Douglas G Moore

US Patent:

7765029, Jul 27, 2010

Filed:

Sep 11, 2006

Appl. No.:

11/530685

Inventors:

Jason G. Fleischer - Del Mar CA, US
Botond Szatmary - Del Mar CA, US
Donald B. Hutson - San Diego CA, US
Douglas A. Moore - San Diego CA, US
James A. Snook - San Diego CA, US
Gerald M. Edelman - La Jolla CA, US
Jeffrey L. Krichmar - Cardiff-by-the-Sea CA, US

Assignee:

Neurosciences Research Foundation, Inc. - San Diego CA

International Classification:

G06N 3/02
G05B 13/00
G06F 19/00
G06E 1/00

US Classification:

700250, 700 48, 700 61, 700249, 700255, 700259, 706 14, 706 15, 706 16, 706 20

Abstract:

A brain-based device (BBD) for moving in a real-world environment has sensors that provide data about the environment, actuators to move the BBD, and a hybrid controller which includes a neural controller having a simulated nervous system being a model of selected areas of the human brain and a non-neural controller based on a computational algorithmic network. The neural controller and non-neural controller interact with one another to control movement of the BBD.

US Patent:

8473436, Jun 25, 2013

Filed:

Nov 18, 2009

Appl. No.:

12/621243

Inventors:

Douglas A. Moore - San Diego CA, US
Kristi H. Tsukida - San Diego CA, US
Paulo B. Ang - Antioch CA, US

Assignee:

The Intellisis Corporation - San Diego CA

International Classification:

G06E 1/00

US Classification:

706 15

Abstract:

Disclosed are systems, methods, and computer-program products for segmenting content of an input signal and applications thereof. In an embodiment, the system includes simulated neurons, a phase modulator, and an entity-identifier module. Each simulated neuron is connected to one or more other simulated neurons and is associated with an activity and a phase. The activity and the phase of each simulated neuron is set based on the activity and the phase of the one or more other simulated neurons connected to each simulated neuron. The phase modulator includes individual modulators, each configured to modulate the activity and the phase of each of the plurality of simulated neurons based on a modulation function. The entity-identifier module is configured to identify one or more distinct entities (e. g. , objects, sound sources, etc.

US Patent:

8521671, Aug 27, 2013

Filed:

Aug 4, 2010

Appl. No.:

12/850352

Inventors:

Douglas A. Moore - San Diego CA, US

Assignee:

The Intellisis Corporation - San Diego CA

International Classification:

G06E 1/00
G06E 3/00
G06F 15/18
G06G 7/00

US Classification:

706 20

Abstract:

Disclosed are systems, apparatuses, and methods for clustering data. Such a method includes providing input data to each of a plurality of cluster microcircuits of a neural network, wherein each cluster microcircuit includes a mean neural group and a variance neural group. The method also includes determining a response of each cluster microcircuit with respect to the input data. The method further includes modulating the mean neural group and the variance neural group of each cluster microcircuit responsive to a value system.

US Patent:

8543526, Sep 24, 2013

Filed:

Sep 16, 2010

Appl. No.:

12/883313

Inventors:

Douglas A. Moore - San Diego CA, US

Assignee:

The Intellisis Corporation - San Diego CA

International Classification:

G06F 15/00
G06F 17/00
G06N 3/10

US Classification:

706 44

Abstract:

Systems, methods, and computer program products are provided to provide noise reduction for an input signal using a neural network. A feed-forward set of neuron groups is provided to enhance neuron activity within a particular frequency band based on prior reception of activity within that frequency band, and also to attenuate surrounding frequency bands. A surround-inhibition set of neuron groups further attenuates activity surrounding the stimulated frequency band.

US Patent:

8583286, Nov 12, 2013

Filed:

Apr 4, 2012

Appl. No.:

13/439702

Inventors:

Jason G. Fleischer - Del Mar CA, US
Botond Szatmáry - Del Mar CA, US
Donald B. Hutson - San Diego CA, US
Douglas A. Moore - San Diego CA, US
James A. Snook - San Diego CA, US
Gerald M. Edelman - La Jolla CA, US
Jeffrey L. Krichmar - Cardiff-by-the-Sea CA, US

Assignee:

Neurosciences Research Foundation, Inc. - La Jolla CA

International Classification:

G06N 3/04
G05B 13/00
G06E 1/00
G05B 15/02

US Classification:

700259, 700245, 700250, 700255, 700258, 901 1, 901 46, 901 47, 901 50

Abstract:

A brain-based device (BBD) for moving in a real-world environment has sensors that provide data about the environment, actuators to move the BBD, and a hybrid controller which includes a neural controller having a simulated nervous system being a model of selected areas of the human brain and a non-neural controller based on a computational algorithmic network. The neural controller and non-neural controller interact with one another to control movement of the BBD.

US Patent:

20110022230, Jan 27, 2011

Filed:

Jul 23, 2010

Appl. No.:

12/842914

Inventors:

Jason G. Fleischer - Del Mar CA, US
Botond Szatmary - Del Mar CA, US
Donald B. Hutson - San Diego CA, US
Douglas A. Moore - San Diego CA, US
James A. Snook - San Diego CA, US
Gerald M. Edelman - La Jolla CA, US
Jeffrey L. Krichmar - Cardiff-by-the-Sea CA, US

Assignee:

NEUROSCIENCES RESEARCH FOUNDATION, INC. - San Diego CA

International Classification:

G05B 19/04

US Classification:

700250

Abstract:

A brain-based device (BBD) for moving in a real-world environment has sensors that provide data about the environment, actuators to move the BBD, and a hybrid controller which includes a neural controller having a simulated nervous system being a model of selected areas of the human brain and a non-neural controller based on a computational algorithmic network. The neural controller and non-neural controller interact with one another to control movement of the BBD.

US Patent:

20110270789, Nov 3, 2011

Filed:

Aug 10, 2010

Appl. No.:

12/853939

Inventors:

Douglas A. MOORE - San Diego CA, US

International Classification:

G06N 3/08

US Classification:

706 25

Abstract:

Disclosed are systems, apparatuses, and methods for implementing a competitive BCM learning rule used in a neural network. Such a method includes identifying a maximally responding neuron with respect to a feature of an input signal. The maximally responding neuron is the neuron in a group that has a response with respect to the feature of the input signal that is greater than a response of each other neuron in the group. Such a method also includes applying a learning rule to weaken the response of each other neuron with respect to the feature of the input signal. The learning rule may also strengthen the response of the maximally responding neuron with respect to the feature of the input signal.

US Patent:

6321928, Nov 27, 2001

Filed:

Oct 27, 2000

Appl. No.:

9/698634

Inventors:

Kim M. Goldenstein - San Diego CA
George T. Lowe - San Diego CA
Douglas R. Moore - Ault CO
Donald J. Pagano - Escondido CA

Assignee:

V.I.T. Products, Inc. - Escondido CA

International Classification:

B65D 8876

US Classification:

220484

Abstract:

An enclosure installation assembly comprises a support base and a mounting pad adapted to be secured to the support base. The support base, having a lower portion slightly larger than its upper portion, is placed in a hole in the ground. Dirt is compacted around the support base to secure the support base in place. The mounting pad is then secured to the support base using support braces that internally engage the support base and fasteners that engage the mounting pad. Finally, an enclosure is installed on the mounting pad, with fasteners located inside the enclosure. The resulting enclosure is securely and easily installed, and is tamper resistant.

Author:

Douglas Moore

ISBN #:

0393002004

Author:

Douglas Moore

ISBN #:

0881880043

Author:

Douglas E. Moore

ISBN #:

0306441047

Author:

Douglas W. Moore

ISBN #:

0811724980

Author:

Douglas W. Moore

ISBN #:

0811728560

Author:

Douglas W. Moore

ISBN #:

0811728692

Author:

Douglas W. Moore

ISBN #:

0811729192

Author:

Douglas V. Moore

ISBN #:

0937462012