arXiv research

Methodology monitors processes using system call count vectors.

Generative x-vectors improve SV performance.

New linear spectral estimators improve phase retrieval accuracy.

The aim of this paper is to prove that a control affine system on a manifold is equivalent by diffeomorphism to a linear system on a Lie group or a homogeneous space if and only the vector fields of the system are complete and generate a finite dimensional Lie algebra. A vector field on a connected Lie group is linear …

HybridRAG combines KGs and vector retrieval for financial document Q&A.

A Lie system is a system of first-order ordinary differential equations describing the integral curves of a $t$-dependent vector field taking values in a finite-dimensional real Lie algebra of vector fields: a so-called Vessiot-Guldberg Lie algebra. We suggest the definition of a particular class of Lie systems, the $k…

New geometric methods find constants and tensors for Lie systems.

A theorem of Maurer-Cartan type for Lie algebroids is presented. Suppose that any vector subbundle of a Lie algebroid is called interior differential system (IDS) for that Lie algebroid. A theorem of Cartan type is obtained. Extending the classical notion of exterior differential system (EDS) to Lie algebroids, a theor…

Method proves connection stability of vector fields on noncompact manifolds.

CVF learns stable dynamical systems from trajectories.

Study investigates Hamiltonian systems in fibered almost-symplectic manifolds.

A new clustering method for vector time series using autoregressive dynamics.

Reduces multisymplectic Lie systems through symmetry analysis.

Proposes a RL method using simulators for stabilizing uncertain systems.

Paper introduces Eden bracket for nonholonomic systems.

In this paper, for a variety of nonholonomic (reducible) Hamiltonian systems, we first give to various distributional Hamiltonian systems, by analyzing carefully the dynamics and structures of the nonholonomic Hamiltonian systems. Secondly, we derive precisely the geometric constraint conditions of the induced distribu…

Study magnetic Hamiltonian systems with constraints, deriving Hamilton-Jacobi equations.

We construct a special class of Lorentz surfaces in the pseudo-Euclidean 4-space with neutral metric which are one-parameter systems of meridians of rotational hypersurfaces with timelike or spacelike axis and call them meridian surfaces. We give the complete classification of the meridian surfaces with parallel mean c…

We define and study invariants which can be uniformly constructed for any gauge system. By a gauge system we understand an (anti-)Poisson supermanifold provided with an odd Hamiltonian self-commuting vector field called a homological vector field. This definition encompasses all the cases usually included into the noti…

The category of generalized Lie algebroids is presented. We obtain an exterior differential calculus for generalized Lie algebroids. In particular, we obtain similar results with the classical and modern results for Lie algebroids. So, a new result of Maurer-Cartan type is presented. Supposing that any vector subbundle…

Paper connects dynamics of mechanical systems to Reeb dynamics.

This paper studies nonholonomic constraints in Hamiltonian systems, deriving equations and theorems.

This paper studies Hamilton-Jacobi equations for magnetic systems with constraints.

Just as an explicit parameterisation of system dynamics by state, i.e., a choice of coordinates, can impede the identification of general structure, so it is too with an explicit parameterisation of system dynamics by control. However, such explicit and fixed parameterisation by control is commonplace in control theory…

In this paper, we give precisely the geometric constraint conditions of canonical symplectic form and regular reduced symplectic forms for the dynamical vector fields of a regular controlled Hamiltonian (RCH) system and its regular reduced systems, which are called the Type I and Type II of Hamilton-Jacobi equations. A…

Recently a variety of LSTM-based conditional language models (LM) have been applied across a range of language generation tasks. In this work we study various model architectures and different ways to represent and aggregate the source information in an end-to-end neural dialogue system framework. A method called snaps…

This paper explores coordinates adapted to vector fields on smooth manifolds.

We construct a special class of Lorentz surfaces in the pseudo-Euclidean 4-space with neutral metric which are one-parameter systems of meridians of rotational hypersurfaces with lightlike axis and call them meridian surfaces. We give the complete classification of the meridian surfaces with constant Gauss curvature an…

It is of fundamental importance to find algorithms obtaining optimal performance for learning of statistical models in distributed and communication limited systems. Aiming at characterizing the optimal strategies, we consider learning of Gaussian Processes (GPs) in distributed systems as a pivotal example. We first ad…

A dynamical system on the total space of the fibre bundle of second order accelerations, $T^2M$, is defined as a third order vector field $S$ on $T^2M$, called semispray, which is mapped by the second order tangent structure into one of the Liouville vector field. For a regular Lagrangian of second order we prove that …

The paper connects geometric structures to mechanical systems and introduces new numerical methods.

A new method classifies heart sounds using i-vectors and machine learning.

We investigate connections between information-theoretic and estimation-theoretic quantities in vector Poisson channel models. In particular, we generalize the gradient of mutual information with respect to key system parameters from the scalar to the vector Poisson channel model. We also propose, as another contributi…

Characterizes winding of braided vector fields in tubular domains.

New symmetries found for scalar and vector ODEs of arbitrary dimensions.

Study timelike meridian surfaces in Minkowski 4-space with specific properties.

An important step in speaker verification is extracting features that best characterize the speaker voice. This paper investigates a front-end processing that aims at improving the performance of speaker verification based on the SVMs classifier, in text independent mode. This approach combines features based on conven…

Study timelike surfaces with parallel mean curvature in Minkowski 4-space.

It is well known that the compactifications of the canonical contact systems living on real jet spaces $J^{\,r}(1,1)$, $r \ge 2$, are locally universal Goursat distributions, $Δ^r$, living on compact manifolds (called Goursat monsters) having open dense jet-like ($J^{\,r}(1,1)$-like) parts. By virtue of the results of …

Contact Lie systems analyze integral curves of Hamiltonian vector fields.

This paper deals with some basic constructions of linear and multilinear algebra on finite-dimensional diffeological vector spaces. We consider the diffeological dual formally checking that the assignment to each space of its dual defines a covariant functor from the category of finite-dimensional diffeological vector …

Improved speaker diarization with LSTM and d-vectors.

Saec compresses recommendation system embeddings by clustering similar features.

Paper constructs various algebroids using n-systems and metric n-systems.

We introduce the concept of bi-conformal transformation, as a generalization of conformal ones, by allowing two orthogonal parts of a manifold with metric $\G$ to be scaled by different conformal factors. In particular, we study their infinitesimal version, called bi-conformal vector fields. We show the differential co…

Efficiently integrates stiff ODEs with vectorized methods.

It is well known that Lagrangian dynamical systems naturally arise in describing wave front dynamics in the limit of short waves (which is called pseudoclassical limit or limit of geometrical optics). Wave fronts are the surfaces of constant phase, their points move along lines which are called rays. In non-homogeneous…

Paper uses sparse learning to estimate quasi-potential and drift components in stochastic systems.