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Found 9 papers, 0 papers with code
Reservoir Computing Using Measurement-Controlled Quantum Dynamics
In this paper, we introduce a quantum RC system that employs the dynamics of a probed atom in a cavity.
Physical Reservoir Computing Enabled by Solitary Waves and Biologically-Inspired Nonlinear Transformation of Input Data
Reservoir computing (RC) systems can efficiently forecast chaotic time series using nonlinear dynamical properties of an artificial neural network of random connections.
Quantum-Inspired Neural Network Model of Optical Illusions
Ambiguous optical illusions have been a paradigmatic object of fascination, research and inspiration in arts, psychology and video games.
The Physics of Preference: Unravelling Imprecision of Human Preferences through Magnetisation Dynamics
Paradoxical decision-making behaviours such as preference reversal often arise from imprecise or noisy human preferences.
Linking Physics and Psychology of Bistable Perception Using an Eye Blink Inspired Quantum Harmonic Oscillator Model
This paper introduces a novel quantum-mechanical model that describes psychological phenomena using the analogy of a harmonic oscillator represented by an electron trapped in a potential well.
Analogue and Physical Reservoir Computing Using Water Waves
This article reviews and critically analyses the recent advances in the field of analogue and reservoir computing that have been driven by unique physical properties and energy of water waves.
Musical creativity enabled by nonlinear oscillations of a bubble in water
Producing original and arranging existing musical outcomes is an art that takes years of learning and practice to master.
Reservoir computing based on solitary-like waves dynamics of film flows: a proof of concept
Several theoretical works have shown that solitons -- waves that self-maintain constant shape and velocity as they propagate -- can be used as a physical computational reservoir, a concept where machine learning algorithms designed for digital computers are replaced by analog physical systems that exhibit nonlinear dynamical behaviour.
Neural Echo State Network using oscillations of gas bubbles in water
In the framework of physical reservoir computing (RC), machine learning algorithms designed for digital computers are executed using analog computer-like nonlinear physical systems that can provide energy-efficient computational power for predicting time-dependent quantities that can be found using nonlinear differential equations.
