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» Verifying Properties of Neural Networks
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NN
2006
Springer
13 years 7 months ago
Propagation and control of stochastic signals through universal learning networks
The way of propagating and control of stochastic signals through Universal Learning Networks (ULNs) and its applications are proposed. ULNs have been already developed to form a s...
Kotaro Hirasawa, Shingo Mabu, Jinglu Hu
ECAL
2003
Springer
14 years 26 days ago
Pattern Recognition in a Bucket
This paper demonstrates that the waves produced on the surface of water can be used as the medium for a “Liquid State Machine” that pre-processes inputs so allowing a simple pe...
Chrisantha Fernando, Sampsa Sojakka
NN
2002
Springer
122views Neural Networks» more  NN 2002»
13 years 7 months ago
Cellular, synaptic and network effects of neuromodulation
All network dynamics emerge from the complex interaction between the intrinsic membrane properties of network neurons and their synaptic connections. Nervous systems contain numer...
Eve Marder, Vatsala Thirumalai
SCL
2010
114views more  SCL 2010»
13 years 2 months ago
Input-state incidence matrix of Boolean control networks and its applications
The input-state incidence matrix of control Boolean network is proposed. It is shown that this matrix contains complete information of the input-state mapping. Using it, an easily...
Yin Zhao, Hongsheng Qi, Daizhan Cheng
TIME
2009
IEEE
14 years 2 months ago
Strong Temporal, Weak Spatial Logic for Rule Based Filters
—Rule-based filters are sequences of rules formed of a condition and a decision. Rules are applied sequentially up to the first fulfilled condition, whose matching decision de...
Roger Villemaire, Sylvain Hallé