Intelligent control with hierarchical stacked neural networks

摘要

A system and method of detecting an aberrant message is provided. An ordered set of words within the message is detected. The set of words found within the message is linked to a corresponding set of expected words, the set of expected words having semantic attributes. A set of grammatical structures represented in the message is detected, based on the ordered set of words and the semantic attributes of the corresponding set of expected words. A cognitive noise vector comprising a quantitative measure of a deviation between grammatical structures represented in the message and an expected measure of grammatical structures for a message of the type is then determined. The cognitive noise vector may be processed by higher levels of the neural network and/or an external processor.

主权项

1. A system configured to analyzing at least one data pattern comprising:
an input configured to receive at least one data pattern; at least one hierarchical neural network, having a plurality of hierarchical layers, each respective hierarchical layer being configured to receive a respective input and to produce a non-arbitrary organization of actions in dependence on the respective input and a respective layer training, the at least one hierarchical neural network comprising:
a first layer configured to produce a non-arbitrary organization of actions which identifies at least one data object from a plurality of data objects, based at least the first layer training to identify a plurality of different data objects, and the at least one data pattern, and to produce a noise vector output, distinct from the non-arbitrary organization of actions of the first layer, representing a deviance of at least a portion of the at least one data pattern from a prototype of the data object identified,a second layer, configured to receive the respective non-arbitrary organization of actions from the first layer identifying the object as the respective input, based on the non-arbitrary organization of actions from the first layer, to ascertain a type of the identified data object from a plurality of different types of each of the plurality of different data objects;wherein the first layer further produces a noise vector output, distinct from the non-arbitrary organization of actions of the first layer, representing a deviance of at least a portion of the at least one data pattern from a prototype of the data object identified, anda processor configured to at least one of: determine a confidence of data object identification, and determine that the data pattern comprises a data object not properly identified by the first layer.