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Cost-effective vibration analysis through data-backed pipeline optimisation
This often leads to complex and convoluted signal processing pipeline designs, which are computationally demanding and cannot be deployed in the Edge devices.
Volume-Centred Range Bars: Novel Interpretable Representation of Financial Markets Designed for Machine Learning Applications
In this study, we propose a volume-price-based market representation for making financial time series more suitable for machine learning pipelines.
A Generic Methodology for the Statistically Uniform & Comparable Evaluation of Automated Trading Platform Components
This work is one of the first in applying this rigorous statistically-backed approach to the field of financial markets and we hope this may be a springboard for more research.
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