Abstract. We propose a non-standard neural network called TPNN which offers the direct mapping from a peptide sequence to a property of interest in order to model the quantitative ...
— Many neural network models of (human) motor learning focus on the acquisition of direct goal-to-action mappings, which results in rather inflexible motor control programs. We ...
Distributed Hash Tables (DHTs) provide a scalable mechanism for mapping identifiers to socket addresses. As each peer in the network can initiate lookup requests, a DHT has to pr...
We consider the in-network computation of approximate “big picture” summaries in bandwidth-constrained sensor networks. First we review early work on computing the Haar wavele...
Abstract. Self-Organizing Map (SOM) is an unsupervised learning neural network and it is used for preserving the structural relationships in the data without prior knowledge. SOM h...