The low-field nuclear magnetic resonance (NMR) technique has been used to probe the pore size distribution and fluid composition in geophysical prospecting related fields. However, speed accuracy of existing numerical inversion methods are still challenging due ill-posed nature first kind Fredholm integral equation contamination noises. This paper proposes a novel algorithm accelerate convergen...

Sparse representation has been extensively investigated for hyperspectral image (HSI) classification and led to substantial improvements in the performance over the traditional methods, such as support vector machine (SVM). However, the existing sparsity-based classification methods typically assume Gaussian noise, neglecting the fact that HSIs are often corrupted by different types of noise in...

Training subjects to step in place on a rotating platform while maintaining a fixed body orientation in space produces a posteffect consisting in inadvertent turning around while stepping in place eyes closed (podokinetic after-rotation, PKAR). We tested the hypothesis that voluntary turning around while stepping in place also produces a posteffect similar to PKAR. Sixteen subjects performed 12...

BACKGROUND When developing risk models for binary data with small or sparse data sets, the standard maximum likelihood estimation (MLE) based logistic regression faces several problems including biased or infinite estimate of the regression coefficient and frequent convergence failure of the likelihood due to separation. The problem of separation occurs commonly even if sample size is large but...

We suggest a method for estimating a covariance matrix on the basis of a sample of vectors drawn from a multivariate normal distribution. In particular, we penalize the likelihood with a lasso penalty on the entries of the covariance matrix. This penalty plays two important roles: it reduces the effective number of parameters, which is important even when the dimension of the vectors is smaller...

Truncated Singular Value Decomposition (TSVD) regularization method have been used by Zhao et al. [ " Kronecker product approximations for image restoration with new mean boundary conditions " (2011), Applied Mathematical Modelling, Vol. 36, pp. 225-237]. In this report, I propose an alternative regularization the Tikhonov method. The new regularization method gives better relative error when a...