Patents by Inventor Bart Kosko

Bart Kosko 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: 20200090071
    Abstract: The invention shows how to use noise-like perturbations to improve the speed and accuracy of Markov Chain Monte Carlo (MCMC) estimates and large-scale optimization, simulated annealing optimization, and quantum annealing for large-scale optimization.
    Type: Application
    Filed: August 8, 2016
    Publication date: March 19, 2020
    Applicant: University of Southern California
    Inventors: Brandon FRANZKE, Bart KOSKO
  • Patent number: 9390065
    Abstract: An estimating computer system may iteratively estimate an unknown parameter of a model or state of a system. An input module may receive numerical data about the system. A noise module may generate random, chaotic, or other type of numerical perturbations of the received numerical data and/or may generate pseudo-random noise. An estimation module may iteratively estimate the unknown parameter of the model or state of the system based on the received numerical data. The estimation module may use the numerical perturbations and/or the pseudo-random noise and the input numerical data during at least one of the iterative estimates of the unknown parameter. A signaling module may signal when successive parameter estimates or information derived from successive parameter estimates differ by less than a predetermined signaling threshold or when the number of estimation iterations reaches a predetermined number.
    Type: Grant
    Filed: July 23, 2013
    Date of Patent: July 12, 2016
    Assignee: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Bart Kosko, Osonde Osoba, Sanya Mitaim
  • Publication number: 20160034814
    Abstract: A learning computer system may update parameters and states of an uncertain system.
    Type: Application
    Filed: August 3, 2015
    Publication date: February 4, 2016
    Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Kartik Audhkhasi, Osonde Osoba, Bart Kosko
  • Publication number: 20160019459
    Abstract: A learning computer system may include a data processing system and a hardware processor and may estimate parameters and states of a stochastic or uncertain system.
    Type: Application
    Filed: July 20, 2015
    Publication date: January 21, 2016
    Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Kartik Audhkhasi, Bart Kosko, Osonde Osoba
  • Publication number: 20160005399
    Abstract: A learning computer system may estimate unknown parameters and states of a stochastic or uncertain system having a probability structure. The system may include a data processing system that may include a hardware processor that has a configuration that: receives data; generates random, chaotic, fuzzy, or other numerical perturbations of the data, one or more of the states, or the probability structure; estimates observed and hidden states of the stochastic or uncertain system using the data, the generated perturbations, previous states of the stochastic or uncertain system, or estimated states of the stochastic or uncertain system; and causes perturbations or independent noise to be injected into the data, the states, or the stochastic or uncertain system so as to speed up training or learning of the probability structure and of the system parameters or the states.
    Type: Application
    Filed: July 17, 2015
    Publication date: January 7, 2016
    Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Kartik Audhkhasi, Osonde Osoba, Bart Kosko
  • Publication number: 20150161232
    Abstract: Non-transitory, tangible, computer-readable storage media may contain a program of instructions that enhances the performance of a computing system running the program of instructions when segregating a set of data into subsets that each have at least one similar characteristic. The instructions may cause the computer system to perform operations comprising: receiving the set of data; applying an iterative clustering algorithm to the set of data that segregates the data into the subsets in iterative steps; during the iterative steps, injecting perturbations into the data that have an average magnitude that decreases during the iterative steps; and outputting information identifying the subsets.
    Type: Application
    Filed: November 25, 2014
    Publication date: June 11, 2015
    Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Bart Kosko, Osonde Osoba
  • Publication number: 20140025356
    Abstract: An estimating computer system may iteratively estimate an unknown parameter of a model or state of a system. An input module may receive numerical data about the system. A noise module may generate random, chaotic, or other type of numerical perturbations of the received numerical data and/or may generate pseudo-random noise. An estimation module may iteratively estimate the unknown parameter of the model or state of the system based on the received numerical data. The estimation module may use the numerical perturbations and/or the pseudo-random noise and the input numerical data during at least one of the iterative estimates of the unknown parameter. A signaling module may signal when successive parameter estimates or information derived from successive parameter estimates differ by less than a predetermined signaling threshold or when the number of estimation iterations reaches a predetermined number.
    Type: Application
    Filed: July 23, 2013
    Publication date: January 23, 2014
    Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Osonde Osoba, Bart Kosko, Sanya Mitaim
  • Patent number: 5539769
    Abstract: A system and method for fuzzy spread spectrum communication. The system includes a fuzzy spreader for spreading an input signal over a range of frequencies and fuzzy despreader for extracting the spread input signal from the range of frequencies. In the illustrative implementation, the inventive system a fuzzy pseudo-random generator for use in the fuzzy spreader and the fuzzy despreader. The fuzzy pseudo-random generator uses a novel method for generating pseudo-random numbers. It does not use encryption or decryption techniques. The invention further provides a method for adaptive rule generation and a novel method for identifying the centroid of the set of output numbers. This allows the fuzzy system to learn spreading rules that favor data compression, compact multiplexing, bandwidth conservation, and other communication tasks as well as rules that favor security.
    Type: Grant
    Filed: March 28, 1994
    Date of Patent: July 23, 1996
    Assignee: University of Southern California
    Inventors: Bart Kosko, Peter J. Pacini