Patent Document ID: 9053431
Application ID: 14322147

Base Claim:
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, and a 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.

---

Claim 4:
4. The system of claim 1 , wherein the second layer is further configured to produce a second noise vector output, distinct from the non-arbitrary organization of actions of the second layer, representing a deviance of the identified object from a prototype of the ascertained type of object, and the at least one hierarchical neural network further comprises a third layer configured to receive the non-arbitrary organization of actions from the second layer, and to further process the information from the at least one data pattern propagated through the first layer and the second layer in dependence on respective training of the third layer.