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CONNECTION
2006
172views more  CONNECTION 2006»
13 years 7 months ago
Temporal sequence detection with spiking neurons: towards recognizing robot language instructions
We present an approach for recognition and clustering of spatio temporal patterns based on networks of spiking neurons with active dendrites and dynamic synapses. We introduce a n...
Christo Panchev, Stefan Wermter
IJCNN
2008
IEEE
14 years 1 months ago
Adaptation of barn owl localization system with spike timing dependent plasticity
— To localize a seen object, the superior colliculus of the barn owl integrates the visual and auditory localization cues which are accessed from the sensory system of the brain....
Juan Huo, Alan F. Murray, Leslie Smith, Zhijun Yan...
JMLR
2002
133views more  JMLR 2002»
13 years 7 months ago
Learning Precise Timing with LSTM Recurrent Networks
The temporal distance between events conveys information essential for numerous sequential tasks such as motor control and rhythm detection. While Hidden Markov Models tend to ign...
Felix A. Gers, Nicol N. Schraudolph, Jürgen S...
JCNS
1998
134views more  JCNS 1998»
13 years 7 months ago
Analytical and Simulation Results for Stochastic Fitzhugh-Nagumo Neurons and Neural Networks
An analytical approach is presented for determining the response of a neuron or of the activity in a network of connected neurons, represented by systems of nonlinear ordinary stoc...
Henry C. Tuckwell, Roger Rodriguez
NN
2002
Springer
208views Neural Networks» more  NN 2002»
13 years 7 months ago
A spiking neuron model: applications and learning
This paper presents a biologically-inspired, hardware-realisable spiking neuron model, which we call the Temporal Noisy-Leaky Integrator (TNLI). The dynamic applications of the mo...
Chris Christodoulou, Guido Bugmann, Trevor G. Clar...