Iterative Computation of Higher Derivatives of Repeated Eigenvalues and the Corresponding Eigenvectors

2002 ◽  
pp. 43-54 ◽  
Author(s):  
Alan L. Andrew ◽  
Roger C. E. Tan
Keyword(s):  
Iterative Computation ◽  
Repeated Eigenvalues ◽  
Higher Derivatives ◽  
Derivatives Of

The Coarse Scale Velocity

2017 ◽  
Author(s):  
Philip Isett
Keyword(s):  
Velocity Field ◽  
Building Blocks ◽  
Coarse Scale ◽  
Divergence Equation ◽  
Higher Derivatives ◽  
Order Of Magnitude ◽  
Derivatives Of

This chapter deals with the coarse scale velocity. It begins the proof of Lemma (10.1) by choosing a double mollification for the velocity field. Here ∈ᵥ is taken to be as large as possible so that higher derivatives of velement are less costly, and each vsubscript Element has frequency smaller than λ‎ so elementv⁻¹ must be smaller than λ‎ in order of magnitude. Each derivative of vsubscript Element up to order L costs a factor of Ξ‎. The chapter proceeds by describing the basic building blocks of the construction, the choice of elementv and the parametrix expansion for the divergence equation.

The Perception of the Higher Derivatives of Visual Motion.

1986 ◽  
Author(s):  
Lloyd Kaufman ◽  
Samuel J. Williamson
Keyword(s):  
Visual Motion ◽  
Higher Derivatives ◽  
Derivatives Of

scholarly journals On the Zeros of Higher Derivatives of Hardy'sZ-Function

1999 ◽  
Vol 75 (2) ◽  
pp. 262-278 ◽  
Author(s):  
Kohji Matsumoto ◽  
Yoshio Tanigawa
Keyword(s):  
Higher Derivatives ◽  
Derivatives Of

An Introduction to Finite Differencing

1998 ◽  
Author(s):  
T. N. Krishnamurti ◽  
H. S. Bedi ◽  
V. M. Hardiker
Keyword(s):  
Finite Difference ◽  
Finite Differences ◽  
Single Point ◽  
Finite Differencing ◽  
Finite Difference Approximations ◽  
Difference Approximations ◽  
Student Reading ◽  
Higher Derivatives ◽  
Derivatives Of

This chapter on finite differencing appears oddly placed in the early part of a text on spectral modeling. Finite differences are still traditionally used for vertical differencing and for time differencing. Therefore, we feel that an introduction to finite-differencing methods is quite useful. Furthermore, the student reading this chapter has the opportunity to compare these methods with the spectral method which will be developed in later chapters. One may use Taylor’s expansion of a given function about a single point to approximate the derivative(s) at that point. Derivatives in the equation involving a function are replaced by finite difference approximations. The values of the function are known at discrete points in both space and time. The resulting equation is then solved algebraically with appropriate restrictions. Suppose u is a function of x possessing derivatives of all orders in the interval (x — n∆x, x + n∆x). Then we can obtain the values of u at points x ± n∆ x, where n is any integer, in terms of the value of the function and its derivatives at point x, that is, u(x) and its higher derivatives.

Symbolic Powers of Regular Primes

1981 ◽  
Vol 33 (6) ◽  
pp. 1331-1337 ◽  
Author(s):  
Yasunori Ishibashi
Keyword(s):  
Prime Ideal ◽  
Finite Type ◽  
Polynomial Ring ◽  
Type A ◽  
Symbolic Power ◽  
Perfect Field ◽  
Symbolic Powers ◽  
Higher Derivatives ◽  
Differential Filtration ◽  
Derivatives Of

In a recent paper [6], P. Seibt has obtained the following result: Let k be a field of characteristic 0, k[T1, … , Tr] the polynomial ring in r indeterminates over k, and let P be a prime ideal of k[T1, … , Tr]. Then a polynomial F belongs to the n-th symbolic power P(n) of P if and only if all higher derivatives of F from the 0-th up to the (n – l)-st order belong to P.In this work we shall naturally generalize this result so as to be valid for primes of the polynomial ring over a perfect field k. Actually, we shall get a generalization as a corollary to a theorem which asserts: For regular primes P in a k-algebra R of finite type, a certain differential filtration of R associated with P coincides with the symbolic power filtration (P(n))n≧0.

scholarly journals A look into the cosmological consequences of a dark energy model with higher derivatives of H in the framework of Chameleon Brans–Dicke cosmology

2019 ◽  
Vol 28 (11) ◽  
pp. 1950149 ◽  
Author(s):  
Antonio Pasqua ◽  
Surajit Chattopadhyay ◽  
Aroonkumar Beesham
Keyword(s):  
Dark Energy ◽  
Dark Energy Model ◽  
Late Time ◽  
Statefinder Parameters ◽  
Eos Parameter ◽  
Higher Derivatives ◽  
De Formula ◽  
Derivatives Of ◽  
The Universe ◽  
Far Future

In this paper, we study some relevant cosmological features of a Dark Energy (DE) model with Granda–Oliveros cut-off, which is just a specific case of Nojiri–Odintsov holographic DE [S. Nojiri and S. D. Odintsov, Gen. Relativ. Gravit. 38 (2006) 1285] unifying phantom inflation with late-time acceleration, in the framework of Chameleon Brans–Dicke (BD) cosmology. Choosing a particular ansatz for some of the quantities involved, we derive the expressions of some important cosmological quantities, like the Equation of State (EoS) parameter of DE [Formula: see text], the effective EoS parameter [Formula: see text], the pressure of DE [Formula: see text] and the deceleration parameter [Formula: see text]. Moreover, we study the behavior of statefinder parameters [Formula: see text] and [Formula: see text], of the cosmographic parameters [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] and of the squared speed of the sound [Formula: see text] for both case corresponding to noninteracting and interacting Dark sectors. We also plot the quantities we have derived and we calculate their values for [Formula: see text] (i.e. for the beginning of the universe history), for [Formula: see text] (i.e. for far future) and for the present time, indicated with [Formula: see text]. The EoS parameters have been tested against various observational values available in the literature.

scholarly journals Integration of the Short-Range Hyperbolic System Jemioluszka and DGPS

2008 ◽  
Vol 4 (1) ◽  
pp. 5-24
Author(s):  
Andrzej Banachowicz ◽  
Adam Wolski ◽  
Grzegorz Banachowicz
Keyword(s):  
Hyperbolic System ◽  
Short Range ◽  
Simulation Method ◽  
State Variables ◽  
Inertial Measurement ◽  
Accuracy Of Measurements ◽  
Higher Derivatives ◽  
Measurement Units ◽  
Navigational System ◽  
Derivatives Of

Integration of the Short-Range Hyperbolic System Jemioluszka and DGPS This article describes an algorithm of an integrated navigational system developed for the navigation and steering along a given trajectory by rescuesalvage ships operated by the Polish Navy. Due to strict requirements concerning the accuracy of measurements of navigational parameters of ships at slow speeds, inertial measurement units have been used, whilst the state variables in the algorithm include higher derivatives of the velocity vector. The algorithm has been verified by a simulation method and at sea trials on board a real ship.

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