Browsing Fakultet for teknologi, kunst og design (TKD) by Subject "Reservoir computing"
Now showing items 1-7 of 7
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Comparison and benchmarking of reservoir computing using cellular automata and random boolean networks as substrates
(ACIT;2022, Master thesis, 2022)Reservoir Computing is an emerging concept in artificial intelligence derived from Recurrent Neural Networks, which utilizes an untrained reservoir substrate to memorize and separate input in such a way that it may be ... -
Criticality-Driven Evolution of Adaptable Morphologies of Voxel-Based Soft-Robots
(Frontiers in Robotics and AI;1 June 2021 | Volume 8 | Article 673156, Peer reviewed; Journal article, 2021-06-17)The paradigm of voxel-based soft robots has allowed to shift the complexity from the control algorithm to the robot morphology itself. The bodies of voxel-based soft robots are extremely versatile and more adaptable than ... -
Deep learning with cellular automaton-based reservoir computing
(Complex Systems;Volume 26, Issue 4, Journal article; Peer reviewed, 2017)Recurrent neural networks (RNNs) have been a prominent concept wiithin artificial intelligence. They are inspired by biological neural net works (BNNs) and provide an intuitive and abstract representation of how BNNs work. ... -
The Dynamical Landscape of Reservoir Computing with Elementary Cellular Automata
(Conference object, 2021)Reservoir Computing with Cellular Automata (ReCA) is a promising concept by virtue of its potential for efficient hardware implementation and theoretical understanding of Cellular Auotmata (CA). However, ReCA has so far ... -
EvoDynamic: A Framework for the Evolution of Generally Represented Dynamical Systems and Its Application to Criticality
(Lecture Notes in Computer Science;Volume 12104, Conference object, 2020-04-09)Dynamical systems possess a computational capacity that may be exploited in a reservoir computing paradigm. This paper presents a general representation of dynamical systems which is based on matrix multiplication. That ... -
A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality
(Cognitive Neurodynamics;, Journal article; Peer reviewed, 2020-06-11)Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ... -
Reservoir Computing Using Nonuniform Binary Cellular Automata
(Complex Systems;Volume 26, Issue 3, Journal article; Peer reviewed, 2017)The reservoir computing (RC) paradigm utilizes a dynamical system (a reservoir) and a linear classifier (a readout layer) to process data from sequential classification tasks. In this paper, the usage of cellular automata ...