ)s for any µ, ρ R. It follows by defining the left hand side to be equal to Proof. Note that L(δ(t µ) δ(t ρ))(s) =e (µ+ρ)s. L(g (t µ) g (t ρ))(s) =L(g (t µ))(s) L(g (t ρ))(s) and the both factors are computed in the proof of Lemma 6.1.
13 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more Proposition 4. For positive µ, R and ρ R, if ρ>,then e µ(t ρ) t>ρ, (1) + lim (e µt g (t ρ))(t) = 1 t = ρ, t < ρ, and if ρ<,then (1) lim (e µt g (t ρ))(t) = t > ρ, 1 t = ρ, t<ρ; e µ(t ρ) and for n N and ρ R, if ρ>,then and if ρ<,then and for µ R, if ρ>,then () + lim (tn g (t ρ))(t) = () lim (tn g (t ρ))(t) = (3) + lim (eµt g (t ρ))(t) = t n t>ρ, ρ n t = ρ, t < ρ, t > ρ, ρ n t = ρ, t n t<ρ; e µ(t ρ) if t>ρ, 1 if t = ρ, if t<ρ, and if ρ<,then (3) lim (eµt g (t ρ))(t) = if t>ρ, 1 if t = ρ, if t<ρ; e µ(t ρ) and for µ R, if ρ>,then and if ρ<,then (4) + lim (sin µt g (t ρ)(t) = (4) lim (sin µt g (t ρ)(t) = sin µ(t ρ) if t>ρ, if t = ρ, if t<ρ, if t>ρ, if t = ρ, sin µ(t ρ) if t<ρ;
14 84 Takahiro Sudo CUBO 17, 3 (15) and if ρ>,then and if ρ>,then (5) + lim (cos µt g (t ρ))(t) = (5) lim (cos µt g (t ρ))(t) = cos µ(t ρ) if t>ρ, 1 if t = ρ, if t<ρ, if t>ρ, 1 if t = ρ, cos µ(t ρ) if t<ρ. Proof. For (1) ± we compute (e µt g (t ρ))(t) = e π e (t τ ρ) µτ dτ = e µ +µ (t ρ) π e (+µ)(τ +µ(t (t ρ) = e µ +µ (t ρ) +µ ) (t ρ) +µ (t ρ) +µ ) dτ π( + µ) e u du where u = + µ(τ (t ρ) µt+ρ +µ ) and if τ = t, thenu =, which goes to as for ρ>. +µ If t>ρ,then (t ρ) +µ goes to and if t<ρ, then it goes to. Therefore, if ρ>,then lim g (e µt (t ρ))(t) = e µ(t ρ) t>ρ, 1 t = ρ, t < ρ, and if ρ<,then lim (e µt g (t ρ))(t) = t > ρ, 1 t = ρ, t<ρ, e µ(t ρ) For () ± we next compute (t n g (t ρ))(t) = n k= and the following integrals are converted as: τ k e (τ ρ) dτ = ( ) n t t n k ( 1) k τ k dρ k π e (τ ρ) (t ρ) ρ (ρ + u ) k e u du
15 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more where u = (τ ρ). We then use Proposition and it follows that if ρ>,then t n t>ρ, lim (tn g (t ρ))(t) = ρ n t = ρ, t < ρ, and if ρ<,then lim (tn g (t ρ))(t) = t > ρ, ρ n t = ρ, t n t<ρ. For (3) ± we next compute (e µt g (t ρ))(t) = e µ(t τ) dτ π e (τ ρ) = e µ 4ρµ 4 e µt π e (τ+ = e µ 4ρµ 4 e µt (t ρ+ µ ) µ ρ µ ρ ) dτ π e u du (u = (τ + µ ρ )), which goes to, if ρ>,then as, and if ρ<,then e µ(t ρ) if t>ρ, 1 if t = ρ, if t<ρ if t>ρ, 1 if t = ρ, if t<ρ. e µ(t ρ) For (4) ± we finally compute by allowing complex coefficients for this case and using the Euler formula as: (sin µt g (t ρ))(t) =( eµti e µti g (t ρ))(t) i = 1 e µ(t τ)i g (τ ρ)dτ 1 e µ(t τ)i g (τ ρ)dτ i i = eµti i e µτi g (τ ρ)dτ e µti i e µτi g (τ ρ)dτ
16 86 Takahiro Sudo CUBO 17, 3 (15) and the first integral is converted to µ ρµi e 4 µ ρµi = e 4 which goes to, if ρ>,then, µi π e (τ ρ+ (t ρ+ µi ) ( ρ+ µi ) ) dτ π e u du (u = (τ ρ + µi )) e ρµi if t>ρ, e ρµi if t = ρ, if t<ρ as via Cauchy integral theorem, and if ρ<,then, if t>ρ, e ρµi if t = ρ, e ρµi if t<ρ. Similarly, the second integral above is converted to have the similar limits as above, where e ρµi is replaced with e ρµi since u is replaced with u = (τ ρ µi ). Therefore, we obtain one of the last two equations in the statement. The other case (5) ± is obtained similarly, by cos µt = e µti +e µti. Remark. The Heaviside unit function u(t) on R is defined by u(t) =1 if t>and u(t) = if t<aswell as u() = 1. For ρ R positive, the shifted Heaviside unit function u(t ρ) is defined similarly. It is known that L(u(t ρ))(s) = e ρs. s We may extend the definition of u(t ρ) for ρ<. But we always have Note also that L 1 ( 1 s e ρs )= L(u(t ρ))(s) = 1 s, ρ. 1 δ(τ ρ)dτ = { 1 t > ρ, t < ρ, where note that this shifted delta function comes from the usual Gaussian functions, not equal to ours multiplied by.
17 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more Algebraic structure with the shifted delta functions We denote by G sδ (R) the algebra generated by G(R) and the shifted delta functions δ(t µ) for µ R, with convolution. For convenience, we define G sδ (R + ) to be the algebra generated by G δ (R) and the positive shifted delta functions δ(t µ) for µ>, restricted to [, ). We define the following convolution as (f δ(t µ))(t) =u(t µ)f(t µ) for f G sδ (R + ) and µ>,whereu(t µ) is the shifted Heaviside unit function on [, ). Note that this definition is not perfectly compatible with Proposition 4 but either changing g (t µ) with it multiplied by 1 on [, ) or cutting off functions to be zero on (,) make sense almost everywhere. In fact, such a scalar multiplication is allowed to define the convolution with the shifted delta functions in the weak sense. We denote by E s1 (C) the algebra generated by E 1 (C) and the set {e ρs ρ>}, with pointwise mulitiplication. We define the Laplace transform L(f g) to be L(f) L(g) for f, g G sδ (R + ). Note that it is known as the first shift law that and L(δ(t µ)) = e µs. L(u(t µ)f(t µ)) = e µs L(f)(s) Corollary 5. The algebra G sδ (R + ) with convolution is isomorphic to E s1 (C) with pointwise multiplication, as a real algebra, via the Laplace transform and the inverse Laplace transform. Proof. The Laplace transform L is injective on G δ (R). The injectiveness of L extends to G sδ (R) by definition. Also, G sδ (R + ) is mapped onto E s1 (C) by L as an algebra homomorphism, by definition. Note that, by definition, G sδ (R + ) contains discontinuous functions such as the shifted Heaviside unit functions. Lemma 7.1. For f, g G sδ (R + ) and for µ, s >, wehave (u(t µ)f(t µ) u(t s)g(t s))(t) { if t<µor t<s, = u f(t τ µ)g(τ s)dτ if t>µand t>s. s Note that in the second non-trivial case, the integral is just the sub-integral of (f(t µ) g(t s))(t) = f(t τ µ)g(τ s)dτ restricted to the sub-interval [s, t µ] of [, t], sothatwemay call the convolution in the statement the sub-convolution. Therefore,
18 88 Takahiro Sudo CUBO 17, 3 (15) Corollary 6. The convolution in G sδ (R + ) generates such sub-convolutions, which generate the algebra. Remark. However, the convolution product in G sδ (R + ) is somewhat difficult to see what it is, but the corresponding point-wise multiplication in E s1 (C) is relatively easy to see what it is. As well known in applications to solving ordinary differential equations with initial values, a problem related to G sδ (R + ) is relatively easily solved in E s1 (C) via the Laplace transform, and then the last task is to compute the corresponding convolution via the inverse Laplace transform. 8 More with the weak derivative Recall that Lemma 8.1. We have L(δ (t)) = s in the weak sense, i.e., as a functional or a distribution, so that we may definel 1 (s) =δ (t) for t R and s C. Proof. We compute L(δ (t)) = = e st δ (t)dt ( 1) t e st δ(t)dt = sl(δ(t)) = s. by definition Note that the algebra G(R) is closed under the usual derivative and that G(R) is contained in C (R) the algebra of all infinitely many times differentiable (or smooth) functions on R. Lemma 8.. For f G(R), wehave in the weak sense. Proof. We compute (f δ )(t) = = (f δ )(t) =f (t) f(t τ)δ (τ)dτ ( 1) τ f(t τ) δ(τ)dτ =(f δ)(t) =f (t).
19 CUBO 17, 3 (15) Computing the Laplace transform and the convolution for more We define the n-th derivative δ (n) to be the n-times convolution with δ. For f G(R), we define f δ (n) to be f (n) the n-th derivative of f. We also define L(δ (n) ) to be s n for s C. We denote by D A (R) the algebra generated by A(R), the delta function δ, and the set {δ (n) n Z,n 1}, with convolution. We also denote by R(C) the algebra of all rational functions on C with point-wise multiplication. Proposition 5. There is an algebra isomorphism by the Laplace transform from D A (R) to R(C). We denote by D G (R) the algebra defined by replacing A(R) with G(R) in the definition of D A (R). We also denote by R E (C) the algebra generated by R(C) and E(C). Proposition 6. There is an algebra isomorphism by the Laplace transform from D G (R) to R E (C). Lemma 8.3. For f G sδ (R + ) and µ>,wehave almost everywhere in the weak sense. (f δ (t µ))(t) =u(t µ)f (t) Proof. We compute (f δ (t µ))(t) = = f(t τ)δ (τ µ)dτ ( 1) τ f(t τ) δ(τ µ)dτ =(f δ(t µ))(t) = u(t µ)f (t) for f G sδ (R + ),wherenotethatf is defined almost everywhere (except some finite points of R + ). We denote by D G sδ(r + ) the algebra generated by G sδ (R + ) and the weak derivatives δ (n) (t µ) for n positive integers and µ>reals. We also denote by R E s1(c) the algebra generated by R(C) and E s1 (C). Proposition 7. There is an algebra isomorphism by the Laplace transform from D G sδ(r + ) to R E s1(c). Received: May 13. Accepted: May 13.
20 9 Takahiro Sudo CUBO 17, 3 (15) References [1] Hiroshi Fukawa, Laplace transformation and ordinary differential equations (in Japanese), Sho-Ko-dou (1995). [] M. S. J., Mathematics Dictionary, (Sugaku Jiten, in Japanese), Math. Soc. Japan, 4th edition, Iwanami (7). [3] T. Sudo, Computing the inverse Laplace transform for rational functions vanishing at infinity, Cubo A Math. J., 16, No 3 (14), [4] A. Vretblad, Fourier Analysis and Its Applications, GTM 3, Springer (3).
Computing the inverse Laplace transform for rational functions vanishing at infinity
CUBO A Mathematical Journal Vol.6, N ō 3, (97 7. October 24 Computing the inverse Laplace transform for rational functions vanishing at infinity Takahiro Sudo Department of Mathematical Sciences, Faculty
More informationf(t)e st dt. (4.1) Note that the integral defining the Laplace transform converges for s s 0 provided f(t) Ke s 0t for some constant K.
4 Laplace transforms 4. Definition and basic properties The Laplace transform is a useful tool for solving differential equations, in particular initial value problems. It also provides an example of integral
More informationGeneralized sources (Sect. 6.5). The Dirac delta generalized function. Definition Consider the sequence of functions for n 1, Remarks:
Generalized sources (Sect. 6.5). The Dirac delta generalized function. Definition Consider the sequence of functions for n, d n, t < δ n (t) = n, t 3 d3 d n, t > n. d t The Dirac delta generalized function
More informationLaplace Transform. Chapter 4
Chapter 4 Laplace Transform It s time to stop guessing solutions and find a systematic way of finding solutions to non homogeneous linear ODEs. We define the Laplace transform of a function f in the following
More informationLaplace Transform Introduction
Laplace Transform Introduction In many problems, a function is transformed to another function through a relation of the type: where is a known function. Here, is called integral transform of. Thus, an
More informationChapter 6: The Laplace Transform 6.3 Step Functions and
Chapter 6: The Laplace Transform 6.3 Step Functions and Dirac δ 2 April 2018 Step Function Definition: Suppose c is a fixed real number. The unit step function u c is defined as follows: u c (t) = { 0
More informationThe Laplace transform
The Laplace transform Samy Tindel Purdue University Differential equations - MA 266 Taken from Elementary differential equations by Boyce and DiPrima Samy T. Laplace transform Differential equations 1
More informationReading assignment: In this chapter we will cover Sections Definition and the Laplace transform of simple functions
Chapter 4 Laplace Tranform 4 Introduction Reading aignment: In thi chapter we will cover Section 4 45 4 Definition and the Laplace tranform of imple function Given f, a function of time, with value f(t
More information(f g)(t) = Example 4.5.1: Find f g the convolution of the functions f(t) = e t and g(t) = sin(t). Solution: The definition of convolution is,
.5. Convolutions and Solutions Solutions of initial value problems for linear nonhomogeneous differential equations can be decomposed in a nice way. The part of the solution coming from the initial data
More informatione st f (t) dt = e st tf(t) dt = L {t f(t)} s
Additional operational properties How to find the Laplace transform of a function f (t) that is multiplied by a monomial t n, the transform of a special type of integral, and the transform of a periodic
More informationOrdinary differential equations
Class 11 We will address the following topics Convolution of functions Consider the following question: Suppose that u(t) has Laplace transform U(s), v(t) has Laplace transform V(s), what is the inverse
More information2.161 Signal Processing: Continuous and Discrete Fall 2008
MIT OpenCourseWare http://ocw.mit.edu.6 Signal Processing: Continuous and Discrete Fall 008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. MASSACHUSETTS
More informationComputing inverse Laplace Transforms.
Review Exam 3. Sections 4.-4.5 in Lecture Notes. 60 minutes. 7 problems. 70 grade attempts. (0 attempts per problem. No partial grading. (Exceptions allowed, ask you TA. Integration table included. Complete
More informationName: Solutions Final Exam
Instructions. Answer each of the questions on your own paper. Put your name on each page of your paper. Be sure to show your work so that partial credit can be adequately assessed. Credit will not be given
More informationADVANCED ENGINEERING MATHEMATICS MATLAB
ADVANCED ENGINEERING MATHEMATICS WITH MATLAB THIRD EDITION Dean G. Duffy Contents Dedication Contents Acknowledgments Author Introduction List of Definitions Chapter 1: Complex Variables 1.1 Complex Numbers
More informationMath Shifting theorems
Math 37 - Shifting theorems Erik Kjær Pedersen November 29, 2005 Let us recall the Dirac delta function. It is a function δ(t) which is 0 everywhere but at t = 0 it is so large that b a (δ(t)dt = when
More informationMULTI-RESTRAINED STIRLING NUMBERS
MULTI-RESTRAINED STIRLING NUMBERS JI YOUNG CHOI DEPARTMENT OF MATHEMATICS SHIPPENSBURG UNIVERSITY SHIPPENSBURG, PA 17257, U.S.A. Abstract. Given positive integers n, k, and m, the (n, k)-th m- restrained
More informationENGIN 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 informationLTI Systems (Continuous & Discrete) - Basics
LTI Systems (Continuous & Discrete) - Basics 1. A system with an input x(t) and output y(t) is described by the relation: y(t) = t. x(t). This system is (a) linear and time-invariant (b) linear and time-varying
More informationUnit 2: Modeling in the Frequency Domain Part 2: The Laplace Transform. The Laplace Transform. The need for Laplace
Unit : Modeling in the Frequency Domain Part : Engineering 81: Control Systems I Faculty of Engineering & Applied Science Memorial University of Newfoundland January 1, 010 1 Pair Table Unit, Part : Unit,
More informationFinite-dimensional spaces. C n is the space of n-tuples x = (x 1,..., x n ) of complex numbers. It is a Hilbert space with the inner product
Chapter 4 Hilbert Spaces 4.1 Inner Product Spaces Inner Product Space. A complex vector space E is called an inner product space (or a pre-hilbert space, or a unitary space) if there is a mapping (, )
More informationHIGHER-ORDER LINEAR ORDINARY DIFFERENTIAL EQUATIONS IV: Laplace Transform Method David Levermore Department of Mathematics University of Maryland
HIGHER-ORDER LINEAR ORDINARY DIFFERENTIAL EQUATIONS IV: Laplace Transform Method David Levermore Department of Mathematics University of Maryland 9 December Because the presentation of this material in
More informationMath 2C03 - Differential Equations. Slides shown in class - Winter Laplace Transforms. March 4, 5, 9, 11, 12, 16,
Math 2C03 - Differential Equations Slides shown in class - Winter 2015 Laplace Transforms March 4, 5, 9, 11, 12, 16, 18... 2015 Laplace Transform used to solve linear ODEs and systems of linear ODEs with
More informationHIGHER-ORDER LINEAR ORDINARY DIFFERENTIAL EQUATIONS IV: Laplace Transform Method. David Levermore Department of Mathematics University of Maryland
HIGHER-ORDER LINEAR ORDINARY DIFFERENTIAL EQUATIONS IV: Laplace Transform Method David Levermore Department of Mathematics University of Maryland 6 April Because the presentation of this material in lecture
More informationbe the set of complex valued 2π-periodic functions f on R such that
. Fourier series. Definition.. Given a real number P, we say a complex valued function f on R is P -periodic if f(x + P ) f(x) for all x R. We let be the set of complex valued -periodic functions f on
More informationSpecial Mathematics Laplace Transform
Special Mathematics Laplace Transform March 28 ii Nature laughs at the difficulties of integration. Pierre-Simon Laplace 4 Laplace Transform Motivation Properties of the Laplace transform the Laplace transform
More information(an improper integral)
Chapter 7 Laplace Transforms 7.1 Introduction: A Mixing Problem 7.2 Definition of the Laplace Transform Def 7.1. Let f(t) be a function on [, ). The Laplace transform of f is the function F (s) defined
More informationLecture 1 January 5, 2016
MATH 262/CME 372: Applied Fourier Analysis and Winter 26 Elements of Modern Signal Processing Lecture January 5, 26 Prof. Emmanuel Candes Scribe: Carlos A. Sing-Long; Edited by E. Candes & E. Bates Outline
More informationLecture 4: Numerical solution of ordinary differential equations
Lecture 4: Numerical solution of ordinary differential equations Department of Mathematics, ETH Zürich General explicit one-step method: Consistency; Stability; Convergence. High-order methods: Taylor
More informationDifferential equations, comprehensive exam topics and sample questions
Differential equations, comprehensive exam topics and sample questions Topics covered ODE s: Chapters -5, 7, from Elementary Differential Equations by Edwards and Penney, 6th edition.. Exact solutions
More informationReading assignment: In this chapter we will cover Sections Definition and the Laplace transform of simple functions
Chapter 4 Laplace Tranform 4 Introduction Reading aignment: In thi chapter we will cover Section 4 45 4 Definition and the Laplace tranform of imple function Given f, a function of time, with value f(t
More informationWe denote the space of distributions on Ω by D ( Ω) 2.
Sep. 1 0, 008 Distributions Distributions are generalized functions. Some familiarity with the theory of distributions helps understanding of various function spaces which play important roles in the study
More informationFORMAL GROUPS OF CERTAIN Q-CURVES OVER QUADRATIC FIELDS
Sairaiji, F. Osaka J. Math. 39 (00), 3 43 FORMAL GROUPS OF CERTAIN Q-CURVES OVER QUADRATIC FIELDS FUMIO SAIRAIJI (Received March 4, 000) 1. Introduction Let be an elliptic curve over Q. We denote by ˆ
More information11.8 Power Series. Recall the geometric series. (1) x n = 1+x+x 2 + +x n +
11.8 1 11.8 Power Series Recall the geometric series (1) x n 1+x+x 2 + +x n + n As we saw in section 11.2, the series (1) diverges if the common ratio x > 1 and converges if x < 1. In fact, for all x (
More informationHW 9, Math 319, Fall 2016
HW 9, Math 39, Fall Nasser M. Abbasi Discussion section 447, Th 4:3PM-: PM December, Contents HW 9. Section. problem................................... Part a....................................... Part
More informationPractice Problems For Test 3
Practice Problems For Test 3 Power Series Preliminary Material. Find the interval of convergence of the following. Be sure to determine the convergence at the endpoints. (a) ( ) k (x ) k (x 3) k= k (b)
More informationMA Ordinary Differential Equations and Control Semester 1 Lecture Notes on ODEs and Laplace Transform (Parts I and II)
MA222 - Ordinary Differential Equations and Control Semester Lecture Notes on ODEs and Laplace Transform (Parts I and II Dr J D Evans October 22 Special thanks (in alphabetical order are due to Kenneth
More information2.161 Signal Processing: Continuous and Discrete Fall 2008
MIT OpenCourseWare http://ocw.mit.edu 2.6 Signal Processing: Continuous and Discrete Fall 2008 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. MASSACHUSETTS
More informationVectors in Function Spaces
Jim Lambers MAT 66 Spring Semester 15-16 Lecture 18 Notes These notes correspond to Section 6.3 in the text. Vectors in Function Spaces We begin with some necessary terminology. A vector space V, also
More informationNotes on uniform convergence
Notes on uniform convergence Erik Wahlén erik.wahlen@math.lu.se January 17, 2012 1 Numerical sequences We begin by recalling some properties of numerical sequences. By a numerical sequence we simply mean
More informationMath 308 Exam II Practice Problems
Math 38 Exam II Practice Problems This review should not be used as your sole source for preparation for the exam. You should also re-work all examples given in lecture and all suggested homework problems..
More informationECEN 420 LINEAR CONTROL SYSTEMS. Lecture 2 Laplace Transform I 1/52
1/52 ECEN 420 LINEAR CONTROL SYSTEMS Lecture 2 Laplace Transform I Linear Time Invariant Systems A general LTI system may be described by the linear constant coefficient differential equation: a n d n
More informationPractice Problems For Test 3
Practice Problems For Test 3 Power Series Preliminary Material. Find the interval of convergence of the following. Be sure to determine the convergence at the endpoints. (a) ( ) k (x ) k (x 3) k= k (b)
More informationMath 201 Lecture 17: Discontinuous and Periodic Functions
Math 2 Lecture 7: Dicontinuou and Periodic Function Feb. 5, 22 Many example here are taken from the textbook. he firt number in () refer to the problem number in the UA Cutom edition, the econd number
More informationLaplace Transforms Chapter 3
Laplace Transforms Important analytical method for solving linear ordinary differential equations. - Application to nonlinear ODEs? Must linearize first. Laplace transforms play a key role in important
More informationMATRIX INTEGRALS AND MAP ENUMERATION 2
MATRIX ITEGRALS AD MAP EUMERATIO 2 IVA CORWI Abstract. We prove the generating function formula for one face maps and for plane diagrams using techniques from Random Matrix Theory and orthogonal polynomials.
More informationComplex Inversion Formula for Stieltjes and Widder Transforms with Applications
Int. J. Contemp. Math. Sciences, Vol. 3, 8, no. 16, 761-77 Complex Inversion Formula for Stieltjes and Widder Transforms with Applications A. Aghili and A. Ansari Department of Mathematics, Faculty of
More informationMath 3313: Differential Equations Laplace transforms
Math 3313: Differential Equations Laplace transforms Thomas W. Carr Department of Mathematics Southern Methodist University Dallas, TX Outline Introduction Inverse Laplace transform Solving ODEs with Laplace
More informationExam Basics. midterm. 1 There will be 9 questions. 2 The first 3 are on pre-midterm material. 3 The next 1 is a mix of old and new material.
Exam Basics 1 There will be 9 questions. 2 The first 3 are on pre-midterm material. 3 The next 1 is a mix of old and new material. 4 The last 5 questions will be on new material since the midterm. 5 60
More informationMATH 1A, Complete Lecture Notes. Fedor Duzhin
MATH 1A, Complete Lecture Notes Fedor Duzhin 2007 Contents I Limit 6 1 Sets and Functions 7 1.1 Sets................................. 7 1.2 Functions.............................. 8 1.3 How to define a
More informationarxiv: v1 [math.ca] 6 May 2016
An elementary purely algebraic approach to generalized functions and operational calculus Vakhtang Lomadze arxiv:1605.02050v1 [math.ca] 6 May 2016 Andrea Razmadze Mathematical Institute, Mathematics Department
More informationJUHA KINNUNEN. Partial Differential Equations
JUHA KINNUNEN Partial Differential Equations Department of Mathematics and Systems Analysis, Aalto University 207 Contents INTRODUCTION 2 FOURIER SERIES AND PDES 5 2. Periodic functions*.............................
More informationSOME FACTORIZATIONS IN THE TWISTED GROUP ALGEBRA OF SYMMETRIC GROUPS. University of Rijeka, Croatia
GLASNIK MATEMATIČKI Vol. 5171)2016), 1 15 SOME FACTORIZATIONS IN THE TWISTED GROUP ALGEBRA OF SYMMETRIC GROUPS Milena Sošić University of Rijeka, Croatia Abstract. In this paper we will give a similar
More informationMATH 205B NOTES 2010 COMMUTATIVE ALGEBRA 53
MATH 205B NOTES 2010 COMMUTATIVE ALGEBRA 53 10. Completion The real numbers are the completion of the rational numbers with respect to the usual absolute value norm. This means that any Cauchy sequence
More informationCITY UNIVERSITY LONDON
No: CITY UNIVERSITY LONDON BEng (Hons)/MEng (Hons) Degree in Civil Engineering BEng (Hons)/MEng (Hons) Degree in Civil Engineering with Surveying BEng (Hons)/MEng (Hons) Degree in Civil Engineering with
More information1 Math 241A-B Homework Problem List for F2015 and W2016
1 Math 241A-B Homework Problem List for F2015 W2016 1.1 Homework 1. Due Wednesday, October 7, 2015 Notation 1.1 Let U be any set, g be a positive function on U, Y be a normed space. For any f : U Y let
More informationIMPROVEMENTS OF COMPOSITION RULE FOR THE CANAVATI FRACTIONAL DERIVATIVES AND APPLICATIONS TO OPIAL-TYPE INEQUALITIES
Dynamic Systems and Applications ( 383-394 IMPROVEMENTS OF COMPOSITION RULE FOR THE CANAVATI FRACTIONAL DERIVATIVES AND APPLICATIONS TO OPIAL-TYPE INEQUALITIES M ANDRIĆ, J PEČARIĆ, AND I PERIĆ Faculty
More informationLecture 7: Laplace Transform and Its Applications Dr.-Ing. Sudchai Boonto
Dr-Ing Sudchai Boonto Department of Control System and Instrumentation Engineering King Mongkut s Unniversity of Technology Thonburi Thailand Outline Motivation The Laplace Transform The Laplace Transform
More informationTaylor and Maclaurin Series
Taylor and Maclaurin Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Background We have seen that some power series converge. When they do, we can think of them as
More information9.2 The Input-Output Description of a System
Lecture Notes on Control Systems/D. Ghose/212 22 9.2 The Input-Output Description of a System The input-output description of a system can be obtained by first defining a delta function, the representation
More informationPart V. 17 Introduction: What are measures and why measurable sets. Lebesgue Integration Theory
Part V 7 Introduction: What are measures and why measurable sets Lebesgue Integration Theory Definition 7. (Preliminary). A measure on a set is a function :2 [ ] such that. () = 2. If { } = is a finite
More information1 Review of di erential calculus
Review of di erential calculus This chapter presents the main elements of di erential calculus needed in probability theory. Often, students taking a course on probability theory have problems with concepts
More informationTopics in Fourier analysis - Lecture 2.
Topics in Fourier analysis - Lecture 2. Akos Magyar 1 Infinite Fourier series. In this section we develop the basic theory of Fourier series of periodic functions of one variable, but only to the extent
More informationL2 gains and system approximation quality 1
Massachusetts Institute of Technology Department of Electrical Engineering and Computer Science 6.242, Fall 24: MODEL REDUCTION L2 gains and system approximation quality 1 This lecture discusses the utility
More informationRecall that any inner product space V has an associated norm defined by
Hilbert Spaces Recall that any inner product space V has an associated norm defined by v = v v. Thus an inner product space can be viewed as a special kind of normed vector space. In particular every inner
More informationMathematical Foundations of Signal Processing
Mathematical Foundations of Signal Processing Module 4: Continuous-Time Systems and Signals Benjamín Béjar Haro Mihailo Kolundžija Reza Parhizkar Adam Scholefield October 24, 2016 Continuous Time Signals
More information1 Signals and systems
978--52-5688-4 - Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis Signals and systems In the first two chapters we will consider some basic concepts and ideas as
More informationConsidering our result for the sum and product of analytic functions, this means that for (a 0, a 1,..., a N ) C N+1, the polynomial.
Lecture 3 Usual complex functions MATH-GA 245.00 Complex Variables Polynomials. Construction f : z z is analytic on all of C since its real and imaginary parts satisfy the Cauchy-Riemann relations and
More information2 Classification of Continuous-Time Systems
Continuous-Time Signals and Systems 1 Preliminaries Notation for a continuous-time signal: x(t) Notation: If x is the input to a system T and y the corresponding output, then we use one of the following
More informationLecture 6 January 21, 2016
MATH 6/CME 37: Applied Fourier Analysis and Winter 06 Elements of Modern Signal Processing Lecture 6 January, 06 Prof. Emmanuel Candes Scribe: Carlos A. Sing-Long, Edited by E. Bates Outline Agenda: Fourier
More information2tdt 1 y = t2 + C y = which implies C = 1 and the solution is y = 1
Lectures - Week 11 General First Order ODEs & Numerical Methods for IVPs In general, nonlinear problems are much more difficult to solve than linear ones. Unfortunately many phenomena exhibit nonlinear
More informationNotions such as convergent sequence and Cauchy sequence make sense for any metric space. Convergent Sequences are Cauchy
Banach Spaces These notes provide an introduction to Banach spaces, which are complete normed vector spaces. For the purposes of these notes, all vector spaces are assumed to be over the real numbers.
More informationName: Solutions Exam 3
Instructions. Answer each of the questions on your own paper. Put your name on each page of your paper. Be sure to show your work so that partial credit can be adequately assessed. Credit will not be given
More informationALEXEY V. GAVRILOV. I p (v) : T p M T Expp vm the operator of parallel transport along the geodesic γ v. Let E p be the map
THE TAYLOR SERIES RELATE TO THE IFFERENTIAL OF THE EXPONENTIAL MAP arxiv:205.2868v [math.g] 3 May 202 ALEXEY V. GAVRILOV Abstract. In this paper we study the Taylor series of an operator-valued function
More informationMath 341 Fall 2008 Friday December 12
FINAL EXAM: Differential Equations Math 341 Fall 2008 Friday December 12 c 2008 Ron Buckmire 1:00pm-4:00pm Name: Directions: Read all problems first before answering any of them. There are 17 pages in
More informatione (x y)2 /4kt φ(y) dy, for t > 0. (4)
Math 24A October 26, 2 Viktor Grigoryan Heat equation: interpretation of the solution Last time we considered the IVP for the heat equation on the whole line { ut ku xx = ( < x
More informationOn Tornheim's double series
ACTA ARITHMETICA LXXV.2 (1996) On Tornheim's double series JAMES G. HUARD (Buffalo, N.Y.), KENNETH S. WILLIAMS (Ottawa, Ont.) and ZHANG NAN-YUE (Beijing) 1. Introduction. We call the double infinite series
More informationHilbert Spaces. Contents
Hilbert Spaces Contents 1 Introducing Hilbert Spaces 1 1.1 Basic definitions........................... 1 1.2 Results about norms and inner products.............. 3 1.3 Banach and Hilbert spaces......................
More informationFourier Series and Transforms. Revision Lecture
E. (5-6) : / 3 Periodic signals can be written as a sum of sine and cosine waves: u(t) u(t) = a + n= (a ncosπnft+b n sinπnft) T = + T/3 T/ T +.65sin(πFt) -.6sin(πFt) +.6sin(πFt) + -.3cos(πFt) + T/ Fundamental
More informationConvolution. Define a mathematical operation on discrete-time signals called convolution, represented by *. Given two discrete-time signals x 1, x 2,
Filters Filters So far: Sound signals, connection to Fourier Series, Introduction to Fourier Series and Transforms, Introduction to the FFT Today Filters Filters: Keep part of the signal we are interested
More informationMath 20D: Form B Final Exam Dec.11 (3:00pm-5:50pm), Show all of your work. No credit will be given for unsupported answers.
Turn off and put away your cell phone. No electronic devices during the exam. No books or other assistance during the exam. Show all of your work. No credit will be given for unsupported answers. Write
More informationX b n sin nπx L. n=1 Fourier Sine Series Expansion. a n cos nπx L 2 + X. n=1 Fourier Cosine Series Expansion ³ L. n=1 Fourier Series Expansion
3 Fourier Series 3.1 Introduction Although it was not apparent in the early historical development of the method of separation of variables what we are about to do is the analog for function spaces of
More information4. Noether normalisation
4. Noether normalisation We shall say that a ring R is an affine ring (or affine k-algebra) if R is isomorphic to a polynomial ring over a field k with finitely many indeterminates modulo an ideal, i.e.,
More informationTHE S 1 -EQUIVARIANT COHOMOLOGY RINGS OF (n k, k) SPRINGER VARIETIES
Horiguchi, T. Osaka J. Math. 52 (2015), 1051 1062 THE S 1 -EQUIVARIANT COHOMOLOGY RINGS OF (n k, k) SPRINGER VARIETIES TATSUYA HORIGUCHI (Received January 6, 2014, revised July 14, 2014) Abstract The main
More information7: FOURIER SERIES STEVEN HEILMAN
7: FOURIER SERIES STEVE HEILMA Contents 1. Review 1 2. Introduction 1 3. Periodic Functions 2 4. Inner Products on Periodic Functions 3 5. Trigonometric Polynomials 5 6. Periodic Convolutions 7 7. Fourier
More informationHecke Operators, Zeta Functions and the Satake map
Hecke Operators, Zeta Functions and the Satake map Thomas R. Shemanske December 19, 2003 Abstract Taking advantage of the Satake isomorphism, we define (n + 1) families of Hecke operators t n k (pl ) for
More informationMATH MEASURE THEORY AND FOURIER ANALYSIS. Contents
MATH 3969 - MEASURE THEORY AND FOURIER ANALYSIS ANDREW TULLOCH Contents 1. Measure Theory 2 1.1. Properties of Measures 3 1.2. Constructing σ-algebras and measures 3 1.3. Properties of the Lebesgue measure
More informationA sufficient condition for the existence of the Fourier transform of f : R C is. f(t) dt <. f(t) = 0 otherwise. dt =
Fourier transform Definition.. Let f : R C. F [ft)] = ˆf : R C defined by The Fourier transform of f is the function F [ft)]ω) = ˆfω) := ft)e iωt dt. The inverse Fourier transform of f is the function
More informationChapter 5. Modular arithmetic. 5.1 The modular ring
Chapter 5 Modular arithmetic 5.1 The modular ring Definition 5.1. Suppose n N and x, y Z. Then we say that x, y are equivalent modulo n, and we write x y mod n if n x y. It is evident that equivalence
More informationMA 201, Mathematics III, July-November 2016, Laplace Transform
MA 21, Mathematics III, July-November 216, Laplace Transform Lecture 18 Lecture 18 MA 21, PDE (216) 1 / 21 Laplace Transform Let F : [, ) R. If F(t) satisfies the following conditions: F(t) is piecewise
More informationSystems Analysis and Control
Systems Analysis and Control Matthew M. Peet Arizona State University Lecture 5: Calculating the Laplace Transform of a Signal Introduction In this Lecture, you will learn: Laplace Transform of Simple
More informationLaplace Transform Theory - 1
Laplace Transform Theory - 1 Existence of Laplace Transforms Before continuing our use of Laplace transforms for solving DEs, it is worth digressing through a quick investigation of which functions actually
More informationCOMPOSITIONAL INVERSION OF TRIANGULAR SETS OF SERIES. Marilena BARNABEI
Publ. I.R.M.A. Strasbourg, 1984, 229/S 08 Actes 8 e Séminaire Lotharingien, p. 5 10 COMPOSITIONAL INVERSION OF TRIANGULAR SETS OF SERIES BY Marilena BARNABEI There are two possible definitions of formal
More informationHarmonic Analysis on the Cube and Parseval s Identity
Lecture 3 Harmonic Analysis on the Cube and Parseval s Identity Jan 28, 2005 Lecturer: Nati Linial Notes: Pete Couperus and Neva Cherniavsky 3. Where we can use this During the past weeks, we developed
More informationConformal maps. Lent 2019 COMPLEX METHODS G. Taylor. A star means optional and not necessarily harder.
Lent 29 COMPLEX METHODS G. Taylor A star means optional and not necessarily harder. Conformal maps. (i) Let f(z) = az + b, with ad bc. Where in C is f conformal? cz + d (ii) Let f(z) = z +. What are the
More informationExistence Theory: Green s Functions
Chapter 5 Existence Theory: Green s Functions In this chapter we describe a method for constructing a Green s Function The method outlined is formal (not rigorous) When we find a solution to a PDE by constructing
More informationAn approach to the Biharmonic pseudo process by a Random walk
J. Math. Kyoto Univ. (JMKYAZ) - (), An approach to the Biharmonic pseudo process by a Random walk By Sadao Sato. Introduction We consider the partial differential equation u t 4 u 8 x 4 (.) Here 4 x 4
More informationMath 210B. Artin Rees and completions
Math 210B. Artin Rees and completions 1. Definitions and an example Let A be a ring, I an ideal, and M an A-module. In class we defined the I-adic completion of M to be M = lim M/I n M. We will soon show
More informationArithmetic Funtions Over Rings with Zero Divisors
BULLETIN of the Bull Malaysian Math Sc Soc (Second Series) 24 (200 81-91 MALAYSIAN MATHEMATICAL SCIENCES SOCIETY Arithmetic Funtions Over Rings with Zero Divisors 1 PATTIRA RUANGSINSAP, 1 VICHIAN LAOHAKOSOL
More informationA CONSTRUCTION FOR ABSOLUTE VALUES IN POLYNOMIAL RINGS. than define a second approximation V 0
A CONSTRUCTION FOR ABSOLUTE VALUES IN POLYNOMIAL RINGS by SAUNDERS MacLANE 1. Introduction. An absolute value of a ring is a function b which has some of the formal properties of the ordinary absolute
More information