Patent ID: 9563843
Date: 2017-02-07
CPC Classifications: G06F,G06K,G06N

Claim:
1. A computer-implemented method in a self-adaptive multi modal data stream processing system having at least one computer processor, the computer processor including a control module that establishes a system of “artificial neurons” and associates data elements and various combinations of data elements with said neurons, a construction module under control of the control module that constructs components of situation models, and at least one spatiotemporal associative memory coupled to the at least one computer processor, the method comprising: receiving multi modal data streams by the computer processor from multiple data stream sources, the multi modal data streams representing an environment of the multi modal data stream processing system; constructing, by the construction module, at least one three-partite situation model of a situation, by making associations of artificial neurons of a plurality of artificial neurons of various types in an artificial neural network in the at least on spatiotemporal associative memory, wherein the three-partite situation model represents at least two entities and a relation between the at least two entities or at least two states of the same entity and a relation between the at least two states, wherein the step of constructing of the at least one three-partite situation model includes: wherein the plurality of artificial neurons of various different types includes a combination of: sensory neurons, temporal neurons, feature neurons, spatial neurons, complex neurons, hyper complex neurons, and semantic neurons wherein the sensory neurons respond to different elements (features) in the incoming streams, the temporal neurons respond to various temporal relations in the activation of sensory neurons, the spatial neurons respond to different locations and relative positions of activation sources, the complex neurons respond to various activation patterns involving sensory, temporal and spatial neurons, the hyper complex neurons respond to various compositions of activation patterns involving complex neurons, and the semantic neurons respond to various patterns of activation involving hyper complex neurons and associate such patterns with labels in a finite set of labels defined by a user to signify meaningful relationships, wherein the dynamic mapping includes manipulating packets by the control module, wherein the manipulating includes applying an operation of enfolding to packets comprising: