We present a novel family of data-driven linear transformations, aimed at visualizing multivariate data in a low-dimensional space in a way that optimally preserves the structure ...
—Recent studies show that network coding improves multicast session throughput. In this paper, we demonstrate how random linear network coding can be incorporated to provide netw...
We propose a class of alternative stochastic volatility models for electricity prices using the quantile function modeling approach. Specifically, we fit marginal distributions ...
Due to resource and power constraints, embedded processors often cannot afford dedicated floating-point units. For instance, the IBM PowerPC processor embedded in Xilinx Virtex-...
Ray C. C. Cheung, Dong-U Lee, Oskar Mencer, Wayne ...
This paper presents analysis and design results for distributed consensus algorithms in multi-agent networks. We consider continuous consensus functions of the initial state of th...