Determining parameters which describe the performance of a solid oxide fuel cell requires the solution of an inverse problem. Two formulations have been presented in the literature; a convolutional approach or a direct quadrature approach. A complete study and analysis of the direct quadrature method, which leads to two systems for the unknown signal given measured complex data, known as the di...

Particle size distribution is one of the important microphysical parameters to characterize aerosol properties. The optical depth used as function wavelength study particle whole atmospheric column. However, inversion equation from belongs Fredholm integral first kind, which usually ill-conditioned. To overcome this drawback, discretized directly by using complex trapezoid formula. Then, corres...

We investigate the use of Tikhonov regularization with the minimum support stabilizer for underdetermined 2-D inversion of gravity data. This stabilizer produces models with nonsmooth properties which is useful for identifying geologic structures with sharp boundaries. A very important aspect of using Tikhonov regularization is the choice of the regularization parameter that controls the trade ...

The received signal strength (RSS) based Wi-Fi fingerprinting method is one of the most potential and easily deployed approaches for a reliable indoor positioning system. However, due to labor intensive time-consuming radio map construction process, interpolation often incorporated. To ensure interpolated robust against environmental noise RSS fluctuations, we propose two novel methods, termed ...

Joint modeling of language and vision has been drawing increasing interest. A multimodal data representation allowing for bidirectional retrieval of images by sentences and vice versa is a key aspect of this modeling. In this paper we show that a cross-view mapping of the search space to the query space achieves state of the art performance in bidirectional retrieval using off the shelf feature...

Singular value decomposition is the key tool in the analysis and understanding of linear regularization methods in Hilbert spaces. Besides simplifying computations it allows to provide a good understanding of properties of the forward problem compared to the prior information introduced by the regularization methods. In the last decade nonlinear variational approaches such as ` or total variati...

Target Audience Clinicians and researchers who wish to improve the detection and diagnosis accuracy of brain tumor or cerebral disease using MR perfusion. Introduction 4-D dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) is a well-established perfusion technique for non-invasive characterization of tissue dynamics, with promising applications in assessing a wide range of d...

The reconstruction methods for solving the ill-posed inverse problem of photoacoustic tomography with limited noisy data are iterative in nature to provide accurate solutions. These performance is highly affected by noise level data. A singular value decomposition (SVD) based plug and play priors method was proposed this work robustness shown be superior as compared total variation regularizati...