In this paper, we first get further consideration of the order perturbation with normwise condition number MTLS problem. For easy estimation, show a lower bound for which is proved to be optimal. overcome problems encountered in calculating number, give an upper computing more effectively and nonstandard unusual bounds Both two types can enjoy storage computational advantages. getting insight i...

This paper uses quantile regression to investigate the asymmetric return-volatility phenomenon with the newly adapted and robust implied volatility indices VIX, VXN, VDAX and VSTOXX. A particular goal is to quantify the effects of positive and negative stock index returns at various quantiles of the implied volatility distribution. As the level of the new volatility index increases during marke...

In Australia, domestic tourism generated AUD71 billion in 2009-10, representing approximately 75.6% of national tourism revenue. While the number of domestic overnight visitors increased by 2.3% in that year, the number of Australians travelling overseas grew by 15.9%. This shows that there is a high tendency for more Australians to travel overseas. There are two possible reasons: first, the in...

In the present study, air quality analyses for ozone (O3) were conducted in Shiraz, a city in the south of Iran. The measurements were taken from 2011 through 2012 in two different locations to prepare average data in the city. The average concentrations were calculated for every 24 hours, each month and each season. Results showed that the highest concentration of ozone occurs generally in the...

A new non-linear Recursive Least Squares (RLS) algorithm is presented in the context of pattern classification problems. The algorithm incorporates the non-linearity of the filter’s output in the updating rules of the classical RLS algorithm. The proposed method yields lower stationary error levels when compared to the standard LMS and RLS algorithms in a classical application of pattern classi...

Analogue to the ADMM method for the filter subproblem, we derive the following Algorithm 3 for solving for the sparse coefficient maps zi. However, unlike in the filter subproblem, we do not enforce consensus among the coefficient feature maps zi since there exists a distinct zi for each bi,∀i = [1 . . . N ]. In Algorithm 3, each zi update takes the form of a Tikhonov-regularized least squares ...

The standard approaches to solving overdetermined linear systems Bx ≈ c construct minimal corrections to the vector c and/or the matrix B such that the corrected system is compatible. In ordinary least squares (LS) the correction is restricted to c, while in data least squares (DLS) it is restricted to B. In scaled total least squares (STLS) [22], corrections to both c and B are allowed, and th...