Analog VLSI and neural systems
Analog VLSI and neural systems
Winner-take-all networks of O(N) complexity
Advances in neural information processing systems 1
A pulse-coded communications infrastructure for neuromorphic systems
Pulsed neural networks
Communicating neuronal ensembles between neuromorphic chips
Neuromorphic systems engineering
Poisson-like neuronal firing due to multiple synfire chains in simultaneous action
CNS '96 Proceedings of the annual conference on Computational neuroscience : trends in research, 1997: trends in research, 1997
A Model of Saliency-Based Visual Attention for Rapid Scene Analysis
IEEE Transactions on Pattern Analysis and Machine Intelligence
Analog VLSI-based modeling of the primate oculomotor system
Neural Computation
Design of an Analogue VLSI Model of an Active Cochlea
Analog Integrated Circuits and Signal Processing
Analog VLSI Excitatory Feedback Circuits for AttentionalShifts and Tracking
Analog Integrated Circuits and Signal Processing
Winner-Take-All Networks with Lateral Excitation
Analog Integrated Circuits and Signal Processing
A Two-Dimensional, Object-Based Analog VLSI Visual Attention System
ARVLSI '99 Proceedings of the 20th Anniversary Conference on Advanced Research in VLSI
An Analogue Electronic Model of Ventral Cochlear Nucleus Neurons
MICRONEURO '96 Proceedings of the 5th International Conference on Microelectronics for Neural Networks and Fuzzy Systems
Analog VLSI Circuits for Covert Attentional Shifts
MICRONEURO '96 Proceedings of the 5th International Conference on Microelectronics for Neural Networks and Fuzzy Systems
A Reconfigurable Neuromorphic VLSI Multi-Chip System Applied to Visual Motion Computation
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
Retinomorphic Chips that see Quadrupple Images
MICRONEURO '99 Proceedings of the 7th International Conference on Microelectronics for Neural, Fuzzy and Bio-Inspired Systems
A 2D Neuromorphic VLSI Architecture for Modeling Selective Attention
IJCNN '00 Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN'00)-Volume 4 - Volume 4
A Silicon Implementation of the Fly's Optomotor Control System
Neural Computation
A Current-Mode Hysteretic Winner-take-all Network, with Excitatory and Inhibitory Coupling
Analog Integrated Circuits and Signal Processing
A VLSI-Based Model of Azimuthal Echolocation in the Big Brown Bat
Autonomous Robots
Modeling short-term synaptic depression in Silicon
Neural Computation
A Real Time Implementation of the Saliency-Based Model of Visual Attention on a SIMD Architecture
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Real-time visual attention on a massively parallel SIMD architecture
Real-Time Imaging
On the Computational Power of Winner-Take-All
Neural Computation
Analog VLSI circuits for short-term dynamic synapses
EURASIP Journal on Applied Signal Processing
Synaptic Dynamics in Analog VLSI
Neural Computation
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Attentional mechanisms are required to overcome the problem of flooding a limited processing capacity system with information. They are present in biological sensory systems and can be a useful engineering tool for artificial visual systems. In this article we present a hardware model of a selective attention mechanism implemented on a very large-scale integration (VLSI) chip, using analog neuromorphic circuits. The chip exploits a spike-based representation to receive, process, and transmit signals. It can be used as a transceiver module for building multichip neuromorphic vision systems. We describe the circuits that carry out the main processing stages of the selective attention mechanism and provide experimental data for each circuit. We demonstrate the expected behavior of the model at the system level by stimulating the chip with both artificially generated control signals and signals obtained from a saliency map, computed from an image containing several salient features.