Non-differentiable variational principles

We develop a calculus of variations for functionals which are defined on a set of non-differentiable curves. We first extend the classical differential calculus in a quantum calculus, which allows us to define a complex operator, called the scale derivative, which is the non-differentiable analogue of the classical derivative. We then define the notion of extremals for our functionals and obtain a characterization in term of a generalized Euler-Lagrange equation. We finally prove that solutions of the Schrödinger equation can be obtained as extremals of a non-differentiable variational principle, leading to an extended Hamilton's principle of least action for quantum mechanics. We compare this approach with the scale relativity theory of Nottale, which assumes a fractal structure of space-time.     

Binary Quasi-Cyclic Goppa Codes

We obtain here a necessary and sufficient condition for a certain class of binary Goppa code to be quasi-cyclic. We also give another sufficient condition which is easier to check. We define a class of quasi-cyclic Goppa codes. We find the true dimension for a part of those quasi-cyclic codes. and also a class of extended quasi-cyclic codes the minimum distance of which is equal to the designed distance.     

Isoperimetric Inequalities for Soluble Groups

We approach the question of which soluble groups are automatic. We describe a class of nilpotent-by-Abelian groups which need to be studied in order to answer this question. We show that the nilpotent-by-cyclic groups in this class have exponential isoperimetric inequality and so cannot be automatic.     

A Polyhedral Approach for Nonconvex Quadratic Programming Problems with Box Constraints

We apply a linearization technique for nonconvex quadratic problems with box constraints. We show that cutting plane algorithms can be designed to solve the equivalent problems which minimize a linear function over a convex region. We propose several classes of valid inequalities of the convex region which are closely related to the Boolean quadric polytope. We also describe heuristic procedures for generating cutting planes. Results of preliminary computational experiments show that our inequalities generate a polytope which is a fairly tight approximation of the convex region.     

Numerical Schemes for Linear and Non-Linear Enhancement of DW-MRI

We consider the linear and non-linear enhancement of diffusion weighted magnetic resonance images (DW-MRI) to use contextual information in denoising and inferring fiber crossings. We describe the space of DW-MRI images in a moving frame of reference, attached to fiber fragments which allows for convection-diffusion along the fibers. Because of this approach, our method is naturally able to handle crossings in data. We will perform experiments showing the ability of the enhancement to infer information about crossing structures, even in diffusion tensor images (DTI) which are incapable of representing crossings themselves. We will present a novel non-linear enhancement technique which performs better than linear methods in areas around ventricles, thereby eliminating the need for additional preprocessing steps to segment out the ventricles. We pay special attention to the details of implementation of the various numerical schemes.     

A unified approach on Springer fibers in the hook, two-row and two-column cases

We consider the Springer fiber over a nilpotent endomorphism. Fix a Jordan basis and consider the standard torus relative to this. We deal with the problem of describing the flags fixed by the torus which belong to a given component of the Springer fiber. We solve the problem in the hook, two-row and two-column cases. We provide two main characterizations which are common to the three cases, and which involve dominance relations between Young diagrams and combinatorial algorithms. Then, for these three cases, we deduce topological properties of the components and their intersections.     

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We study the random variables of radial asymmetry based on copulas. We research on the structure of random variables which radial asymmetry degree isand get the exact best-possible bounds of random variables which radial asymmetry degree is equal to. Then we expand to general case. We propose an essential condition of radial asymmetry degree is and study the structure of copula. We provide a broad bounds of copula that the radial asymmetry degree is .     

Critical duality

We look for a general framework in which the Ekeland duality can be formulated. We propose a scheme in which the parameter sets are provided with a coupling function which induces a conjugacy. The decision spaces are not supposed to have any special structure. We examine several examples. In particular, we consider some special classes of generalized convex functions.     

An optimal stocking problem to minimize the expected time to sellout

We consider an assortment planning problem where the objective is to minimize the expected time to sell all items in the assortment. We provide several structural results for the optimal assortment. We present a heuristic policy, which we prove is asymptotically optimal. We also show that there are alternate objective criteria under which the problem simplifies considerably.     

An analysis of the complex dynamic behaviour of nonlinear oligopoly models with time delays

We consider the fate of output in the Cournot oligopoly model when the equilibrium is locally unstable. We discuss types of nonlinearities which may be present to bound the motion and introduce time lags in production and information which serve as bifurcation parameters. We apply the Hopf bifurcation theorem to determine conditions under which limit cycle motion is born, and use computer simulations to investigate the nature of the attractors generated by such models.     

Local overlaps in special unfoldings of convex polyhedra

We define a notion of local overlaps in polyhedron unfoldings. We use this concept to construct convex polyhedra for which certain classes of edge unfoldings contain overlaps, thereby negatively resolving some open conjectures. In particular, we construct a convex polyhedron for which every shortest path unfolding contains an overlap. We also present a convex polyhedron for which every steepest edge unfolding contains an overlap. We conclude by analyzing a broad class of unfoldings and again find a convex polyhedron for which they all contain overlaps.     

Optimal Policies for Investment with Time-Varying Return Distributions

We develop a model in which investors must learn the distribution of asset returns over time. The process of learning is made more difficult by the fact that the distributions are not constant through time. We consider risk-neutral investors who have quadratic utility and are selecting between two risky assets. We determine the time at which it is optimal to update the distribution estimate and hence, alter portfolio weights. Our results deliver an optimal policy for asset allocation, that is, the sequence of time intervals at which it is optimal to switch between assets, based on stochastic optimal control theory. In addition, we determine the time intervals in which asset switching leads to a loss with high probability. We provide estimates of the effectiveness of the optimal policy.     

Self-organized criticality and partial synchronization in an evolving network

We describe an evolving network type model of stock market, and present numerical results. Recent works on Self-organized criticality in pulse coupled relaxation oscillators have shown SOC to be related to frustrated attempts of the system to synchronise. Other works have shown the emergence of a self-organized control parameter which feeds back onto an order parameter, causing avalanches which separate periods of stasis. We define an all-to-all network of connected spins which also have an attached fitness. We find a self-organized fitness threshold given by the mean fitness, which separates a solid type state from a gaseous type state. We also find a self-organized control parameter given by the fitness deviation. Approach of this parameter to zero causes `avalanches' of partial synchronizations which occur on all sizes, separated by periods of stasis, and re-order the system.     

Stein's idea and minimax admissible estimation of a multivariate normal mean

We consider estimation of a multivariate normal mean vector under sum of squared error loss.We propose a new class of minimax admissible estimator which are generalized Bayes with respect to a prior distribution which is a mixture of a point prior at the origin and a continuous hierarchical type prior. We also study conditions under which these generalized Bayes minimax estimators improve on the James–Stein estimator and on the positive-part James–Stein estimator.     

Temperley-Lieb pfaffinants and Schur Q-positivity conjectures

We study pfaffian analogues of immanants, which we call pfaffinants. Our main object is the TL-pfaffinants which are analogues of Rhoades and Skandera's TL-immanants. We show that TL-pfaffinants are positive when applied to planar networks and explain how to decompose products of complementary pfaffians in terms of TL-pfaffinants. We conjecture in addition that TL-pfaffinants have positivity properties related to Schur Q-functions.     

Analysis of a Class of Frictional Contact Problems for the Bingham Fluid

We consider a mathematical model which describes the stationary flow of a Bingham fluid with friction. The frictional contact is modeled by a general velocity dependent dissipation functional. We derive a weak formulation of the model which consists in a variational inequality for the velocity field. We establish the existence and uniqueness of the weak solution as well as its continuous dependence with respect to the contact condition. Finally, we describe a number of concrete friction conditions which may be set in this general framework and for which our results apply.     

Reduction and construction of exact solutions for a nonlinear system of the parabolic type

We study a system of two equations of the parabolic type with two nonlinearities depending on the sum of squares of two unknown functions. We derive conditions under which the system can be reduced to a single equation. We indicate conditions under which this equation can be reduced to a linear heat equation or to semilinear equations. We construct parametric families of exact solutions defined by elementary functions. We derive a control law providing the existence of a wide class of functions that can be realized as exact solutions.     

Rollout Algorithms for Stochastic Scheduling Problems

Stochastic scheduling problems are difficult stochastic control problems with combinatorial decision spaces. In this paper we focus on a class of stochastic scheduling problems, the quiz problem and its variations. We discuss the use of heuristics for their solution, and we propose rollout algorithms based on these heuristics which approximate the stochastic dynamic programming algorithm. We show how the rollout algorithms can be implemented efficiently, with considerable savings in computation over optimal algorithms. We delineate circumstances under which the rollout algorithms are guaranteed to perform better than the heuristics on which they are based. We also show computational results which suggest that the performance of the rollout policies is near-optimal, and is substantially better than the performance of their underlying heuristics.     

A Baer-Krull Theorem for Quasi-Ordered Groups

We give group analogs of two important theorems of real algebra concerning convex valuations, one of which is the Baer-Krull theorem. We do this by using quasi-orders, which gives a uniform approach to valued and ordered groups. We also recover the classical Baer-Krull theorem from its group analog.