Skip to main content
Signal Processing

Return to Answer

added 86 characters in body
Source Link
hotpaw2
hotpaw2
  • 36k
  • 10
  • 49
  • 94

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that infinite series of Sinc functions will be conjugate mirrored (needed to cancel out any imaginary components in the real data). The

The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large for frequency peaks near DC and Fs/2, where higher portions of the 2 Sincs overlap. (and thusThus, the conjugate mirror interference will be smaller near Fs/4, use that frequency if you want to see symmetry).

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that infinite series of Sinc functions will be conjugate mirrored (needed to cancel out any imaginary components in the real data). The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large near DC and Fs/2 (and thus smaller near Fs/4, use that frequency if you want to see symmetry).

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that infinite series of Sinc functions will be conjugate mirrored (needed to cancel out any imaginary components in the real data).

The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large for frequency peaks near DC and Fs/2, where higher portions of the 2 Sincs overlap. (Thus, the conjugate mirror interference will be smaller near Fs/4, use that frequency if you want to see symmetry).

added 27 characters in body
Source Link
hotpaw2
hotpaw2
  • 36k
  • 10
  • 49
  • 94

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that infinite series of Sinc functions will be conjugate mirrored (needed to cancel out any imaginary components in the real data). The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large near DC and Fs/2 (and thus smaller near Fs/4, use that frequency if you want to see symmetry).

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that series will be conjugate mirrored (needed to cancel out any imaginary components in the real data). The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large near DC and Fs/2.

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that infinite series of Sinc functions will be conjugate mirrored (needed to cancel out any imaginary components in the real data). The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large near DC and Fs/2 (and thus smaller near Fs/4, use that frequency if you want to see symmetry).

Source Link
hotpaw2
hotpaw2
  • 36k
  • 10
  • 49
  • 94

For sampled strictly real data, the Sinc function will be repeated periodically across an infinite spectrum (this is what allows undersampling to work) (sum called a Dirichlet kernel), and that series will be conjugate mirrored (needed to cancel out any imaginary components in the real data). The "interference" from conjugate mirrored Sinc (with the shape of the assumed symmetric Sinc) is especially large near DC and Fs/2.