In this paper, we introduce the use of nonlinear dimension reduction for the analysis of functional neuroimaging datasets. Using a Laplacian Embedding approach, we show the power ...
— Dynamic power noises may not only degrade the circuit performance but also reduce the noise margin which may result in the functional errors in integrated circuit. Decoupling c...
This paper is concerned with developing an information-theoretic framework to aggregate the state space of a Hidden Markov Model (HMM) on discrete state and observation spaces. The...
Partially Observable Markov Decision Processes (POMDPs) are a well-established and rigorous framework for sequential decision-making under uncertainty. POMDPs are well-known to be...
Power has become an increasingly important design constraint for FPGAs in nanometer technologies, and global interconnects should be the focus of FPGA power reduction as they cons...