Different methods for Blind Source Separation (BSS) have been recently proposed. Most of these methods are suitable for separating either a mixture of sub-Gaussian source or a mixture of super-Gaussian sources. In this paper, a unified statistical approach for separating the mixture of sub-Gaussian and super-Gaussian source is proposed. Source separation techniques use an objective function to be optimized. The optimization process requires probability density function to be expressed in the terms of the random variable. Two different density models have been used for representing sub-Gaussian and super-Gaussian sources. Optimization of the objective function yields different nonlinear functions. Kurtosis has been ušed as measure of Gaussianity of a source. Depending upon the sign of kurtosis one of the nonlinearities is ušed in the proposed algorithm. Simulations with artificiaily generated as well as audio signals demonstrate effectiveness of the proposed approach.
A short approach to the Kurzweil-Henstock integral is outlined, based on approximating a real function on a compact interval by suitable step-functions, and using filterbase convergence to define the integral. The properties of the integral are then easy to establish.
In this paper, we consider a distributed stochastic computation of AXB=C with local set constraints over an multi-agent system, where each agent over the network only knows a few rows or columns of matrixes. Through formulating an equivalent distributed optimization problem for seeking least-squares solutions of AXB=C, we propose a distributed stochastic mirror-descent algorithm for solving the equivalent distributed problem. Then, we provide the sublinear convergence of the proposed algorithm. Moreover, a numerical example is also given to illustrate the effectiveness of the proposed algorithm.
Maintaining liquid asset portfolios involves a high carry cost and is mandatory by law for most financial institutions. Taking this into account a financial institution's aim is to manage a liquid asset portfolio in an "optimal" way, such that it keeps the minimum required liquid assets to comply with regulations. In this paper we propose a multi-stage dynamic stochastic programming model for liquid asset portfolio management. The model allows for portfolio rebalancing decisions over a multi-period horizon, as well as for flexible risk management decisions, such as reinvesting coupons, at intermediate time steps. We show how our problem closely relates to insurance products with guarantees and utilize this in the formulation. We will discuss our formulation and implementation of a multi-stage stochastic programming model that minimizes the down-side risk of these portfolios. The model is back-tested on real market data over a period of two years
In a Discounted Markov Decision Process (DMDP) with finite action sets the Value Iteration Algorithm, under suitable conditions, leads to an optimal policy in a finite number of steps. Determining an upper bound on the necessary number of steps till gaining convergence is an issue of great theoretical and practical interest as it would provide a computationally feasible stopping rule for value iteration as an algorithm for finding an optimal policy. In this paper we find such a bound depending only on structural properties of the Markov Decision Process, under mild standard conditions and an additional "individuality" condition, which is of interest in its own. It should be mentioned that other authors find such kind of constants using non-structural information, i.e., information not immediately apparent from the Decision Process itself. The DMDP is required to fulfill an ergodicity condition and the corresponding ergodicity index plays a critical role in the upper bound.
In this paper we obtain a strong invariance principle for negatively associated random fields, under the assumptions that the field has a finite $(2+\delta )$th moment and the covariance coefficient $u(n)$ exponentially decreases to $0$. The main tools are the Berkes-Morrow multi-parameter blocking technique and the Csörgő-Révész quantile transform method.
BACKGROUND: Radio frequency (RF) and chemical peels have been used for nonablative skin rejuvenation. Both of these cause collagen remodeling in the dermis and neo-collagen formation resulting in facial rejuvenation. There is limited literature on the evaluation of collagen remodeling by objective methods. OBJECTIVE: To compare the benefits of monopolar radiofrequency and glycolic acid peels in facial rejuvenation with regards to histopathology and Ultrabiomicroscopic sonography (UBM). METHODOLOGY: In this study, forty patients with mild to moderate photoaging received four treatments with 3 weeks interval of monopolar radiofrequency on one side of face and glycolic acid peels in increasing concentrations (NeostrataR) on the other side. Pre and post treatment, 2 mm biopsies were taken from both preauricular areas and Ultrasonography using a 35 MHz probe was done from outer canthus of eye and nasolabial folds from both sides of face. A blinded assessment was done to measure the increase in the grenz zone and dermal thickness. RESULTS: In 35/40 patients there was a significant increase in the grenz zone on histopathology and decrease in subepidermal low-echogenic band (SLEB) on UBM of the nasolabial folds on both sides of the face (p < 0.05). CONCLUSION: Radiofrequency and chemical peels showed equal efficacy in the treatment of facial rejuvenation. and D. V. Wakade, C. S. Nayak, K. D. Bhatt
The present study was designed to investigate the acute relaxing effect of phytoestrogen resveratrol on isolated porcine coronary arteries and to determine the mechanisms underlying its vasodilatation. Rings of porcine coronary arteries were suspended in organ baths containing Krebs-Henseleit solution, and then isometric tension was measured. Resveratrol concentration-dependently relaxed arterial rings precontracted with 30 mM KCl. The IC50 value of resveratrol was 38.67±3.21 μM. Incubation with Nω-L-nitro-arginine (L-NNA), endothelium removal or the presence of a potent inhibitor of protein tyrosine phosphatase sodium orthovanadate partly decreased the relaxation induced by resveratrol. However, the relaxation induced by resveratrol was unaffected by the estrogen receptor antagonist tamoxifen, the inhibitor of prostanoid synthesis indomethacin, the antagonist of β-adrenoceptors propranolol or the protein synthesis inhibitor, cycloheximide. In addition, resveratrol significantly decreased the contractile responses of
5-HT, KCl and CaCl2, and shifted their cumulative concentration-response curves to the right. These results suggest that the mechanisms of vasorelaxation induced by resveratrol are heterogeneous, two mechanisms participating partially in the relaxation of porcine coronary artery were detected in the study, one being the nitric oxide released from the endothelium, the other causing inhibition of Ca2+ influx, but estrogen receptors were not involved in resveratrol-induced relaxation.