NM500, neuromorphic chip with 576 neurons
The NM500 is a neuromorphic chip opening new frontiers for smart sensors and cognitive computing applications. It can solve pattern recognition problems from text and data analytics, vision, audition, and multi-sensory fusion with orders of magnitude less energy and complexity than modern microprocessors.
Non linear classifier
Identify, Classify, Detect novelty, cope with non linearity and ill defined problems, report cases of unknown and cases of uncertainty.
Real-time learning, high speed clustering, intrinsic deduplication, tracability of the knowledge built by the neurons
Fixed latency regardless of the number of neurons, order of micro-seconds per pattern, low power consumption (0.5 Watts), low clock frequency, small footprint
|Neuron memory size||256 bytes|
|Category register||15 bits|
|Distance register||16 bits|
|Context register||7 bits|
|Recognition status||Identified, Uncertain or Unknown|
|Classifiers||Radial Basis Function (RBF), K-Nearest Neighbor (KNN)|
|Distance Norms||L1 (Manhattan), Lsup|