Physical correction filter for improving the optical quality of an image

A family of physical correction filters is described. Each filter is designed to correct image content of a photographed scene of limited resolution and includes a first filter element with a pinhole through which light passes to a differential amplifier. A second filter element through which light passes through one or more openings, whose geometric configuration is a function of the cause of the resolution loss included. The light, passing through the second filter element, is also supplied to the differential amplifier whose output is used to activate an optical display or recorder to reproduce a photograph or display of the scene in the original photograph or display of the scene in the original photograph with resolution which is significantly greater than that characterizing the original photograph

Hamiltonian approach to slip-stacking dynamics

Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stacking efficiency. The dynamics are applied specifically to the Fermilab Booster-Recycler complex. The dynamics can also be applied to other accelerator complexes.Comment: 10 p

Explicit inverse Fourier transformation of a rational function and a new theorem

Explicit inverse Fourier transformation of rational function with new theore

Nonparametric tests of conditional treatment effects

We develop a general class of nonparametric tests for treatment effects conditional on covariates. We consider a wide spectrum of null and alternative hypotheses regarding conditional treatment effects, including (i) the null hypothesis of the conditional stochastic dominance between treatment and control groups; ii) the null hypothesis that the conditional average treatment effect is positive for each value of covariates; and (iii) the null hypothesis of no distributional (or average) treatment effect conditional on covariates against a one-sided (or two-sided) alternative hypothesis. The test statistics are based on L1-type functionals of uniformly consistent nonparametric kernel estimators of conditional expectations that characterize the null hypotheses. Using the Poissionization technique of Giné et al. (2003), we show that suitably studentized versions of our test statistics are asymptotically standard normal under the null hypotheses and also show that the proposed nonparametric tests are consistent against general fixed alternatives. Furthermore, it turns out that our tests have non-negligible powers against some local alternatives that are n−½ different from the null hypotheses, where n is the sample size. We provide a more powerful test for the case when the null hypothesis may be binding only on a strict subset of the support and also consider an extension to testing for quantile treatment effects. We illustrate the usefulness of our tests by applying them to data from a randomized, job training program (LaLonde, 1986) and by carrying out Monte Carlo experiments based on this dataset