Linear Quadratic Approximations Research Articles

Quadratic blind linear unmixing: A graphical user interface for tissue characterization

Spectral unmixing is the process of breaking down data from a sample into its basic components and their abundances. Previous work has been focused on blind unmixing of multi-spectral fluorescence lifetime imaging microscopy (m-FLIM) datasets under a linear mixture model and quadratic approximations. This method provides a fast linear decomposition and can work without a limitation in the maximum number of components or end-members. Hence this work presents an interactive software which implements our blind end-member and abundance extraction (BEAE) and quadratic blind linear unmixing (QBLU) algorithms in Matlab. The options and capabilities of our proposed software are described in detail. When the number of components is known, our software can estimate the constitutive end-members and their abundances. When no prior knowledge is available, the software can provide a completely blind solution to estimate the number of components, the end-members and their abundances. The characterization of three case studies validates the performance of the new software: ex-vivo human coronary arteries, human breast cancer cell samples, and in-vivo hamster oral mucosa. The software is freely available in a hosted webpage by one of the developing institutions, and allows the user a quick, easy-to-use and efficient tool for multi/hyper-spectral data decomposition.

Kinematic feedback control laws for generating natural arm movements

We propose a stochastic optimal feedback control law for generating natural robot arm motions. Our approach, inspired by the minimum variance principle of Harris and Wolpert (1998 Nature 394 780–4) and the optimal feedback control principles put forth by Todorov and Jordan (2002 Nature Neurosci. 5 1226–35) for explaining human movements, differs in two crucial respects: (i) the endpoint variance is minimized in joint space rather than Cartesian hand space, and (ii) we ignore the dynamics and instead consider only the second-order differential kinematics. The feedback control law generating the motions can be straightforwardly obtained by backward integration of a set of ordinary differential equations; these equations are obtained exactly, without any linear–quadratic approximations. The only parameters to be determined a priori are the variance scale factors, and for both the two-DOF planar arm and the seven-DOF spatial arm, a table of values is constructed based on the given initial and final arm configurations; these values are determined via an optimal fitting procedure, and consistent with existing findings about neuromuscular motor noise levels of human arm muscles. Experiments conducted with a two-link planar arm and a seven-DOF spatial arm verify that the trajectories generated by our feedback control law closely resemble human arm motions, in the sense of producing nearly straight-line hand trajectories, having bell-shaped velocity profiles, and satisfying Fitts Law.

Optimal Monetary Policy Under Uncertainty: A Markov Jump-Linear-Quadratic Approach

This paper studies the design of optimal monetary policy under uncertainty using a Markov jumplinear-quadratic (MJLQ) approach. To approximate the uncertainty that policymakers face, the authors use different discrete modes in a Markov chain and take mode-dependent linear-quadratic approximations of the underlying model. This allows the authors to apply a powerful methodology with convenient solution algorithms that they have developed. They apply their methods to analyze the effects of uncertainty and potential gains from experimentation for two sources of uncertainty in the New Keynesian Phillips curve. The examples highlight that learning may have sizable effects on losses and, although it is generally beneficial, it need not always be so. The experimentation component typically has little effect and in some cases it can lead to attenuation of policy. (JEL E42, E52, E58)

On Linear-Quadratic Approximations

We prove the generality of the methodology proposed in Benigno and Woodford (2006). We show that, even in the presence of a distorted steady state, it is always possible and relatively simple to obtain a purely quadratic approximation to the welfare measure. We also show that, in order to do so, the timeless perspective assumption is crucial.

A Comparison of Angular Difference Schemes for One-Dimensional Spherical Geometry SN Equations

To investigate errors caused by angular differencing in approximating the streaming terms of the transport equation, five different approximations are evaluated for three test problems in one-dimensional spherical geometry. The following schemes are compared: diamond, special truncation error minimizing weighted diamond, linear continuous (the original SN scheme), linear discontinuous, and new quadratic continuous. To isolate errors caused by angular differencing, the approximations are derived from the transport equation without spatial differencing, and the resulting coupled ordinary differential equations (ODEs) are solved with an ODE solver. Results from the approximations are compared with analytic solutions derived for two-region purely absorbing spheres. Most of the approximations are derived by taking moments of the conservation form of the transport equation. The quadratic continuous approximation is derived taking the zeroth moment of both the transport equation and the first angular derivative of the transport equation. The advantages of this approach are described. In all of the approximations, the desirability is shown of using an initializing computation of the μ = -1 angular flux to correctly compute the central flux and of having a difference approximation that ensures this central flux is the same for all directions. The behavior of the standard discrete ordinates equations in the diffusion limit is reviewed, and the linear and quadratic continuous approximations are shown to have the correct diffusion limit if an equal interval discrete quadrature is used.In all three test problems, the weighted diamond difference approximation has smaller maximum and average relative flux errors than the diamond or the linear continuous difference approximations. The quadratic continuous approximation and the linear discontinuous approximation are both more accurate than the other approximations, and the quadratic continuous approximation has a decided edge over the linear discontinuous approximation in relative flux errors. The diamond, weighted diamond, and linear continuous approximations show quadratic system absorption and system leakage error reduction behavior with increasing N. The linear discontinuous and quadratic continuous approximations show fourth-order error reduction in these quantities. In one of the two-region test problems, the slope of the exact angular flux changes from nearly vertical to nearly horizontal at those points in the exterior region at which the interior region source just becomes visible. At these spatial points, errors in the continuous approximations propagate to each successive outgoing direction, leading to an oscillatory spatial error. The discontinuous approximation does not propagate these errors, although errors near the point of rapid slope change are larger than in the quadratic continuous approximation.

A novel approach for the stochastic effects of radiation on cell survival

A cell subjected to radiation damage could survive if the radiation induced lesions are repaired correctly or survive as a mutant if repaired incorrectly or die which is reflected by its inability to divide. In this paper we develop a stochastic model to analyse the effects of radiation on living cells incorporating the rates of lesion induction, damaged DNA replication and rates of repair, misrepair and death. The cell survival probability is explicitly obtained and is shown to be a concave function of the dose so that the obtained cell survival probability exhibits a “shoulder”. Also the number distribution of the potential lethal lesions which forms the core of cell studies is obtained. A brief comparison with other existing models has also been made. In particular, well known models of Neyman and Puri (1981) and Yang and Swenberg (1991) are obtained from our model and our results are in agreement with theirs. A linear-quadratic approximations for the cell survival probability as a function of dose is made. The model is shown to give sufficiently good fit for the survival data of EAT and CHO cells irradiated with different doses of UV-radiation and x-rays (Iliakis and Nusse (1982), Metting et. al. (1985))