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» Probabilistic Neural Network Models for Sequential Data
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WCNC
2008
IEEE
14 years 2 months ago
Integrated Source-Channel Decoding for Correlated Data-Gathering Sensor Networks
Abstract— This paper explores integrated source-channel decoding, driven by wireless sensor network applications where correlated information acquired by the network is gathered ...
Sheryl L. Howard, Paul G. Flikkema
ICANN
2001
Springer
14 years 17 days ago
Independent Variable Group Analysis
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
Krista Lagus, Esa Alhoniemi, Harri Valpola
ICDE
2002
IEEE
149views Database» more  ICDE 2002»
14 years 9 months ago
GADT: A Probability Space ADT for Representing and Querying the Physical World
Large sensor networks are being widely deployed for measurement, detection, and monitoring applications. Many of these applications involve database systems to store and process d...
Anton Faradjian, Johannes Gehrke, Philippe Bonnet
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
14 years 8 months ago
Domain-constrained semi-supervised mining of tracking models in sensor networks
Accurate localization of mobile objects is a major research problem in sensor networks and an important data mining application. Specifically, the localization problem is to deter...
Rong Pan, Junhui Zhao, Vincent Wenchen Zheng, Jeff...
ISNN
2007
Springer
14 years 2 months ago
A Hierarchical Self-organizing Associative Memory for Machine Learning
This paper proposes novel hierarchical self-organizing associative memory architecture for machine learning. This memory architecture is characterized with sparse and local interco...
Janusz A. Starzyk, Haibo He, Yue Li