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» Digital data networks design using genetic algorithms
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FPGA
2010
ACM
232views FPGA» more  FPGA 2010»
13 years 9 months ago
High-throughput bayesian computing machine with reconfigurable hardware
We use reconfigurable hardware to construct a high throughput Bayesian computing machine (BCM) capable of evaluating probabilistic networks with arbitrary DAG (directed acyclic gr...
Mingjie Lin, Ilia Lebedev, John Wawrzynek
FLAIRS
2004
13 years 10 months ago
Iterative Improvement of Neural Classifiers
A new objective function for neural net classifier design is presented, which has more free parameters than the classical objective function. An iterative minimization technique f...
Jiang Li, Michael T. Manry, Li-min Liu, Changhua Y...
MOBIHOC
2005
ACM
14 years 8 months ago
Low-coordination topologies for redundancy in sensor networks
Tiny, low-cost sensor devices are expected to be failure-prone and hence in many realistic deployment scenarios for sensor networks these nodes are deployed in higher than necessa...
Rajagopal Iyengar, Koushik Kar, Suman Banerjee
IPSN
2009
Springer
14 years 3 months ago
Simultaneous placement and scheduling of sensors
We consider the problem of monitoring spatial phenomena, such as road speeds on a highway, using wireless sensors with limited battery life. A central question is to decide where ...
Andreas Krause, Ram Rajagopal, Anupam Gupta, Carlo...
SIGMOD
2006
ACM
219views Database» more  SIGMOD 2006»
14 years 9 months ago
Modeling skew in data streams
Data stream applications have made use of statistical summaries to reason about the data using nonparametric tools such as histograms, heavy hitters, and join sizes. However, rela...
Flip Korn, S. Muthukrishnan, Yihua Wu