Winner-take-all networks of O(N) complexity
Advances in neural information processing systems 1
Analog VLSI circuits for stimulus localization and centroid computation
International Journal of Computer Vision - Special issue: VLSI for computer vision
IEEE Spectrum
Analog VLSI Excitatory Feedback Circuits for AttentionalShifts and Tracking
Analog Integrated Circuits and Signal Processing
Conjunction Search Using a 1-D, Analog VLSI-based, Attentional Search/Tracking Chip
ARVLSI '99 Proceedings of the 20th Anniversary Conference on Advanced Research in VLSI
Multi-Bit [sigma-delta] Analog-to-Digital Converters with Nonlinearity Correction
Multi-Bit [sigma-delta] Analog-to-Digital Converters with Nonlinearity Correction
IEEE Transactions on Neural Networks
ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I
A model of analogue K-winners-take-all neural circuit
Neural Networks
Hi-index | 0.00 |
An approach for implementing a high precision image target centroid—center of mass (COM) detection system via an adaptive K-winner-take-all (WTA) circuit in conjunction with a 2-D dynamic element matching (DEM) algorithm implementation for image sensor arrays is proposed. The proposed system outputs a high precision COM location of the most salient target in a programmable active region of the field of view (FOV) for star tracking purposes and is suitable for real time applications. The system allows target selection and locking with multiple targets tracking capability. This solution utilizes the separability property of the COM, and therefore reduces the computational complexity by utilizing 1-D circuits for the computation. The DEM algorithm, commonly used in ADC and DAC circuits, allows reducing the required WTA circuit precision to 5–6 bits, while still achieving a high output precision. Simulation results prove the concept and demonstrate the high precision COM result. In addition, a possible low-level hardware implementation is described.