Results 71 to 80 of about 150,677 (317)
Causal‐Guided Ultra‐Long‐Term Time Series Forecasting Via Anticipated Covariates
Often treated as unknown, information from the future remains underutilized.We demonstrate that in a coupled dynamical system, providing the future state of the effect enables accurate forecasting of the cause for a long timesteps. A time series forecasting paradigm that introduces anticipated covariates to represent such known future states is ...
Jintong Zhao +4 more
wiley +1 more source
Planktonic communities and chaotic advection in dynamical models of Langmuir circulation [PDF]
A deterministic mechanism for the production of plankton patches within a typical medium scale oceanic structure is proposed and investigated. By direct numerical simulation of a simple model of Langmuir circulation we quantify the effects of unsteady ...
Bees, M.A.
core +1 more source
Physical reservoir computing (PRC) based on spin wave interference has demonstrated high computational performance, yet room for improvement remains. In this study, we fabricated this concept PRC with eight detectors and evaluated the impact of the number of detectors using a chaotic time series prediction task.
Sota Hikasa +6 more
wiley +1 more source
Fuzzy clustering chaotic-based differential evolution for resource leveling in construction projects
Project scheduling is an important part of project planning in many management companies. Resource leveling problem describes the process of reducing the fluctuations in resource usage over the project duration.
Min-Yuan Cheng +2 more
doaj +1 more source
Chaotic analogue‐to‐information conversion with chaotic state modulation
Chaotic compressive sensing is a non‐linear framework for compressive sensing. Along the framework, this study proposes a chaotic analogue‐to‐information converter, ‘chaotic modulation’, to acquire and reconstruct band‐limited sparse analogue signals at sub‐Nyquist rate.
Shengyao Chen, Feng Xi, Zhong Liu 0001
openaire +2 more sources
Synchronization of Analog Neuron Circuits With Digital Memristive Synapses: An Hybrid Approach
An hybrid circuit mimicking neural units coupled using memristive synapses is introduced. The analog neurons provide flexibility and robustness, and the digital memristive coupling guarantees the full reconfigurability of the interconnection. The onset of a synchronized spiking behavior in two circuits mimicking the Izhikevich neuron is discussed from ...
Lamberto Carnazza +3 more
wiley +1 more source
Between the crystalline and the chaotic [PDF]
This short feature documents elements of research in advance of a long-term work. Rather than a technical account or retrospective, the aim is to demonstrate by example how research itself is a primary process, illustrated by work carried out at the Institute of Creative Technologies (IOCT) during the last few years.
openaire +2 more sources
In this paper, a modified chaotic shift keying method is proposed to transmit digital bits securely over a communication channel. The scheme is based upon encrypting the digital bits 0 and 1 into infinite levels by applying the keystream such that there
Ghassemlooy, Zabih +5 more
core
On the Role of Preprocessing and Memristor Dynamics in Reservoir Computing for Image Classification
ABSTRACT Reservoir computing (RC) is an emerging recurrent neural network architecture that has attracted growing attention for its low training cost and modest hardware requirements. Memristor‐based circuits are particularly promising for RC, as their intrinsic dynamics can reduce network size and parameter overhead in tasks such as time‐series ...
Rishona Daniels +4 more
wiley +1 more source
Chaotic newton’s sequences [PDF]
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +3 more sources

