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Neuromorphic systems are engineering solutions that take inspiration from biological neural systems. They use spike-or event-based representation and codification of the information. This codification allows performing complex computations, filters, classifications and learning in a pseudo-simultaneous way. Small incremental processing is done per event, which shows useful results with very low latencies...
Neuromorphic engineering is a growing and promising discipline nowadays. Neuro-inspiration and brain understanding applied to solve engineering problems is boosting new architectures, solutions and products today. The biological brain and neural systems process information at relatively low speeds through small components, called neurons, and it is impressive how they connect each other to construct...
Multisensory integration is commonly used in various robotic areas to collect more environmental information using different and complementary types of sensors. Neuromorphic engineers mimics biological systems behavior to improve systems performance in solving engineering problems with low power consumption. This work presents a neuromorphic sensory integration scenario for measuring the rotation...
Multisensory integration is commonly used in various robotic areas to collect much more information from an environment using different and complementary types of sensors. This demonstration presents a scenario where the motor rotation frequency is obtained using an AER DVS128 retina chip (Dynamic Vision Sensor) and a frequency decomposer auditory system on a FPGA that mimics a biological cochlea...
Nowadays spike-based brain processing emulation is taking off. Several EU and others worldwide projects are demonstrating this, like SpiNNaker, BrainScaleS, FACETS, or NeuroGrid. The larger the brain process emulation on silicon is, the higher the communication performance of the hosting platforms has to be. Many times the bottleneck of these system implementations is not on the performance inside...
Spike-based motor control is very important in the field of robotics and also for the neuromorphic engineering community to bridge the gap between sensing / processing devices and motor control without losing the spike philosophy that enhances speed response and reduces power consumption. This paper shows an accurate neuro-inspired spike-based system composed of a DVS retina, a visual processing system...
Distance calculation is always one of the most important goals in a digital stereoscopic vision system. In an AER system this goal is very important too, but it cannot be calculated as accurately as we would like. This demonstration shows a first approximation in this field, using a disparity algorithm between both retinas. The system can make a distance approach about a moving object, more specifically,...
Spike-based systems are neuro-inspired circuits implementations traditionally used for sensory systems or sensor signal processing. Address-Event-Representation (AER) is a neuromorphic communication protocol for transferring asynchronous events between VLSI spike-based chips. These neuro-inspired implementations allow developing complex, multilayer, multichip neuromorphic systems and have been used...
Neuromorphic engineers study models and implementations of systems that mimic neurons behavior in the brain. Neuro-inspired systems commonly use spikes to represent information. This representation has several advantages: its robustness to noise thanks to repetition, its continuous and analog information representation using digital pulses, its capacity of pre-processing during transmission time,...
Neuromorphic engineering tries to mimic biological information processing. Address-Event-Representation (AER) is an asynchronous protocol for transferring the information of spiking neuro-inspired systems. Currently AER systems are able sense visual and auditory stimulus, to process information, to learn, to control robots, etc. In this paper we present an AER based layer able to correct in real time...
Correcting digital images tilt needs huge quantities of memory, high computational resources, and use to take a considerable amount of time. This demonstration shows how a spikes-based silicon retina dynamic vision sensor (DVS) tilt can corrected in real time using a commercial accelerometer. DVS output is a stream of spikes codified using the address-event representation (AER). Event-based processing...
Neuromorphic engineering tries to mimic biology in information processing. Address-event representation (AER) is a neuromorphic communication protocol for spiking neurons between different layers. AER bio-inspired image sensor are called ldquoretinardquo. This kind of sensors measure visual information not based on frames from real life and generates corresponding events. In this paper we provide...
Neuromorphic engineering tries to mimic biological information processing. Address-event representation (AER) is a neuromorphic communication protocol for spiking neurons between different chips. We present a new way to drive robotic platforms using spiking neurons. We have simulated spiking control models for DC motors, and developed a mobile robot (Eddie) controlled only by spikes. We apply AER...
Address-event-representation (AER) is an emergent neuromorphic interchip communication protocol that allows for real-time virtual massive connectivity between huge number neurons located on different chips. By exploiting high speed digital communication circuits (with nano-seconds timings), synaptic neural connections can be time multiplexed, while neural activity signals (with miliiseconds timings)...
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