▁the ▁presence ▁of ▁add itive ▁random ▁noise . ▁That ▁is ▁because ▁the ▁noise ▁produces ▁a ▁stronger ▁response ▁with ▁high - dynamic - range ▁windows ▁than ▁with ▁high - resol ution ▁windows . ▁ ▁At ▁the ▁other ▁extreme ▁of ▁the ▁range ▁of ▁window ▁types ▁are ▁windows ▁with ▁high ▁dynamic ▁range ▁but ▁low ▁resolution ▁and ▁sens itivity . ▁High - dynamic - range ▁windows ▁are ▁most ▁often ▁just ified ▁in ▁wide band ▁applications , ▁where ▁the ▁spectrum ▁being ▁analyz ed ▁is ▁expected ▁to ▁contain ▁many ▁different ▁components ▁of ▁various ▁amplit udes . ▁ ▁In ▁between ▁the ▁extrem es ▁are ▁moder ate ▁windows , ▁such ▁as ▁Ham ming ▁and ▁Hann . ▁They ▁are ▁commonly ▁used ▁in ▁narrow band ▁applications , ▁such ▁as ▁the ▁spectrum ▁of ▁a ▁tele phone ▁channel . ▁ ▁In ▁summary , ▁spectral ▁analysis ▁involves ▁a ▁trade - off ▁between ▁resol ving ▁compar able ▁strength ▁components ▁with ▁similar ▁frequencies ▁( high ▁resolution ▁/ ▁sens itivity ) ▁and ▁resol ving ▁dispar ate ▁strength ▁components ▁with ▁dis similar ▁frequencies ▁( high ▁dynamic ▁range ). ▁That ▁trade - off ▁occurs ▁when ▁the ▁window ▁function ▁is ▁chosen . ▁ ▁Dis crete - time ▁signals ▁▁ ▁When ▁the ▁input ▁wave form ▁is ▁time - sample d , ▁instead ▁of ▁continuous , ▁the ▁analysis ▁is ▁usually ▁done ▁by ▁applying ▁a ▁window ▁function ▁and ▁then ▁a ▁discrete ▁Fourier ▁transform ▁( DF T ). ▁But ▁the ▁D FT ▁provides ▁only ▁a ▁sparse ▁sampling ▁of ▁the ▁actual ▁discrete - time ▁Fourier ▁transform ▁( DT FT ) ▁spectrum . ▁Figure ▁ 2 , ▁row