نتایج جستجو برای: jacobian of transformation

تعداد نتایج: 21178142  

2009
WENHUA ZHAO

We first study some properties of images of commuting differential operators of polynomial algebras of order one with constant leading coefficients. We then propose what we call the image conjecture on these differential operators and show that the Jacobian conjecture [BCW], [E] (hence also the Dixmier conjecture [D]) and the vanishing conjecture [Z3] of differential operators with constant coe...

Journal: :Optimization Methods and Software 2009
Andrew Lyons Ilya Safro

We describe a code transformation technique that, given code for a vector function F , produces code suitable for computing collections of Jacobian-vector products F (x)ẋ or Jacobiantranspose-vector products F (x) ȳ. Exploitation of scarcity a measure of the degrees of freedom in the Jacobian matrix means solving a combinatorial optimization problem that is believed to be hard. Our heuristics t...

2002
Raquel Frizera Vassallo José Santos-Victor Hans Jörg Schneebeli

Computing a camera’s ego-motion from an image sequence is easier to accomplish when a spherical retina is used, as opposed to a standard retinal plane. On a spherical field of view both the focus of expansion and contraction are visible, whereas for a planar retina that is not necessarily the case. Recent research has shown that omnidirectional systems can be used to emulate spherical retinas b...

Journal: :journal of linear and topological algebra (jlta) 0
m nili ahmadabadi f ahmad spain g yuan china a azzam assuite university

a systematic way is presented for the construction of multi-step iterative method with frozen jacobian. the inclusion of an auxiliary function is discussed. the presented analysis shows that how to incorporate auxiliary function in a way that we can keep the order of convergence and computational cost of newton multi-step method. the auxiliary function provides us the way to overcome the singul...

Journal: :SIAM J. Scientific Computing 2002
Weiming Cao Weizhang Huang Robert D. Russell

A new adaptive mesh movement strategy is presented, which, unlike many existing moving mesh methods, targets the mesh velocities rather than the mesh coordinates. The mesh velocities are determined in a least squares framework by using the geometric conservation law, specifying a form for the Jacobian determinant of the coordinate transformation defining the mesh, and employing a curl condition...

2000
Manuel Mañas

We construct Darboux transformations for the super-symmetric KP hierarchies of Manin–Radul and Jacobian types. We also consider the binary Darboux transformation for the hierarchies. The iterations of both type of Darboux transformations are briefly discussed.

پایان نامه :وزارت علوم، تحقیقات و فناوری - دانشگاه صنعتی اصفهان 1390

we commence by using from a new norm on l1(g) the -algebra of all integrable functions on locally compact group g, to make the c-algebra c(g). consequently, we find its dual b(g), which is a banach algebra so-called fourier-stieltjes algebra, in the set of all continuous functions on g. we consider most of important basic theorems about this algebra. this consideration leads to a rather com...

2003
Michael Pitz Hermann Ney

We have shown previously that vocal tract normalization (VTN) results in a linear transformation in the cepstral domain. In this paper we show that Mel-frequency warping can equally well be integrated into the framework of VTN as linear transformation on the cepstrum. We show examples of transformation matrices to obtain VTN warped Mel-frequency cepstral coefficients (VTN-MFCC) as linear transf...

2012
Soji Yamakawa Kenji Shimada

This paper presents a new computational method for identifying side faces of thin-walled solids that can be excluded from the first step of conformal transformation from a tet mesh to an all-hex mesh. By excluding such side faces, all-hex meshes created by the conformal transformation method better align with the boundary of the side faces and tend to exhibit better scaled Jacobian quality. The...

Journal: :CoRR 2014
Laurent Dinh David Krueger Yoshua Bengio

We propose a deep learning framework for modeling complex high-dimensional densities via Nonlinear Independent Component Estimation (NICE). It is based on the idea that a good representation is one in which the data has a distribution that is easy to model. For this purpose, a non-linear deterministic transformation of the data is learned that maps it to a latent space so as to make the transfo...

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