Difference between revisions of "Winograd small convolution algorithm"
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− | A general strategy for computing linear and cyclic convolutions by applying the polynomial version of the [[ | + | A general strategy for computing linear and cyclic convolutions by applying the polynomial version of the [[Chinese remainder theorem]] [[#References|[a1]]]. For polynomials $ g ( x ) $ |
and $ h ( x ) $ | and $ h ( x ) $ | ||
of degree $ N - 1 $ | of degree $ N - 1 $ | ||
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====References==== | ====References==== | ||
− | <table><TR><TD valign="top">[a1]</TD> <TD valign="top"> A. Borodin, I. Munro, "Computational complexity and algebraic and numeric problems" , Amer. Elsevier (1975)</TD></TR><TR><TD valign="top">[a2]</TD> <TD valign="top"> S. Winograd, "Some bilinear forms whose multiplicative complexity depends on the field of constants" ''Math. Systems Th.'' , '''10''' (1977) pp. 169–180</TD></TR><TR><TD valign="top">[a3]</TD> <TD valign="top"> R.C. Agarwal, J.W. Cooley, "New algorithms for digital convolution" ''IEEE Trans. Acoustics, Speech and Signal Processing'' , '''25''' (1977) pp. 392–410</TD></TR></table> | + | <table> |
+ | <TR><TD valign="top">[a1]</TD> <TD valign="top"> A. Borodin, I. Munro, "Computational complexity and algebraic and numeric problems" , Amer. Elsevier (1975)</TD></TR> | ||
+ | <TR><TD valign="top">[a2]</TD> <TD valign="top"> S. Winograd, "Some bilinear forms whose multiplicative complexity depends on the field of constants" ''Math. Systems Th.'' , '''10''' (1977) pp. 169–180</TD></TR> | ||
+ | <TR><TD valign="top">[a3]</TD> <TD valign="top"> R.C. Agarwal, J.W. Cooley, "New algorithms for digital convolution" ''IEEE Trans. Acoustics, Speech and Signal Processing'' , '''25''' (1977) pp. 392–410</TD></TR> | ||
+ | </table> |
Latest revision as of 06:01, 26 May 2024
A general strategy for computing linear and cyclic convolutions by applying the polynomial version of the Chinese remainder theorem [a1]. For polynomials $ g ( x ) $
and $ h ( x ) $
of degree $ N - 1 $
and $ M - 1 $,
respectively, the linear convolution
$$ s ( x ) = h ( x ) g ( x ) $$
has degree $ L - 1 $, where $ L = M + N - 1 $. For any polynomial $ m ( x ) $ of degree $ L $, the linear convolution $ s ( x ) $ can be computed by computing the product $ h ( x ) g ( x ) $ modulo $ m ( x ) $, i.e.,
$$ s ( x ) \equiv s ( x ) { \mathop{\rm mod} } m ( x ) . $$
The Chinese remainder theorem permits this computation to be localized. Choose a factorization
$$ m ( x ) = m _ {1} ( x ) \dots m _ {r} ( x ) $$
into relatively prime factors. The Winograd small convolution algorithm proceeds by first computing the reduced polynomials
$$ h ^ {( k ) } ( x ) \equiv h ( x ) { \mathop{\rm mod} } m _ {k} ( x ) , 1 \leq k \leq r, $$
$$ g ^ {( k ) } ( x ) \equiv g ( x ) { \mathop{\rm mod} } m _ {k} ( x ) , 1 \leq k \leq r, $$
followed by the local computations
$$ s ^ {( k ) } ( x ) \equiv h ^ {( k ) } g ^ {( k ) } ( x ) { \mathop{\rm mod} } m _ {k} ( x ) , 1 \leq k \leq r, $$
and is completed by combining these local computations using the formula
$$ s ( x ) = \sum _ {k = 1 } ^ { r } s ^ {( k ) } ( x ) e _ {k} ( x ) , $$
where
$$ \left \{ {e _ {k} ( x ) } : {1 \leq k \leq r } \right \} $$
is a complete system of idempotents corresponding to the initial factorization of $ m ( x ) $.
S. Winograd [a2] expanded on this general strategy by developing bilinear algorithms for computing the product of polynomials modulo a polynomial. Within this general strategy, these bilinear algorithms permit one to use small efficient algorithms as building blocks for larger-size algorithms [a3].
References
[a1] | A. Borodin, I. Munro, "Computational complexity and algebraic and numeric problems" , Amer. Elsevier (1975) |
[a2] | S. Winograd, "Some bilinear forms whose multiplicative complexity depends on the field of constants" Math. Systems Th. , 10 (1977) pp. 169–180 |
[a3] | R.C. Agarwal, J.W. Cooley, "New algorithms for digital convolution" IEEE Trans. Acoustics, Speech and Signal Processing , 25 (1977) pp. 392–410 |
Winograd small convolution algorithm. Encyclopedia of Mathematics. URL: http://encyclopediaofmath.org/index.php?title=Winograd_small_convolution_algorithm&oldid=49228