Further results on independent Metropolis-Hastings-Klein sampling

Sampling from a lattice Gaussian distribution is emerging as an important problem in coding and cryptography. This paper gives a further analysis of the independent Metropolis-Hastings-Klein (MHK) algorithm we presented at ISIT 2015. We derive the exact spectral gap of the induced Markov chain, which dictates the convergence rate of the independent MHK algorithm. Then, we apply the independent MHK algorithm to lattice decoding and obtained the decoding complexity for solving the CVP as Õ(e∥Bx-c∥2 / mini ∥b̂i∥2). Finally, the tradeoff between decoding radius and complexity is also established

Tail Asymptotics of Deflated Risks

Random deflated risk models have been considered in recent literatures. In this paper, we investigate second-order tail behavior of the deflated risk X=RS under the assumptions of second-order regular variation on the survival functions of the risk R and the deflator S. Our findings are applied to approximation of Value at Risk, estimation of small tail probability under random deflation and tail asymptotics of aggregated deflated riskComment: 2

Designs of low delay cosine modulated filter banks and subband amplifiers

This paper proposes a design of a low delay cosine modu-lated filter bank and subband amplifier coefficients for digi-tal audio hearing aids denoising applications. The objective of the design is to minimize the delay of the filter bank. Speci-fications on the maximum magnitude of both the real and the imaginary parts of the transfer function distortion and the aliasing distortion of the filter bank are imposed. Also, the constraint on the maximum absolute difference between the desirable magnitude square response and the designed mag-nitude square response of the prototype filter over both the passband and the stopband is considered. The subband am-plifier coefficients are designed based on a least squares training approach. The average mean square errors between the noisy samples and the clean samples is minimized. Com-puter numerical simulation results show that our proposed approach could significantly improve the signal-to-noise ratio of digital audio hearing aids

How prudent are rural households in developing transition economies:

Rural households in developing economies frequently use precautionary saving to cope with income risk. Such prudent behavior can be strengthened in transition economies where more risks are typically faced by households during and after reforms. This paper uses a rich panel of rural households in Zhejiang, China, to examine the correlation between income uncertainty and the target ratio of wealth to permanent income as suggested by the buffer-stock model. The empirical results suggest that Chinese rural households hold a significant level of wealth to mitigate the adverse impacts of income risk. Simulation results show that an increase in income risk leads to a sharp increase in household wealth and precautionary saving could drop substantially if income risk is eliminated. The high level of prudence of rural households under economic transition can help us better understand the developments in China, which will have policy implications for both developing and transition countries.buffer-stock model, Income risk, precautionary saving,

Mean, median or something else

Non parametric inferential statistics was used to guide the numerical optimization study to search for the optimum result in this article. The technique was demonstrated in a case study and a significant improved predictive model was formulated with 4% less residual sum of squares (RSS) than the median model, 20% less than the mean model and 79% less than a benchmarked empirical model. The methodology proposed herewith addressed the selection dilemma between mean and median. It identified an optimum value and formulated a better predictive model than those by either mean or median

Symmetric mettropolis-within-Gibbs algorithm for lattice Gaussian sampling

As a key sampling scheme in Markov chain Monte Carlo (MCMC) methods, Gibbs sampling is widely used in various research fields due to its elegant univariate conditional sampling, especially in tacking with multidimensional sampling systems. In this paper, a Gibbs-based sampler named as symmet- ric Metropolis-within-Gibbs (SMWG) algorithm is proposed for lattice Gaussian sampling. By adopting a symmetric Metropolis- Hastings (MH) step into the Gibbs update, we show the Markov chain arising from it is geometrically ergodic, which converges exponentially fast to the stationary distribution. Moreover, by optimizing its symmetric proposal distribution, the convergence efficiency can be further enhanced

The Entanglement in Anisotropic Heisenberg XYZ Chain with inhomogeneous magnetic field

The thermal entanglement of a two-qubit anisotropic Heisenberg $XYZ$ chain under an inhomogeneous magnetic field b is studied. It is shown that when inhomogeneity is increased to certain value, the entanglement can exhibit a larger revival than that of less values of b. The property is both true for zero temperature and a finite temperature. The results also show that the entanglement and critical temperature can be increased by increasing inhomogeneous exteral magnetic field