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225
Differentiation of Heat Semigroups and Applications
, 1994
"... Introduction Consider the Stratonovich stochastic differential equation dx t = X(x t ) ffi dB t +A(x t )dt: (1) on R n with coefficients A : R n ! R n a smooth vector field and X : R n ! L (R m ; R n ) a smooth map into the space of linear maps of R m into R n , driven by the white ..."
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by the white noise determined by a Brownian motion fB t : t 0g on R m . It can also be written dx t = m X 1 X i (x t ) ffi dB<F23.
http://zoobank.org/urn:lsid:zoobank.org:pub:AF4F85B3DB544EE4BBA8B23F39D32CEB
"... www.mapress.com/zootaxa/ ..."
A class of integration by parts formulae in stochastic analysis I
"... Introduction Consider a Stratonovich stochastic differential equation dx t = X(x t ) ffi dB t +A(x t )dt (1) with C 1 coefficients on a compact Riemannian manifold M , with associated differential generator A = 1 2 \Delta M +Z and solution flow f¸ t : t 0g of random smooth diffeomorphisms of ..."
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Cited by 19 (10 self)
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Introduction Consider a Stratonovich stochastic differential equation dx t = X(x t ) ffi dB t +A(x t )dt (1) with C 1 coefficients on a compact Riemannian manifold M , with associated differential generator A = 1 2 \Delta M +Z and solution flow f¸ t : t 0g of random smooth diffeomorphisms
Optimal Approximations Of Fractional Derivatives
, 1998
"... . In this paper we consider the following fractional differentiation problem: given noisy data f ffi 2 L 2 (IR) to f , determine the fractional derivative u = D fi f 2 L 2 (IR) for fi ? 0, which is the solution of the integral equation of first kind (A fi u)(x) = 1 \Gamma(fi ) R x \Gamma1 ..."
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. In this paper we consider the following fractional differentiation problem: given noisy data f ffi 2 L 2 (IR) to f , determine the fractional derivative u = D fi f 2 L 2 (IR) for fi ? 0, which is the solution of the integral equation of first kind (A fi u)(x) = 1 \Gamma(fi ) R x \Gamma1
An Improved Nuclear Level Density Description
"... o magic numbers, other spherical nuclei, and deformed nuclei), thus increasing the number of parameters by a factor of three. The deviations were still up to a factor of 45. We employed a different treatment of the density parameter a which includes thermal damping of shell effects [5]. The param ..."
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]. The parameter a is then given by a(U; Z; N ) = a (A)[1 + C(Z; N ) f(U \Gamma ffi ) U \Gamma ffi ] ; where a = ffA + fiA 2=3 , and A, U , and ffi denote the mass number, excitation energy, and backshift, respectively. The shell correction is given by C. The shape of the function f(U ) was found b
obtained by the Chase decoding with the CMI of R 2, a slight improvement is achieved when the CMI of eye level x R is used. An SNR reduction of about 1 dB is obtained for a BER all0 3.
"... lock codes using received signal envelopes in fading channels'. ICC '88 Conference Record, 1988, pp. 24.4.1 5 STJERNVALL, I. E., and IJDDENFELDT, J.: 'Gaussian MSK with different demodulators and channel coding for mobile telephony'. IEEE ICC '84 Conference Record, 1984. pp ..."
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. pp. 12191222 6 EKEMARK, s., anlXI, K., and STJERNVALL, 1. E.: 'Modulation and channel coding in digital mobile telephony'. Nordic Seminar on Digital Land Mobile Radio Communication, 1985, pp. 180188 7 OHNO, K., and ,XDAC:n, F.: 'Halfbit offset decision frequency detection
American Society of Civil Engineers, Task Committee of the Watershed Management Committee.
"... Beasley, D.B., L.F. Huggins, and E.J. Monke. 1980. ANSWERS: A model for watershed planning. Trans. ASAE 23:938944. Beaulac, M.N., and K.H. Reckhow. 1982. An examination of land usenutrient export relationships. Water Resources Bulletin 18(6): 1013 1024. ..."
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Beasley, D.B., L.F. Huggins, and E.J. Monke. 1980. ANSWERS: A model for watershed planning. Trans. ASAE 23:938944. Beaulac, M.N., and K.H. Reckhow. 1982. An examination of land usenutrient export relationships. Water Resources Bulletin 18(6): 1013 1024.
GraphBased Logic snd Sketches II: FiniteProduct Categories and Equational Logic
, 1997
"... ion. In this case the equational rule of inference reads Given a set of typed variables and x 2 Vbl[S] n V , e = V e 0 e = V [fxg e 0 We define ø : = Type[e] = Type[e 0 ] and oe : = Type[x], and f : P ! ø : = Arr [e; V; ø ] f 0 : P ! ø : = Arr \Theta e 0 ; V; ø g : Q ! ø : = Arr [e; ..."
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; V [ fxg; ø ] g 0 : Q ! ø : = Arr \Theta e 0 ; V [ fxg; ø Using Lemma 4.4.1, we may choose a map h : Y (V [ fxg) ! V such that g = f ffi h and g 0 = f 0 ffi h. Thus coded as arrows the rule reads f = f 0 f ffi h = f 0 ffi h GRAPHBASED LOGIC AND SKETCHES II 23 5
Concerning the Geometry of Stochastic Differential Equations and Stochastic Flows
 Kusuoka and I. Shigekawa (Eds.) New Trends in Stochastic Analysis. Proc. Taniguchi Symposium
, 1995
"... Le Jan and Watanabe showed that a nondegenerate stochastic flow f¸ t : t 0g on a manifold M determines a connection on M . This connection is characterized here and shown to be the LeviCivita connection for gradient systems. This both explains why such systems have useful properties and allows u ..."
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Cited by 16 (10 self)
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Bochner vanishing theorem. 1 Introduction and Notations A. Consider a Stratonovich stochastic differential equation dx t = X(x t ) ffi dB t +A(x t )dt (1) on an ndimensional C 1 manifold M , e.g. M = R n . Here A is a C 1 vector field on M , so A(x) lies in the tangent space T x M to M at x
Collapsing threemanifolds under a lower curvature bound
 J. Differential Geom
"... Abstract The purpose of this paper is to completely characterize the topology of threedimensional Riemannian manifolds with a uniform lower bound of sectional curvature which converges to a metric space of lower dimension. Introduction We study the topology of threedimensional Riemannian manifolds ..."
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Cited by 30 (3 self)
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'weak' singularities ([38]) in some sense. According to Perelman ([28]), it is also known that if X has no 'bad' singularities (precisely called extremal subsets), there is an isomorphism π k (M i , F i ) π k (X) for homotopy groups, where F i is a 'general fibre' and i
Results 1  10
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