Exploring emergent properties of recurrent neural networks using a novel energy function formalism
The stability analysis of dynamical neural network systems typically involves finding a
suitable Lyapunov function, as demonstrated in Hopfield's famous paper on content …
suitable Lyapunov function, as demonstrated in Hopfield's famous paper on content …
A Computational Framework for Time's Subjective Expansion in Temporal Oddball Paradigm Using Recurrent Neural Network
R Sengupta, A Shukla… - 2024 10th International …, 2024 - ieeexplore.ieee.org
In behavioral psychology, the temporal oddball paradigm is a widely used tool to investigate
the relationship between attention and time perception, specifically focusing on a …
the relationship between attention and time perception, specifically focusing on a …
Comparing Visual and Auditory P300-based Brain-Computer Interfaces: An Experimental Study
Brain-computer interfaces (BCIs) have traditionally focused on visual paradigms, with the
P300-based EEGBCI being a common approach. However, auditory BCIs are gaining …
P300-based EEGBCI being a common approach. However, auditory BCIs are gaining …
How embodied is time?
R Sengupta - Journal of Indian Council of Philosophical Research, 2018 - Springer
It is a standard understanding that we live in time. In fact, the whole physical world as
described in sciences is based on the idea of objective (not absolute) time. For centuries, we …
described in sciences is based on the idea of objective (not absolute) time. For centuries, we …
From neural network to psychophysics of time: Exploring emergent properties of RNNs using novel Hamiltonian formalism
The stability analysis of dynamical neural network systems generally follows the route of
finding a suitable Liapunov function after the fashion Hopfield's famous paper on content …
finding a suitable Liapunov function after the fashion Hopfield's famous paper on content …