32,495 research outputs found

    Direct 3D Tomographic Reconstruction and Phase-Retrieval of Far-Field Coherent Diffraction Patterns

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    We present an alternative numerical reconstruction algorithm for direct tomographic reconstruction of a sample refractive indices from the measured intensities of its far-field coherent diffraction patterns. We formulate the well-known phase-retrieval problem in ptychography in a tomographic framework which allows for simultaneous reconstruction of the illumination function and the sample refractive indices in three dimensions. Our iterative reconstruction algorithm is based on the Levenberg-Marquardt algorithm. We demonstrate the performance of our proposed method with simulation studies

    OPED reconstruction algorithm for limited angle problem

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    The structure of the reconstruction algorithm OPED permits a natural way to generate additional data, while still preserving the essential feature of the algorithm. This provides a method for image reconstruction for limited angel problems. In stead of completing the set of data, the set of discrete sine transforms of the data is completed. This is achieved by solving systems of linear equations that have, upon choosing appropriate parameters, positive definite coefficient matrices. Numerical examples are presented.Comment: 17 page

    A Fast Reconstruction Algorithm for Gene Networks

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    This paper deals with gene networks whose dynamics is assumed to be generated by a continuous-time, linear, time invariant, finite dimensional system (LTI) at steady state. In particular, we deal with the problem of network reconstruction in the typical practical situation in which the number of available data is largely insufficient to uniquely determine the network. In order to try to remove this ambiguity, we will exploit the biologically a priori assumption of network sparseness, and propose a new algorithm for network reconstruction having a very low computational complexity (linear in the number of genes) so to be able to deal also with very large networks (say, thousands of genes). Its performances are also tested both on artificial data (generated with linear models) and on real data obtained by Gardner et al. from the SOS pathway in Escherichia coli.Comment: 12 pages, 3 figure

    Validity of using the Sheffield algorithm for the Sussex EIT MK4

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    This paper introduces the image reconstruction algorithm from Sheffield group and the validity of this algorithm to the Sussex MK4
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