# US 2016/0260010 A1 · System and method for a recursive cortical network

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2016/0260010 A1
- Document ID: US20160260010A1
- Status: Published application
- Kind: A1
- Application number: 15/158,472
- Filed: 2016-05-18
- Published: 2016-09-08
- Earliest claimed: 2012-05-15
- Assignees: Vicarious FPC, Inc.
- Applicants: Vicarious FPC, Inc.
- Inventors: Dileep George; Kenneth Kansky; D Scott Phoenix; Bhaskara Marthi; Christopher Laan; Wolfgang Lehrach
- Web page: https://patentgrep.com/patent/US20160260010A1

## CPC

- G06N 3/044: Recurrent networks, e.g. Hopfield networks
- G06N 3/045: Combinations of networks
- G06N 3/0475: Generative networks
- G06N 3/0495: Quantised networks; Sparse networks; Compressed networks
- G06N 3/082: modifying the architecture, e.g. adding, deleting or silencing nodes or connections
- G06N 20/00: Machine learning
- G06N 3/049: Temporal neural networks, e.g. delay elements, oscillating neurons or pulsed inputs
- G06N 5/04: Inference or reasoning models
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS

## Abstract

A system includes: a recursively architected network of sub-networks organized into a hierarchical layers; the sub-networks including at least a parent feature node, a pool node, a parent-specific child feature (PSCF) node, and a child feature node; the parent feature node of at least one sub-network configured with a selection function actionable on at least two pool nodes connected to the parent feature node of the at least one sub-network; the pool node of the at least one sub-network configured with a selection function actionable on at least two PSCF nodes connected to the pool node of the at least one sub-network; the PSCF node of the at least one sub-network configured to activate a connected child feature node; the child feature node connectable to at least a parent feature node of a sub-network at a lower hierarchical layer.

## Claims

### Claim 1

A method for generating patterns with a network comprising:
providing a recursive network of sub-networks with a parent feature input node and at least two child feature output nodes;
propagating node selection down the network layer hierarchy in a manner consistent with node connections of sub-networks of the network, the propagation within the sub-network comprising:
at an activated parent feature node of a sub-network, selecting a pool node consistent with a selection function of the parent feature node;
at a pool node of a sub-network, selecting at least a first parent-specific child feature (PSCF) node that corresponds to a child feature node of the sub-network; and
in response to the selection of a first node of the sub-network, enforcing a selection constraint on at least a second node of a second pool according to a lateral constraint node of the sub-network; and
compiling the state of final child feature nodes of the network into a generated output.

### Claim 2 (depends on 1)

The method of claim 1, wherein the first node is the first PSCF node, and the second node of the second pool is a PSCF node.

### Claim 3 (depends on 2)

The method of claim 2, wherein the second PSCF node of the second pool is within the same sub-network.

### Claim 4 (depends on 2)

The method of claim 2, wherein the second PSCF node of the second pool is in a second sub-network.

### Claim 5 (depends on 2)

The method of claim 2, wherein first PSCF node is in a network of a first time instant and the second PSCF node of the second pool is in a network of a second time instant.

### Claim 6 (depends on 2)

The method of claim 2, further comprising in response to selecting the PSCF node selecting at least one child feature node; mapping selected child feature nodes to data features that are compiled into the generated output.

### Claim 7 (depends on 6)

The method of claim 6, wherein the generated output is an image

### Claim 8 (depends on 6)

The method of claim 6, wherein the generated output is a sequence of images.

### Claim 9 (depends on 6)

The method of claim 6, wherein the generated output is audio.

### Claim 10 (depends on 6)

The method of claim 6, wherein the selection functions are Boolean logical selection functions.

### Claim 11 (depends on 10)

The method of claim 10, wherein the child feature nodes of a first layer sub-network are the parent feature nodes for at least two sub-networks in a second layer.

### Claim 12 (depends on 11)

The method of claim 11, wherein selecting the pool node consistent with a selection function comprises selecting each pool node connected to the parent node according to a logical AND selection function; wherein selecting the first PSCF node comprises randomly selecting only one PSCF node from the set of PSCF nodes connected to the pool node according to a logical XOR selection function of the pool node.