def noelle_5(h1, h2): # 26 us @array, 52 us @list \w 100 bins
    r"""
    Extension of `fidelity_based` proposed by [1]_.
    
    .. math::
    
        d_{\sin F}(H, H') = \sqrt{1 -d_{F}^2(H, H')}
    
    See `fidelity_based` for the definition of :math:`d_{F}(H, H')`.
                
    *Attributes:*

    - metric
    
    *Attributes for normalized histograms:*

    - :math:`d(H, H')\in[0, 1]`
    - :math:`d(H, H) = 0`
    - :math:`d(H, H') = d(H', H)`
    
    *Attributes for not-normalized histograms:*

    - not applicable
    
    *Attributes for not-equal histograms:*

    - not applicable
    
    Parameters
    ----------
    h1 : sequence
        The first histogram, normalized.
    h2 : sequence
        The second histogram, normalized, same bins as ``h1``.
    
    Returns
    -------
    fidelity_based : float
        Fidelity based distance.
    
    References
    ----------
    .. [1] M. Noelle "Distribution Distance Measures Applied to 3-D Object Recognition", 2003
    """
    return math.sqrt(1 - math.pow(fidelity_based(h1, h2), 2))