Scalable Non-Binary Distributed Source Coding Using Gray Codes
In this paper we propose a bit-plane based, scalable distributed source coding (DSC) scheme for non-binary correlated sources. In the source coding part of DSC, the symbols are quantized and the quantization indices are converted into binary forms using Gray codes. The channel coding part encodes each bit-plane independently using turbo codes. The turbo decoder that works in binary domain is facilitated by an outer loop that captures the symbol-domain correlation. Simulation results show that, in asymmetric DSC of joint Gaussian sources, the overall system performance is greatly improved by using Gray codes. It is also demonstrated that progressive transmission is well supported
Abstract This study contributes to the literature on socially responsible investing by examining the diversification potential of commodities, specifically oil, gold and clean energy together with the Brazilian Corporate Sustainability Index (ISE). Multivariate GARCH models are used to model volatility spillovers and conditional correlation in pairs of stocks containing ISE. Specifically, A-BEKK and A-DCC models with spillovers are estimated. The models’ results are used to compute and analyze the optimal weights and hedge ratios for stock portfolio holdings. The greatest benefit from diversification is obtained through the acquisition of gold and then OVX.