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A matlab and python toolkit for functional controllability measurement, dynamic minimum control energy and prediction behavior tasks.

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functional_controllability

This toolkit is for computing the controllability measurements, minimum control energy, and kernel ridge prediction for behavior tasks.

Test environment

  1. Matlab 2018a
  2. Python version 3.6.7
  3. sklearn version 0.19.1

minimum control energy

Use Energy Efficiency/pipelineCompareStaticDynamicEnergy.m to compute the minimum static and dynamic control energy. [Es, Ed, delta_s] = pipelineCompareStaticDynamicEnergy(time_series, control_node, window_size)

Efficiency/pipelineCompareDynamicEnergyAfterShuffle.m to compute the dynamic control energy before and after shuffle. Er = pipelineCompareDynamicEnergyAfterShuffle(time_series, control_node, window_size, shuffle_times)

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A matlab and python toolkit for functional controllability measurement, dynamic minimum control energy and prediction behavior tasks.

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