Sökning: "Brain-like computing"

Hittade 5 uppsatser innehållade orden Brain-like computing.

  1. 1. Evaluating Brain-Inspired Machine Learning Models for Time Series Forecasting: A Comparative Study on Dynamical Memory in Reservoir Computing and Neural Networks

    Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Eddie Nevander Hellström; Johan Slettengren; [2023]
    Nyckelord :;

    Sammanfattning : Brain-inspired computing is a promising research field, with potential to encouragebreakthroughs within machine learning and enable us to solve complex problems in a moreefficient way. This study aims to compare the performance of brain-like machine learningalgorithms for time series forecasting. LÄS MER

  3. 2. Regression with Bayesian Confidence Propagating Neural Networks

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Raghav Rajendran Bongole; [2023]
    Nyckelord :Machine Learning; Neural Networks; Brain-like computing; Bayesian Confidence Propagating Neural Networks; Maskininlärning; neurala nätverk; hjärnliknande datorer; Bayesian Förtroendespridande neurala nätverk;

    Sammanfattning : Bayesian Confidence Propagating Neural Networks (BCPNNs) are biologically inspired artificial neural networks. These networks have been modeled to account for brain-like aspects such as modular architecture, divisive normalization, sparse connectivity, and Hebbian learning. LÄS MER

  4. 3. Modelling synaptic rewiring in brain-like neural networks for representation learning

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Kunal Bhatnagar; [2023]
    Nyckelord :Adaptive Sparsity; Computational Neuroscience; Rewiring; Structural Plasticity; Brain-like Computing; Neural Networks; Hebbian Learning; Adaptiv gleshet; beräkningsneurovetenskap; omkoppling; strukturell plasticitet; Hjärnliknande beräkning; Neurala Nätverk; Hebbskt lärande;

    Sammanfattning : This research investigated the concept of a sparsity method inspired by the principles of structural plasticity in the brain in order to create a sparse model of the Bayesian Confidence Propagation Neural Networks (BCPNN) during the training phase. This was done by extending the structural plasticity in the implementation of the BCPNN. LÄS MER

  5. 4. Hierarchical Clustering using Brain-like Recurrent Attractor Neural Networks

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Hannah Kühn; [2023]
    Nyckelord :Hierarchical Clustering; Attractor Network; Recurrent Neural Network; Brain-like computing; Hierarkisk klustring; Anlockningsnätverk; Återkommande neurala nätverk; Hjärnliknande databehandling;

    Sammanfattning : Hierarchical clustering is a family of machine learning methods that has many applications, amongst other data science and data mining. This thesis belongs to the research area of brain-like computing and introduces a novel approach to hierarchical clustering using a brain-like recurrent neural network. LÄS MER

  7. 5. A SystemC model for the eBrain

    Master-uppsats, KTH/Skolan för informations- och kommunikationsteknik (ICT)

    Författare :Dimitrios Stathis; [2017]
    Nyckelord :;

    Sammanfattning : The development of neural networks has become one of the most interesting topics in the scientific community. Systems that are based on the brain behavior can find applications in a wide variety of fields, from simulating the brain to better understand it (applications in neuroscience), to control theory and super computing. LÄS MER