Patents by Inventor Robert M. TAYLOR, Jr.

Robert M. TAYLOR, Jr. has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Publication number: 20240283945
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Application
    Filed: January 30, 2024
    Publication date: August 22, 2024
    Applicant: The MITRE Corporation
    Inventors: Robert M. TAYLOR, JR., Jeffrey P. WOODARD
  • Patent number: 11895303
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Grant
    Filed: May 24, 2021
    Date of Patent: February 6, 2024
    Assignee: The MITRE Corporation
    Inventors: Robert M. Taylor, Jr., Jeffrey P. Woodard
  • Patent number: 11221990
    Abstract: A system for machine learning model parameters for image compression, including partitioning image files into a first set of regions, determining a first set of machine learned model parameters based on the regions, the first set of machine learned model parameters representing a first level of patterns in the image files, constructing a representation of each of the regions based on the first set of machine learned model parameters, constructing representations of the image files by combining the representations of the regions in the first set of regions, partitioning the representations of the image files into a second set of regions, and determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the image files.
    Type: Grant
    Filed: April 3, 2015
    Date of Patent: January 11, 2022
    Assignee: The MITRE Corporation
    Inventors: Robert M. Taylor, Jr., Burhan Necioglu
  • Publication number: 20210281860
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Application
    Filed: May 24, 2021
    Publication date: September 9, 2021
    Applicant: The MITRE Corporation
    Inventors: Robert M. TAYLOR, JR., Jeffrey P. WOODARD
  • Patent number: 11051030
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Grant
    Filed: January 6, 2020
    Date of Patent: June 29, 2021
    Assignee: The MITRE Corporation
    Inventors: Robert M. Taylor, Jr., Jeffrey P. Woodard
  • Publication number: 20200145673
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Application
    Filed: January 6, 2020
    Publication date: May 7, 2020
    Applicant: The MITRE Corporation
    Inventors: Robert M. TAYLOR, JR., Jeffrey P. WOODARD
  • Patent number: 10531099
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Grant
    Filed: September 30, 2016
    Date of Patent: January 7, 2020
    Assignee: The MITRE Corporation
    Inventors: Robert M. Taylor, Jr., Jeffrey P. Woodard
  • Publication number: 20180097557
    Abstract: A system and method for implementing a distributed source coding quantization scheme is provided. In one example, two independent but statistically correlated data sources can be asymmetrically compressed so that one source is compressed at a higher ratio than the other. The resulting signals are transmitted and decoded by a receiver. The highly compressed source can utilize the non-highly compressed source as side information so as to minimize the compression loss associated with the higher compression ratio. A conditional codebook can be created that not only depends on the highly compressed quantizer, but also depends on the quantized symbol received from the non-highly compressed data source.
    Type: Application
    Filed: September 30, 2016
    Publication date: April 5, 2018
    Applicant: The MITRE Corporation
    Inventors: Robert M. TAYLOR, JR., Jeffrey P. WOODARD
  • Publication number: 20160292589
    Abstract: A system for machine learning model parameters for image compression, including partitioning image files into a first set of regions, determining a first set of machine learned model parameters based on the regions, the first set of machine learned model parameters representing a first level of patterns in the image files, constructing a representation of each of the regions based on the first set of machine learned model parameters, constructing representations of the image files by combining the representations of the regions in the first set of regions, partitioning the representations of the image files into a second set of regions, and determining a second set of machine learned model parameters based on the second set of regions, the second set of machine learned model parameters representing a second level of patterns in the image files.
    Type: Application
    Filed: April 3, 2015
    Publication date: October 6, 2016
    Applicant: The MITRE Corporation
    Inventors: Robert M. TAYLOR, Jr., Burhan NECIOGLU