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» Modeling Neural Processes in Lindenmayer Systems
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96
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IJON
2002
154views more  IJON 2002»
15 years 3 days ago
Nonlinear model predictive control of a cutting process
Nonlinear model predictive control (MPC) of a simulated chaotic cutting process is presented. The nonlinear MPC combines a neural-network model and a genetic-algorithm-based optim...
Primoz Potocnik, Igor Grabec
NIPS
1998
15 years 1 months ago
Modeling Surround Suppression in V1 Neurons with a Statistically Derived Normalization Model
We examine the statistics of natural monochromatic images decomposed using a multi-scale wavelet basis. Although the coefficients of this representation are nearly decorrelated, t...
Eero P. Simoncelli, Odelia Schwartz
109
Voted
IROS
2008
IEEE
161views Robotics» more  IROS 2008»
15 years 6 months ago
Segmenting acoustic signal with articulatory movement using Recurrent Neural Network for phoneme acquisition
— This paper proposes a computational model for phoneme acquisition by infants. Human infants perceive speech sounds not as discrete phoneme sequences but as continuous acoustic ...
Hisashi Kanda, Tetsuya Ogata, Kazunori Komatani, H...
IJCNN
2007
IEEE
15 years 6 months ago
A Closed Form Solution for Multiple-Input Spike Based Adaptive Filters
— Neurons are point process systems, in the sense that the inputs and output which are spike trains can be treated as point processes. System identification of a point process s...
Il Park, António R. C. Paiva, Jose C. Princ...
96
Voted
GECCO
2007
Springer
212views Optimization» more  GECCO 2007»
15 years 6 months ago
A developmental model of neural computation using cartesian genetic programming
The brain has long been seen as a powerful analogy from which novel computational techniques could be devised. However, most artificial neural network approaches have ignored the...
Gul Muhammad Khan, Julian F. Miller, David M. Hall...