Wiring considerations in analog VLSI systems, with application to field-programmable networks
Wiring considerations in analog VLSI systems, with application to field-programmable networks
VLSI analogs of neuronal visual processing: a synthesis of form and function
VLSI analogs of neuronal visual processing: a synthesis of form and function
Communicating neuronal ensembles between neuromorphic chips
Neuromorphic systems engineering
Spikes: exploring the neural code
Spikes: exploring the neural code
A new class of linear feedback shift register generators
Proceedings of the 32nd conference on Winter simulation
Test infrastructure for address-event-representation communications
IWANN'05 Proceedings of the 8th international conference on Artificial Neural Networks: computational Intelligence and Bioinspired Systems
On algorithmic rate-coded AER generation
IEEE Transactions on Neural Networks
An AER-Based Actuator Interface for Controlling an Anthropomorphic Robotic Hand
IWINAC '07 Proceedings of the 2nd international work-conference on Nature Inspired Problem-Solving Methods in Knowledge Engineering: Interplay Between Natural and Artificial Computation, Part II
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
From Vision Sensor to Actuators, Spike Based Robot Control through Address-Event-Representation
IWANN '09 Proceedings of the 10th International Work-Conference on Artificial Neural Networks: Part I: Bio-Inspired Systems: Computational and Ambient Intelligence
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Address-Event-Representation (AER) is a communication protocol for transferring images between chips, originally developed for bio-inspired image-processing systems. Such systems may consist of a complicated hierarchical structure with many chips that transmit images among them in real time, while performing some processing (for example, convolutions). In developing AER-based systems it is very convenient to have available some means of generating AER streams from on-computer stored images. Rank order coding (ROC) and Poisson rate coding are the extremes of spikes coding. In this paper, we present a pseudo-random hardware method for generating AER streams in real time from a sequence of images stored in a computer's memory. The Kolmogorov-Smirnov test has been applied to quantify that this method follows a Poisson distribution of the spikes. A USB-AER board, developed by our RTCAR group, have been used for the measurements. An example scenario of use under the EU CAVIAR project is presented.