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» Can Dynamic Neural Filters Produce Pseudo-Random Sequences
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ICANN
2005
Springer
13 years 10 months ago
Can Dynamic Neural Filters Produce Pseudo-Random Sequences?
Abstract. Dynamic neural filters (DNFs) are recurrent networks of binary neurons. Under proper conditions of their synaptic matrix they are known to generate exponentially large c...
Yishai M. Elyada, David Horn
JMM2
2007
183views more  JMM2 2007»
13 years 5 months ago
A Chaos Theoretic Analysis of Motion and Illumination in Video Sequences
— Accurate and robust image motion detection has been of substantial interest in the image processing and computer vision communities. Unfortunately, no single motion detection a...
Michael E. Farmer
IROS
2008
IEEE
161views Robotics» more  IROS 2008»
13 years 11 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...
ADHOCNOW
2005
Springer
13 years 10 months ago
Location Tracking in Mobile Ad Hoc Networks Using Particle Filters
Mobile ad hoc networks (MANET) are dynamic networks formed on-the-fly as mobile nodes move in and out of each others’ transmission ranges. In general, the mobile ad hoc networki...
Rui Huang, Gergely V. Záruba
IJCV
2000
195views more  IJCV 2000»
13 years 5 months ago
Optical Flow Constraints on Deformable Models with Applications to Face Tracking
Optical flow provides a constraint on the motion of a deformable model. We derive and solve a dynamic system incorporating flow as a hard constraint, producing a model-based least...
Douglas DeCarlo, Dimitris N. Metaxas