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NECO
2010
147views more  NECO 2010»
15 years 5 months ago
Connectivity, Dynamics, and Memory in Reservoir Computing with Binary and Analog Neurons
Abstract: Reservoir Computing (RC) systems are powerful models for online computations on input sequences. They consist of a memoryless readout neuron which is trained on top of a ...
Lars Büsing, Benjamin Schrauwen, Robert A. Le...
ICPR
2002
IEEE
16 years 7 months ago
Learning and Extracting Edges from Images by a Modified Hopfield Neural Network
This paper introduced a modified unsupervised Hopfield network that can learn the underlying process in an edge detection task from grey level images. After the learning phase, th...
Sylvain Chartier, Richard Lepage

Tutorial
3234views
16 years 2 months ago
Nguyen-Widrow and other Neural Network Weight/Threshold Initialization Methods
Neural networks learn by adjusting numeric values called weights and thresholds. A weight specifies how strong of a connection exists between two neurons. A threshold is a value,...
Jeff Heaton
SKG
2006
IEEE
16 years 20 days ago
Service Discovery Protocol in Wireless Sensor Networks
Sensor network is a novel technology about acquiring and processing information. This paper introduces the basic interaction patterns between requesters and providers of services ...
Xin-lian Zhou, Min Wu
160
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EUSFLAT
2007
183views Fuzzy Logic» more  EUSFLAT 2007»
15 years 8 months ago
Soft Computing in Wireless Sensors Networks
The embedded soft computing approach in wireless sensor networks is suggested. This approach means a combination of embedded fuzzy logic and neural networks models for information...
Alexey N. Averkin, A. G. Belenki