Pages that link to "Item:Q551124"
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The following pages link to Neural network method for determining embedding dimension of a time series (Q551124):
Displaying 21 items.
- Evaluating Lyapunov exponent spectra with neural networks (Q400825) (← links)
- Influence of data dimensionality on the quality of forecasts given by a multilayer perceptron (Q870257) (← links)
- Practical method for determining the minimum embedding dimension of a scalar time series (Q1373907) (← links)
- Modelling temporal series through synaptic delay-based neural networks (Q1403018) (← links)
- Modified multiscale cross-sample entropy for complex time series (Q1733624) (← links)
- Development of a new diagnostic protocol using a neuro-dynamical tool (Q1775719) (← links)
- Optimal embedding parameters: a modelling paradigm (Q1888128) (← links)
- Detecting high-dimensional determinism in time series with application to human movement data (Q1926167) (← links)
- Chaoticity versus stochasticity in financial markets: are daily S\&P 500 return dynamics chaotic? (Q2076249) (← links)
- Robustness of LSTM neural networks for multi-step forecasting of chaotic time series (Q2122985) (← links)
- Exploring time-delay-based numerical differentiation using principal component analysis (Q2139951) (← links)
- NF-CECP: a novel approach to distinguish signals with different properties via modified Fisher information measure (Q2208089) (← links)
- Flow field forecasting for univariate time series (Q2870759) (← links)
- Methodology of estimating the embedding dimension in chaos time series based on the prediction performance of radial basis function neural networks (Q2888676) (← links)
- A Tribute to J. C. Sprott (Q4602538) (← links)
- Determining the Minimum Embedding Dimensions of Input–Output Time Series Data (Q4941321) (← links)
- Compound method of time series classification (Q4968033) (← links)
- Machine Learning of Time Series Using Time-Delay Embedding and Precision Annealing (Q5214389) (← links)
- New Computational Paradigms (Q5717058) (← links)
- Time series prediction and neural networks (Q5955301) (← links)
- A new parameter-free entropy based on fragment oscillation and its application in fault diagnosis (Q6199718) (← links)
