Pattern synchronization for associative memory in pulse coded neural networks

For image processing a lot of algorithms have been developed in the past that are well suited for specific tasks. These algorithms are often optimized for high performance computers with high power consumption, thus, it is not possible to use these algorithms for mobile applications. In this paper, a massive parallel vision system is partly discussed which is biologically inspired and requires less power. This system consists of several layers of pulsed neural networks, e.g. some layers form specific features detectors to decompose the input image in several features. The features are completed or bound by an associative memory that needs a synchronized input pulse pattern. In this paper, we focus on the synchronization stage of the system that is combined with the associative memory. The discussed synchronization unit detects correlated pulses in the network, collects them and activates a synchrones output pattern.