Learn More
In this paper, we consider full-duplex and half-duplex Gaussian relay channels where the noises at the relay and destination are arbitrarily correlated. We first derive the capacity upper bound and the achievable rates with three existing schemes: Decode-and-Forward (DF), Compress-and-Forward (CF), and Amplify-and-Forward (AF). We present two capacity(More)
—In the reported metrics of the existing literature, the realistic wireless channel situation is generally ignored in selecting the appropriate next-hop relay node during packet forwarding in wireless sensor networks (WSNs). In this paper, we propose a new energy-efficient local metric, which is called the efficient advancement metric (EAM), for sensor(More)
Topology preservation of Self-Organizing Maps (SOMs) is an advantageous property for correct clustering. Among several existing measures of topology violation, this paper studies the Topographic Function (TF) [1]. We find that this measuring method, demonstrated for low-dimensional data in [1], has a reliable foundation in its distance metric for the(More)
In this paper we elaborate on the challenges of learning man-ifolds that have many relevant clusters, and where the clusters can have widely varying statistics. We call such data manifolds highly structured. We describe approaches to structure identification through self-organized learning, in the context of such data. We present some of our recently(More)