Patents by Inventor Laurent Herault

Laurent Herault 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).

  • Patent number: 8315265
    Abstract: The invention concerns a management process for a network of routers based on the technique of training by reinforcement in which priority is given to objects already present in the network over those which wish to enter.
    Type: Grant
    Filed: July 18, 2006
    Date of Patent: November 20, 2012
    Assignee: Xantima LLC
    Inventors: Dominique Derou-Madeline, Laurent Herault
  • Publication number: 20070091867
    Abstract: The invention concerns a management process for a network of routers based on the technique of training by reinforcement in which priority is given to objects already present in the network over those which wish to enter.
    Type: Application
    Filed: July 18, 2006
    Publication date: April 26, 2007
    Inventors: Dominique Derou-Madeline, Laurent Herault
  • Patent number: 7079487
    Abstract: The invention concerns a management process for a network of routers based on the technique of training by reinforcement in which priority is given to objects already present in the network over those which wish to enter.
    Type: Grant
    Filed: December 18, 2001
    Date of Patent: July 18, 2006
    Inventors: Dominique Derou-Madeline, Laurent Herault
  • Publication number: 20030145111
    Abstract: The invention concerns a management process for a network of routers based on the technique of training by reinforcement in which priority is given to objects already present in the network over those which wish to enter.
    Type: Application
    Filed: December 18, 2001
    Publication date: July 31, 2003
    Inventors: Dominique Derou-Madeline, Laurent Herault
  • Patent number: 5963584
    Abstract: Direct sequence spread spectrum transmission process that generates and optimizes sequences used by respective users of a communications system. A set of random sequences is produced and the sequences are optimized by a combinatorial operation in order to minimize residual noise. The random sequences belong to an M.sup.th set of roots unity, where respective of the N random sequences have given length L.
    Type: Grant
    Filed: November 7, 1997
    Date of Patent: October 5, 1999
    Assignee: Commissariat a l'Energie Atomique
    Inventors: Christophe Boulanger, Jean-Rene Lequepeys, Laurent Herault
  • Patent number: 5696882
    Abstract: Method and apparatus for selecting an optimized subset of trajectories from an available class of potential trajectories in a velocimetry application. In an exemplary method, a neural network is constructed wherein each neuron in the network represents a trajectory in the overall class. A binary output of each neuron indicates whether the object represented by the neuron is to be selected. In the exemplary method, the neural network is in an initially converged state. The network is then alternately excited and constrained so that it settles to additional converged states. During excitation, correction factors including a parameter-optimizing term are applied to neuron input potentials. During constraint, the parameter-optimizing terms are interrupted. Each time the network converges, the outputs of the neurons in the network are decoded to establish a subset of trajectories to be selected, and a value for an optimization parameter associated with the established subset is computed.
    Type: Grant
    Filed: April 18, 1995
    Date of Patent: December 9, 1997
    Assignee: Commissariat a l'Energie Atomique
    Inventor: Laurent Herault
  • Patent number: 5675712
    Abstract: Method and apparatus for selecting an optimal number of trajectories from an available class of potential trajectories in a velocimetry application. In an exemplary method, a neural network is constructed wherein each neuron in the network represents a trajectory in the overall class. A binary output of each neuron indicates whether the trajectory represented by the neuron is to be selected. In the exemplary method, the neural network is initialized with a starting solution wherein the network is in an initially converged state. The network is then alternately excited and constrained so that it settles to additional converged states. During excitation, correction factors including a set-size maximizing term are applied to neuron input potentials. During constraint, the set-size maximizing terms are interrupted. Each time the network converges, the outputs of the neurons in the network are decoded to obtain a subset of trajectories which are to be selected.
    Type: Grant
    Filed: April 18, 1995
    Date of Patent: October 7, 1997
    Assignee: Commissariat a l'Energie Atomique
    Inventor: Laurent Herault
  • Patent number: 5598355
    Abstract: The invention relates to a process for obtaining trajectories of moving objects, by optimizing at least one criterion from the physics of the phenomenon observed and comprising the following stages: a stage of recording signals (10), a stage (11) of extracting given parts of the signals, a stage (12) of subdividing the group of parts of the signals previously extracted into classes, each class representing a potential trajectory, a stage (13, 14) of selecting a subset of classes satisfying constraints linked with the observed network type, a stage (15) of selecting from among the classes representing the potential trajectories those satisfying the constraints, so as to obtain "real" trajectories of the objects. The invention also relates to a device for performing this process.
    Type: Grant
    Filed: April 18, 1995
    Date of Patent: January 28, 1997
    Assignee: Commissariat a l'Energie Atomique
    Inventors: Dominique Derou, Laurent Herault