Scattering correction using continuously thickness-adapted kernels

Analog Forecasting with Dynamics-Adapted Kernels

Analog forecasting is a nonparametric technique introduced by Lorenz in 1969 which predicts the evolution of states of a dynamical system (or observables defined on the states) by following the evolution of the sample in a historical record of observations which most closely resembles the current initial data. Here, we introduce a suite of forecasting methods which improve traditional analog fo...

Determining the accuracy of measuring the thickness of steel plates using Compton scattering method

When there is limitation access to one side of the structure in industry, one of the best methods for thickness measurements is the Compton scattering. In this paper, due to the statistical behavior of dispersed beam counting, we discuss the accuracy of the measurement for steel thickness. Using the experimental method and comparing it with MCNP simulation code, the accuracy is obtained less th...

Texture Retrieval Using Scattering Coefficients and Probability Product Kernels

In this paper we introduce a content based image retrieval system that leverages the benefits of the scattering transform as a means of feature extraction. To measure similarity between feature vectors, we adapt a probability product kernel and derive an approximate version which can be implemented efficiently. The proposed approach achieves a retrieval performance superior to comparable filter...

Learning Convex Combinations of Continuously Parameterized Basic Kernels

We study the problem of learning a kernel which minimizes a regularization error functional such as that used in regularization networks or support vector machines. We consider this problem when the kernel is in the convex hull of basic kernels, for example, Gaussian kernels which are continuously parameterized by a compact set. We show that there always exists an optimal kernel which is the co...

Quantum error correction for continuously detected errors