| CPC G06F 18/214 (2023.01) [G06F 1/022 (2013.01); G06F 2218/12 (2023.01); G06N 3/08 (2013.01)] | 20 Claims |

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1. A method for producing synthetic signals for testing machine-learning systems, comprising:
generating a set of N composite sinusoidal signals, wherein each of the N composite sinusoidal signals is an additive combination of multiple constituent sinusoidal signals with different periodicities;
adding time-varying random noise values to each of the N composite sinusoidal signals, wherein a standard deviation of the time-varying random noise values varies over successive time periods;
multiplying each of the N composite sinusoidal signals by time-varying amplitude values, wherein the time-varying amplitude values vary over successive time periods; and
adding time-varying mean values to each of the N composite sinusoidal signals, wherein the time-varying mean values vary over successive time periods.
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