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In the paper, some concepts of modern differential geometry are used as a basis to develop an invariant theory of mechanical systems, including systems with gyroscopic forces. An interpretation of systems with gyroscopic forces in the form…

Differential Geometry · Mathematics 2014-02-03 M. P. Kharlamov

This dissertation presents a multifaceted look into the structural decomposition of permutation classes. The theory of permutation patterns is a rich and varied field, and is a prime example of how an accessible and intuitive definition…

Combinatorics · Mathematics 2014-10-13 Cheyne Homberger

The aim of this work is to establish the existence of invariant manifolds in complex systems. Considering trajectory curves integral of multiple time scales dynamical systems of dimension two and three (predator-prey models, neuronal…

Dynamical Systems · Mathematics 2014-08-19 Jean-Marc Ginoux , Bruno Rossetto

We investigate the representation of symmetric polynomials as a sum of squares. Since this task is solved using semidefinite programming tools we explore the geometric, algebraic, and computational implications of the presence of discrete…

Commutative Algebra · Mathematics 2007-05-23 Karin Gatermann , Pablo A. Parrilo

The integrability condition called shape invariance is shown to have an underlying algebraic structure and the associated Lie algebras are identified. These shape-invariance algebras transform the parameters of the potentials such as…

Quantum Physics · Physics 2009-10-30 A. B. Balantekin

Decidability and synthesis of inductive invariants ranging in a given domain play an important role in many software and hardware verification systems. We consider here inductive invariants belonging to an abstract domain $A$ as defined in…

Programming Languages · Computer Science 2020-07-14 Francesco Ranzato

A system is invariant with respect to an input transformation if we can transform any dynamic input by this function and obtain the same output dynamics after adjusting the initial conditions appropriately. Often, the set of all such input…

Dynamical Systems · Mathematics 2021-03-02 Moritz Lang

We consider tilings of Euclidean spaces by polygons or polyhedra, in particular, tilings made by a substitution process, such as the Penrose tilings of the plane. We define an isomorphism invariant related to a subgroup of rotations and…

Dynamical Systems · Mathematics 2018-07-10 Charles Radin , Lorenzo Sadun

We investigate functionals defined on manifolds through parameterizations. If they are to be meaningful, from a geometrical viewpoint, they ought to be invariant under reparameterizations. Standard, local, integral functionals with this…

Differential Geometry · Mathematics 2024-11-08 Pablo Pedregal

Moment invariants are a powerful tool for the generation of rotation-invariant descriptors needed for many applications in pattern detection, classification, and machine learning. A set of invariants is optimal if it is complete,…

Computer Vision and Pattern Recognition · Computer Science 2025-04-04 Roxana Bujack , Emily Shinkle , Alice Allen , Tomas Suk , Nicholas Lubbers

In [Trace identities and $\bf {Z}/2\bf {Z}$-graded invariants, {\it Trans. Amer. Math. Soc. \bf309} (1988), 581--589] we generalized the first and second fundamental theorems of invariant theory from the general linear group to the general…

Rings and Algebras · Mathematics 2010-10-22 Allan Berele

Three new graph invariants are introduced which may be measured from a quantum graph state and form examples of a framework under which other graph invariants can be constructed. Each invariant is based on distinguishing a different number…

Quantum Physics · Physics 2019-11-20 P. W. Mills , R. P. Rundle , J. H. Samson , Simon J. Devitt , Todd Tilma , V. M. Dwyer , Mark J. Everitt

Loop invariants are software properties that hold before and after every iteration of a loop. As such, invariants provide inductive arguments that are key in automating the verification of program loops. The problem of generating loop…

Logic in Computer Science · Computer Science 2023-05-25 George Kenison , Laura Kovács , Anton Varonka

Random invariant manifolds are geometric objects useful for understanding complex dynamics under stochastic influences. Under a nonuniform hyperbolicity or a nonuniform exponential dichotomy condition, the existence of random pseudo-stable…

Dynamical Systems · Mathematics 2009-01-06 Tomas Caraballo , Jinqiao Duan , Kening Lu , Bjorn Schmalfuss

In this work we derive important properties regarding matrix invariants which occur in the theory of differential equations with reflection.

Classical Analysis and ODEs · Mathematics 2018-12-26 Santiago Codesido , F. Adrián F. Tojo

In this paper we describe the algebra of differential invariants for GL(n,C)-structures. This leads to classification of almost complex structures of general positions. The invariants are applied to the existence problem of…

Differential Geometry · Mathematics 2007-12-21 Boris Kruglikov

Recognizing the actions of others from visual stimuli is a crucial aspect of human visual perception that allows individuals to respond to social cues. Humans are able to identify similar behaviors and discriminate between distinct actions…

Neurons and Cognition · Quantitative Biology 2018-02-07 Andrea Tacchetti , Leyla Isik , Tomaso Poggio

When solving data analysis problems it is important to integrate prior knowledge and/or structural invariances. This paper contributes by a novel framework for incorporating algebraic invariance structure into kernels. In particular, we…

Machine Learning · Statistics 2014-12-01 Franz J. Király , Andreas Ziehe , Klaus-Robert Müller

One of the most challenging problems in the domain of 2-D image or 3-D shape is to handle the non-rigid deformation. From the perspective of transformation groups, the conformal transformation is a key part of the diffeomorphism. According…

Graphics · Computer Science 2018-08-31 He Zhang , Hanlin Mo , You Hao , Qi Li , Hua Li

The study of representations invariant to common transformations of the data is important to learning. Most techniques have focused on local approximate invariance implemented within expensive optimization frameworks lacking explicit…

Machine Learning · Computer Science 2017-02-27 Dipan K. Pal , Marios Savvides