Sökning: "Bayesian Confidence Propagation Neural Network BCPNN"

Visar resultat 1 - 5 av 6 uppsatser innehållade orden Bayesian Confidence Propagation Neural Network BCPNN.

1. 1. Modelling Long Term Memory in the Bayesian Confidence Neural Network Model

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

   Författare :Charu Karn; Samir Samahunov; [2023]
   Nyckelord :;

   Sammanfattning : Memory is a fascinating and complex part of human life. Understanding memory and simulating itthrough modelling can help society take steps towards understanding health issues such asAlzheimer's, dementia and amnesia. LÄS MER

3. 2. Role of Context in Episodic Memory : A Bayesian-Hebbian Neural Network Model of Episodic Recall

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

   Författare :Rohan Raj; [2022]
   Nyckelord :episodic memory; long-term memory; Bayesian Confidence Propagation Neural Network; synaptic plasticity; plasticity modulation; computational neuroscience;

   Sammanfattning : Episodic memory forms a fundamental aspect of human memory that accounts for the storage of events as well as the spatio-temporal relations between events during a lifetime. These spatio-temporal relations in which episodes are embedded can be understood as their contexts. Contexts play a crucial role in episodic memory retrieval. LÄS MER

4. 3. The Impact of Selective Plasticity Modulationon Simulated Long Term Memory

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

   Författare :Silvia Barrett; Alicia Palmér; [2021]
   Nyckelord :BCPNN; Long-term memory; Computational brain modeling; Reminiscence bump; Plasticity modulation;

   Sammanfattning : Understanding the brain and its functions is achallenging undertaking. To facilitate this work, brain-inspiredtechnology may be used to examine cognitive phenomena to acertain extent, by replacing real biological brains with simulations. LÄS MER

5. 4. Unsupervised learning of data representations in brain-like neural networks

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

   Författare :Arian Javdan; [2021]
   Nyckelord :;

   Sammanfattning : Recently, there has been a growing interest in brain-plausible neural networks that closely resemble the brain’s structure. However, conventional networks do not make good models for the brain since these connections are modelled differently, hence the interest in brain-plausible networks. LÄS MER

7. 5. Attractor Neural Network modelling of the Lifespan Retrieval Curve

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

   Författare :Patrícia Pereira; [2020]
   Nyckelord :reminiscence bump; attractor neural network; Bayesian Confidence Propagation Neural Network BCPNN ; recency; synaptic plasticity; episodic memory; ”reminiscence bump”; attraktorneuronnät; Bayesian Confidence Propagation Neural Network BCPNN ; nysseffekt; synaptisk plasticitet; episodiskt mine.;

   Sammanfattning : Human capability to recall episodic memories depends on how much time has passed since the memory was encoded. This dependency is described by a memory retrieval curve that reflects an interesting phenomenon referred to as a reminiscence bump - a tendency for older people to recall more memories formed during their young adulthood than in other periods of life. LÄS MER