Convolution and Correlation Functions

Convolution is an operation used to define an output signal from any linear time-invariant (LTI) processor in response to any input signal.

The correlation functions described in this section estimate either the auto-correlation of a source vector or the cross-correlation of two vectors.

• Special Arguments
  
• AutoCorrNormGetBufferSize
  Computes the size of the work buffer for the ippsAutoCorrNorm function.
• AutoCorrNorm
  Calculates normal, biased, and unbiased auto-correlation of a vector.
• CrossCorrNormGetBufferSize
  Computes the size of the work buffer for the ippsCrossCorrNorm function.
• CrossCorrNorm
  Calculates the cross-correlation of two vectors.
• ConvolveGetBufferSize
  Computes the size of the work buffer for the ippsConvolve function.
• Convolve
  Performs a finite linear convolution of two vectors.
• ConvBiased
  Computes the specified number of elements of the full finite linear convolution of two vectors.