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» Probabilistic Neural Network Models for Sequential Data
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MLG
2007
Springer
14 years 2 months ago
Inferring Vertex Properties from Topology in Large Networks
: Network topology not only tells about tightly-connected “communities,” but also gives cues on more subtle properties of the vertices. We introduce a simple probabilistic late...
Janne Sinkkonen, Janne Aukia, Samuel Kaski
RECOMB
2003
Springer
14 years 8 months ago
A multi-expert system for the automatic detection of protein domains from sequence information
We describe a novel method for detecting the domain structure of a protein from sequence information alone. The method is based on analyzing multiple sequence alignments that are ...
Niranjan Nagarajan, Golan Yona
ENGL
2008
142views more  ENGL 2008»
13 years 8 months ago
A Solid-State Neuron for Spiking Neural Network Implementation
This paper presents a compact analog neuron cell incorporating an array of charge-coupled synapses connected via a common output terminal. The novel silicon synapse is based on a t...
Yajie Chen, Steve Hall, Liam McDaid, Octavian Buiu...
ICAISC
2004
Springer
14 years 1 months ago
Semi-mechanistic Models for State-Estimation - Soft Sensor for Polymer Melt Index Prediction
Nonlinear state estimation is a useful approach to the monitoring of industrial (polymerization) processes. This paper investigates how this approach can be followed to the develop...
Balazs Feil, János Abonyi, Peter Pach, Sand...
BMCBI
2006
146views more  BMCBI 2006»
13 years 8 months ago
Optimized Particle Swarm Optimization (OPSO) and its application to artificial neural network training
Background: Particle Swarm Optimization (PSO) is an established method for parameter optimization. It represents a population-based adaptive optimization technique that is influen...
Michael Meissner, Michael Schmuker, Gisbert Schnei...