The 4th International Conference on Working Memory
DOI: 10.13140/RG.2.2.19565.60644 Abstract Dorota Styk & Eddy J. DavelaarSchool of Psychological SciencesBirkbeck, University of London Novel approach in
The 4th International Conference on Working Memory (2024)
Åkerlund E, Esbjornsson E, Sunnerhagen KS, Bjorkdahl A (2013). Can computerized working memory training improve impaired working memory, cognition and
Adaptive N-back Task using Hidden Markov Models – PYTHON
Table of Contents Introduction Installation Required Imports Data Preparation Parameter Estimation Model Initialization Online Adaptation Performance
N-back- adaptive training HMM
Adaptive n-back task using Hidden Markov Models (HMM) based on reaction time and response accuracy, follow these steps: Process Overview Data Collection:
WMT: Why Use HMM with Gaussian Emissions?
Why Use HMM with Gaussian Emissions?In the context of creating an adaptive n-back task using Hidden Markov Models (HMMs), we use HMM with Gaussian emissions