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Diffstat (limited to 'ml/dlib/dlib/matrix/matrix_conv_abstract.h')
| -rw-r--r-- | ml/dlib/dlib/matrix/matrix_conv_abstract.h | 158 |
1 files changed, 0 insertions, 158 deletions
diff --git a/ml/dlib/dlib/matrix/matrix_conv_abstract.h b/ml/dlib/dlib/matrix/matrix_conv_abstract.h deleted file mode 100644 index b342f2668..000000000 --- a/ml/dlib/dlib/matrix/matrix_conv_abstract.h +++ /dev/null @@ -1,158 +0,0 @@ -// Copyright (C) 2011 Davis E. King (davis@dlib.net) -// License: Boost Software License See LICENSE.txt for the full license. -#undef DLIB_MATRIx_CONV_ABSTRACT_Hh_ -#ifdef DLIB_MATRIx_CONV_ABSTRACT_Hh_ - -#include "matrix_abstract.h" - -namespace dlib -{ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp conv ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - ensures - - returns a matrix R such that: - - R is the convolution of m1 with m2. In particular, this function is - equivalent to performing the following in matlab: R = conv2(m1,m2). - - R::type == the same type that was in m1 and m2. - - R.nr() == m1.nr()+m2.nr()-1 - - R.nc() == m1.nc()+m2.nc()-1 - !*/ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp xcorr ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - ensures - - returns a matrix R such that: - - R is the cross-correlation of m1 with m2. In particular, this - function returns conv(m1,flip(m2)) if the matrices contain real - elements and conv(m1,flip(conj(m2))) if they are complex. - - R::type == the same type that was in m1 and m2. - - R.nr() == m1.nr()+m2.nr()-1 - - R.nc() == m1.nc()+m2.nc()-1 - !*/ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp xcorr_fft ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - - m1 and m2 contain real or complex values and must be double, float, or long - double valued. (e.g. not integers) - ensures - - This function is identical to xcorr() except that it uses a fast Fourier - transform to do the convolution and is therefore much faster when both m1 and - m2 are large. - !*/ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp conv_same ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - ensures - - returns a matrix R such that: - - R is the convolution of m1 with m2. In particular, this function is - equivalent to performing the following in matlab: R = conv2(m1,m2,'same'). - In particular, this means the result will have the same dimensions as m1 and will - contain the central part of the full convolution. Therefore, conv_same(m1,m2) is - equivalent to subm(conv(m1,m2), m2.nr()/2, m2.nc()/2, m1.nr(), m1.nc()). - - R::type == the same type that was in m1 and m2. - - R.nr() == m1.nr() - - R.nc() == m1.nc() - !*/ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp xcorr_same ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - ensures - - returns a matrix R such that: - - R is the cross-correlation of m1 with m2. In particular, this - function returns conv_same(m1,flip(m2)) if the matrices contain real - elements and conv_same(m1,flip(conj(m2))) if they are complex. - - R::type == the same type that was in m1 and m2. - - R.nr() == m1.nr() - - R.nc() == m1.nc() - !*/ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp conv_valid ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - ensures - - returns a matrix R such that: - - R is the convolution of m1 with m2. In particular, this function is - equivalent to performing the following in matlab: R = conv2(m1,m2,'valid'). - In particular, this means only elements of the convolution which don't require - zero padding are included in the result. - - R::type == the same type that was in m1 and m2. - - if (m1 has larger dimensions than m2) then - - R.nr() == m1.nr()-m2.nr()+1 - - R.nc() == m1.nc()-m2.nc()+1 - - else - - R.nr() == 0 - - R.nc() == 0 - !*/ - -// ---------------------------------------------------------------------------------------- - - const matrix_exp xcorr_valid ( - const matrix_exp& m1, - const matrix_exp& m2 - ); - /*! - requires - - m1 and m2 both contain elements of the same type - ensures - - returns a matrix R such that: - - R is the cross-correlation of m1 with m2. In particular, this - function returns conv_valid(m1,flip(m2)) if the matrices contain real - elements and conv_valid(m1,flip(conj(m2))) if they are complex. - - R::type == the same type that was in m1 and m2. - - if (m1 has larger dimensions than m2) then - - R.nr() == m1.nr()-m2.nr()+1 - - R.nc() == m1.nc()-m2.nc()+1 - - else - - R.nr() == 0 - - R.nc() == 0 - !*/ - -// ---------------------------------------------------------------------------------------- - -} - -#endif // DLIB_MATRIx_CONV_ABSTRACT_Hh_ - - |