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Vector disparity sensor with vergence control for active vision systems
This paper presents an architecture for computing vector disparity for active vision systems as used on robotics applications. The …
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Adaptive cerebellar spiking model embedded in the control loop: context switching and robustness against noise
This work evaluates the capability of a spiking cerebellar model embedded in different loop architectures (recurrent, forward, and …
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Cerebellar input configuration toward object model abstraction in manipulation tasks
It is widely assumed that the cerebellum is one of the main nervous centers involved in correcting and refining planned movement and …
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Cerebellarlike corrective model inference engine for manipulation tasks
This paper presents how a simple cerebellumlike architecture can infer corrective models in the framework of a control task when …
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Timing in the cerebellum: oscillations and resonance in the granular layer
The brain generates many rhythmic activities, and the olivo-cerebellar system is not an exception. In recent years, the cerebellum has …
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Local image phase, energy and orientation extraction using FPGAs
Local features such as phase, energy and orientation have been widely used in the literature for multiple computer vision applications …
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A real-time spiking cerebellum model for learning robot control
We describe a neural network model of the cerebellum based on integrate-and-fire spiking neurons with conductance-based synapses. The …
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Event-driven simulation of cerebellar granule cells
Around half of the neurons of a human brain are granule cells (approximately 1011granule neurons) [Kandel, E.R., Schwartz, J.H., …
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Real-Time System for High-Image Resolution Disparity Estimation
We present the hardware implementation of a simple, fast technique for depth estimation based on phase measurement. This technique …
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Hardware Event-driven Simulation Engine for Spiking Neural Networks
The efficient simulation of spiking neural networks (SNN) remains an open challenge. Current SNN computing engines are still far away …
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