Jove
Visualize
Contact Us

Related Experiment Videos

Real time distributed processing of multiple associated pulse pattern sequences.

A J Travis

    Neural Networks : the Official Journal of the International Neural Network Society
    |October 30, 2001
    PubMed
    Summary
    This summary is machine-generated.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    The Domestic Dog Embryo: In Vitro Fertilization, Culture, and Transfer.

    Methods in molecular biology (Clifton, N.J.)·2019
    Same author

    Anti-Müllerian Hormone in the Domestic Dog during the Anestrus to Oestrous Transition.

    Reproduction in domestic animals = Zuchthygiene·2015
    Same author

    What sperm can teach us about energy production.

    Reproduction in domestic animals = Zuchthygiene·2012
    Same author

    Development of new stem cell-based technologies for carnivore reproduction research.

    Reproduction in domestic animals = Zuchthygiene·2009
    Same author

    A defined medium supports changes consistent with capacitation in stallion sperm, as evidenced by increases in protein tyrosine phosphorylation and high rates of acrosomal exocytosis.

    Theriogenology·2008
    Same author

    Germ cell transplantation for the propagation of companion animals, non-domestic and endangered species.

    Reproduction, fertility, and development·2007
    Same journal

    Q-learning based asynchronous Boolean control networks stabilization with data loss.

    Neural networks : the official journal of the International Neural Network Society·2026
    Same journal

    New results on prescribed-time synchronization of complex networks via intermittent control.

    Neural networks : the official journal of the International Neural Network Society·2026
    Same journal

    Variance-constrained multi-view ensemble broad network for imbalanced data.

    Neural networks : the official journal of the International Neural Network Society·2026
    Same journal

    Dynamic analysis and reliable mechanical optimization application of ring HNN effected with a memristive neuron.

    Neural networks : the official journal of the International Neural Network Society·2026
    Same journal

    DAFF-Net: A detection and search method for small-scale low surface brightness galaxies.

    Neural networks : the official journal of the International Neural Network Society·2026
    Same journal

    Quasi-synchronization for complex networks with hybrid pinning intermittent control.

    Neural networks : the official journal of the International Neural Network Society·2026
    See all related articles
    JoVE
    x logofacebook logolinkedin logoyoutube logo
    ABOUT JoVE
    OverviewLeadershipBlogJoVE Help Center
    AUTHORS
    Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
    LIBRARIANS
    TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
    RESEARCH
    JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
    EDUCATION
    JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
    Terms & Conditions of Use
    Privacy Policy
    Policies

    A novel Real Time Distributed Associative Memory Artificial Neural Network (RTANN) learns to associate and regenerate pulse patterns. This artificial neural network can generate novel descriptive sentences about object combinations after real-time training.

    Area of Science:

    • Artificial Intelligence
    • Computational Neuroscience
    • Machine Learning

    Background:

    • Traditional artificial neural networks often require extensive offline training.
    • Associative memory models are crucial for pattern recognition and recall.
    • Real-time learning capabilities are essential for dynamic environments.

    Purpose of the Study:

    • To introduce a Real Time Distributed Associative Memory Artificial Neural Network (RTANN).
    • To demonstrate real-time training and pattern regeneration capabilities.
    • To evaluate the network's ability to generalize and generate novel associations.

    Main Methods:

    • Developed an RTANN architecture with units processing pulse pattern sequences.
    • Incorporated a wide range of transmission delays within network connections.

    Related Experiment Videos

  • Implemented a training mechanism that enhances connection weights based on pulse coincidences.
  • Utilized pattern regeneration through the reoccurrence of coincidences between delayed pulses.

    • Main Results:

    • The RTANN successfully associated dual pattern sequences representing object shape and color.
    • The network demonstrated real-time learning by direct input of pattern sequences.
    • Simulations showed the RTANN could regenerate associated patterns and generate novel descriptive sentences.
    • The network generalized to describe object-color combinations not present in the training data.

    Conclusions:

    • RTANNs offer a viable model for real-time associative memory and pattern regeneration.
    • The network's ability to generalize suggests potential for complex cognitive tasks.
    • This approach advances artificial neural network capabilities in dynamic learning and creative generation.