, are responsible for a degree of linear independence among components. Roughly speaking, and depending on the relative amplitudes of the components, these terms become important only at times that are long enough so that the quantity ( ) r r t becomes significant. If the signal decays into the noise or if the signal is truncated before these terms become apparent, then the data cannot be used to distinguish a distribution of components having relaxation rates in the range between r  and r  from a single component having the amplitude-weighted average of these relaxation rates.