Neuromorphic Sensory-Processing-Learning Systems inspired in Computation Neuroscience

Computational Neuroscience provides a great inspiration for building efficient sensing, processing and learning artificial systems based on computing and processing with spikes. In this symposium we will review present state-of-the-art on so called “neuromorphic” systems, which are artificial systems which sense, compute and learn based on events. In neural biology, information is encoded in spikes or sequences of spikes, providing highly efficient means of encoding relevant information and resulting in fast and energy efficient sensory processing and learning systems. In the world of engineering, understanding the underlying computing principles is crystalizing already in a number of interesting applications, although there is still a long path to understanding the mysteries of the brain. We will present state-of-the-art sensory neuromorphic systems, review the state of artificial neuromorphic learning, and illustrate computations in the neuromorphic domain.

• Neuromorphic Sensing
• Neuromorphic Learning
• Neuromorphic Computation