Nonnegative Convex Research Articles

From Microstructure-Independent Formulas for Composite Materials to Rank-One Convex, Non-quasiconvex Functions

Examples of non-quasiconvex functions that are rank-one convex are rare. In this paper we construct a family of such functions by means of the algebraic methods of the theory of exact relations for polycrystalline composite materials, developed to identify G-closed sets of positive codimensions. The algebraic methods are used to construct a set of materials of positive codimension that is closed under lamination but is not G-closed. The well-known link between G-closed sets and quasiconvex functions and sets closed under lamination and rank-one convex functions is then used to construct a family of rotationally invariant, nonnegative, and 2-homogeneous rank-one convex functions, that are not quasiconvex.

Inertia of some special matrices

There have been several articles in literature that study the spectral behaviour of special classes of matrices such as the matrices based on power function given by the matrices , the matrices for positive values of r and positive real numbers . Bhatia and Jain in 2015 and Dyn, Goodman and Micchelli in 1986 have studied the spectral behaviour of and , respectively, for all real values of r. The power function is operator monotone when and operator convex when . It is natural to study the inertia of all these matrices when the power function is replaced by any operator monotone or operator convex function. In the present work, inertia of the matrices and is discussed for non-negative operator monotone and operator convex function f, which further leads to many known and new results.

Walkr: MCMC Sampling from Non-Negative Convex Polytopes

walkr: MCMC Sampling from Non-Negative Convex Polytopes

Super-replication of European Options with Convex Payoff under Proportional Transaction Costs

The paper examines the super-replication of contingent claims in a discrete time financial market with proportional transaction costs. The sole assumption on stock price dynamics is that the returns are bounded. The class of path-dependent European options with nonnegative convex payoff functions is considered. It is proved that the pricing of this type of options can be studied through the pricing of a suitable binomial model. As a consequence, it is shown that the pricing algorithm, which is essentially a dynamic programming procedure on a tree, can be used when the set of possible scenarios is not finite.

Multivariate stochastic dominance for risk averters and risk seekers

This paper first extends some well-known univariate stochastic dominance results to multivariate stochastic dominances (MSD) for both risk averters and risk seekers, respectively, to n order for any n ≥ 1 when the attributes are assumed to be independent and the utility is assumed to be additively and separable. Under these assumptions, we develop some properties for MSD for both risk averters and risk seekers. For example, we prove that MSD are equivalent to the expected-utility maximization for both risk averters and risk seekers, espectively. We show that the hierarchical relationship exists for MSD. We establish some dual relationships between the MSD for risk averters and risk seekers. We develop some properties for non-negative combinations and convex combinations random variables of MSD and develop the theory of MSD for the preferences of both risk averters and risk seekers on diversification. At last, we discuss some MSD relationships when attributes are dependent and discuss the importance and the use of the results developed in this paper.

Amoebas, nonnegative polynomials and sums of squares supported on circuits

We completely characterize sections of the cones of nonnegative polynomials, convex polynomials and sums of squares with polynomials supported on circuits, a genuine class of sparse polynomials. In particular, nonnegativity is characterized by an invariant, which can be immediately derived from the initial polynomial. Furthermore, nonnegativity of such polynomials f coincides with solidness of the amoeba of f, i.e., the Log-absolute-value image of the algebraic variety $${\mathcal {V}} (f) \subset (\mathbb {C}^*)^n$$ V ( f ) ⊂ ( C ∗ ) n of f. These results generalize earlier works both in amoeba theory and real algebraic geometry by Fidalgo, Kovacec, Reznick, Theobald and de Wolff and solve an open problem by Reznick. They establish the first direct connection between amoeba theory and nonnegativity of real polynomials. Additionally, these statements yield a completely new class of nonnegativity certificates independent from sums of squares certificates.

Finding a maximal element of a non-negative convex set through its characteristic cone: an application to finding a strictly complementary solution

In order to express a polyhedron as the Minkowski sum of a polytope and a polyhedral cone, Motzkin (Beitrage zur Theorie der linearen Ungleichungen. Dissertation, University of Basel, 1936) devised a homogenization technique that translates the polyhedron to a polyhedral cone in one higher dimension. Refining his technique, we present a conical representation of a set in the Euclidean space. Then, we use this representation to reach four main results: First, we establish a convex programming based framework for determining a maximal element—an element with the maximum number of positive components—of a non-negative convex set—a convex set in the non-negative Euclidean orthant. Second, we develop a linear programming problem for finding a relative interior point of a polyhedron. Third, we propose two procedures for identifying a strictly complementary solution in linear programming. Finally, we generalize Motzkin’s (Beitrage zur Theorie der linearen Ungleichungen. Dissertation, University of Basel, 1936) representation theorem for a class of closed convex sets in the Euclidean space.

Partially ordered rings II

This paper is a continuation of [6]. We study partially ordered rings in terms of non-negative semi-cones and convex ideals, considering order-preserving homomorphisms, residue class rings, and certain product rings, etc.

Continued fractions built from convex sets and convex functions

In a partially ordered semigroup with the duality (or polarity) transform, it is possible to define a generalization of continued fractions. General sufficient conditions for convergence of continued fractions are provided. Two particular applications concern the cases of convex sets with the Minkowski addition and the polarity transform and the family of non-negative convex functions with the Legendre–Fenchel and Artstein-Avidan–Milman transforms.

Fast Non-Negative Orthogonal Matching Pursuit

One of the important classes of sparse signals is the non-negative signals. Many algorithms have already been proposed to recover such non-negative representations, where greedy and convex relaxed algorithms are among the most popular methods. The greedy techniques have been modified to incorporate the non-negativity of the representations. One such modification has been proposed for Orthogonal Matching Pursuit (OMP), which first chooses positive coefficients and uses a non-negative optimisation technique as a replacement for the orthogonal projection onto the selected support. Beside the extra computational costs of the optimisation program, it does not benefit from the fast implementation techniques of OMP. These fast implementations are based on the matrix factorisations. We here first investigate the problem of positive representation, using pursuit algorithms. We will then describe a new implementation, which can fully incorporate the positivity constraint of the coefficients, throughout the selection stage of the algorithm. As a result, we present a novel fast implementation of the Non-Negative OMP, which is based on the QR decomposition and an iterative coefficients update. We will empirically show that such a modification can easily accelerate the implementation by a factor of ten in a reasonable size problem.

The upper bound for Sugeno integral of nonnegative convex functions

The upper bound for Sugeno integral of nonnegative convex functions

Operator P-class functions

Abstract We introduce and investigate the notion of an operator P-class function. We show that every nonnegative operator convex function is of operator P-class, but the converse is not true in general. We present some Jensen type operator inequalities involving P-class functions and some Hermite-Hadamard inequalities for operator P-class functions. MSC:47A63, 47A60, 26D15.

Compactness of the space of embedded minimal surfaces with free boundary in three-manifolds with nonnegative Ricci curvature and convex boundary

We prove a lower bound for the first Steklov eigenvalue of embedded minimal hypersurfaces with free boundary in a compact $n$-dimensional Riemannian manifold which has nonnegative Ricci curvature and strictly convex boundary. When $n=3$, this implies an apriori curvature estimate for these minimal surfaces in terms of the geometry of the ambient manifold and the topology of the minimal surface. An important consequence of the estimate is a smooth compactness theorem for embedded minimal surfaces with free boundary when the topological type of these minimal surfaces is fixed.

Tilings of the plane and Thurston semi-norm

We show that the problem of tiling the Euclidean plane with a finite set of polygons (up to translation) boils down to prove the existence of zeros of a non-negative convex function defined on a finite-dimensional simplex. This function is a generalisation, in the framework of branched surfaces, of the Thurston semi-norm originally defined for compact $$3$$ -manifolds.

Conic structure of the non-negative operator convex functions on $(0,\infty)$

The conic structure of the convex cone of non-negative operator convex functions on $(0,\infty)$ (also on $(-1,1)$) is clarified. We completely determine the extreme rays, the closed faces, and the simplicial closed faces of this convex cone.

Global analysis of smooth solutions to a hyperbolic-parabolic coupled system

We investigate a model arising from biology, which is a hyperbolic-parabolic coupled system. First, we prove the global existence and asymptotic behavior of smooth solutions to the Cauchy problem without any smallness assumption on the initial data. Second, if the Hs ∩ L1-norm of initial data is sufficiently small, we also establish decay rates of the global smooth solutions. In particular, the optimal L2 decay rate of the solution and the almost optimal L2 decay rate of the first-order derivatives of the solution are obtained. These results are obtained by constructing a new nonnegative convex entropy and combining spectral analysis with energy methods.

Minimization of a convex functional in a linear system of delay differential equations with fixed ends

A numerical method is proposed for solving the problem of moving a dynamic object described by a system of linear differential-difference equations to the origin with the minimization of a nonnegative convex functional. The method is proved to converge globally to an ?-optimal solution. The ?-optimal solution is understood as an extremal control u(t), t ? [0, T], that moves the system to the ?-neighborhood of the origin.

Nonnegative Mixed-Norm Convex Optimization for Mitotic Cell Detection in Phase Contrast Microscopy

This paper proposes a nonnegative mix-norm convex optimization method for mitotic cell detection. First, we apply an imaging model-based microscopy image segmentation method that exploits phase contrast optics to extract mitotic candidates in the input images. Then, a convex objective function regularized by mix-norm with nonnegative constraint is proposed to induce sparsity and consistence for discriminative representation of deformable objects in a sparse representation scheme. At last, a Support Vector Machine classifier is utilized for mitotic cell modeling and detection. This method can overcome the difficulty in feature formulation for deformable objects and is independent of tracking or temporal inference model. The comparison experiments demonstrate that the proposed method can produce competing results with the state-of-the-art methods.

On norm sub-additivity and super-additivity inequalities for concave and convex functions

Sub-additive and super-additive inequalities for concave and convex functions have been generalized to the case of matrices by several authors over a period of time. These lead to some interesting inequalities for matrices, which in some cases coincide with, and in other cases are at variance with the corresponding inequalities for real numbers. We survey some of these matrix inequalities and do further investigations into these. We introduce the novel notion of dominated majorization between the spectra of two Hermitian matrices B and C, dominated by a third Hermitian matrix A. Based on an explicit formula for the gradient of the sum of the k largest eigenvalues of a Hermitian matrix, we show that under certain conditions dominated majorization reduces to a linear majorization-like relation between the diagonal elements of B and C in a certain basis. We use this notion as a tool to give new, elementary proofs for the sub-additivity inequality for non-negative concave functions first proved by Bourin and Uchiyama and the corresponding super-additivity inequality for non-negative convex functions first proven by Kosem. Finally, we present counterexamples to some conjectures that Ando's inequality for operator convex functions could more generally hold, e.g. for ordinary convex, non-negative functions.

A numerical method for solving an optimal control problem with fixed endpoints of trajectories and a convex functional

We propose a numerical method for solving the problem of taking a nonlinear system to the zero state while minimizing a nonnegative convex functional. The particular cases include the problem of minimizing the consumption of resources or energy. The method is based on the maximum principle and approximations of bodies with some families of simplices. The properties of coverings of bodies with simplices enable us to justify the convergence of the method.