signal

Value Members

1. def fft[Input, Output](v: Input)(implicit canFFT: CanFFT[Input, Output]): Output

   Returns the fast fourier transform of a DenseVector or DenseMatrix.

   Returns the fast fourier transform of a DenseVector or DenseMatrix. Currently, DenseVector/DenseMatrix types of Double and Complex are supported. Scaling follows the common signal processing convention, i.e. no scaling on forward DFT, and 1/n scaling for the inverse DFT. Of note, fft(x: DenseMatrix[Double]) will perform the 2D fft in both row and column dimensions, as opposed to the MatLab toolbox syntax, which performs column-wise 1D fft. Implementation is via the implicit trait CanFFT[ InputType, OutputType ], which is found in breeze.signal.support.CanFFT.scala.

   v

   DenseVector or DenseMatrix to be fft'ed

   canFFT

   implicit delegate which is used for implementation. End-users should not use this argument.

   returns

2. def ifft[Input, Output](v: Input)(implicit canIFFT: CanIFFT[Input, Output]): Output

   Returns the inverse fast fourier transform of a DenseVector or DenseMatrix.

   Returns the inverse fast fourier transform of a DenseVector or DenseMatrix. Currently, DenseVector/DenseMatrix types of Double and Complex are supported. Scaling follows the common signal processing convention, i.e. no scaling on forward DFT, and 1/n scaling for the inverse DFT. Of note, ifft(x: DenseMatrix[Double]) will perform the 2D ifft in both row and column dimensions, as opposed to the MatLab toolbox syntax, which performs column-wise 1D ifft. Implementation is via the implicit trait CanIFFT[ InputType, OutputType ], which is found in breeze.signal.support.CanIFFT.scala.

   v

   DenseVector or DenseMatrix to be fft'ed

   canIFFT

   implicit delegate which is used for implementation. End-users should not use this argument.

   returns

3. package support