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Approximate Implementation of Arithmetic Operations in Image Filters
Válek, Matěj ; Vašíček, Zdeněk (oponent) ; Sekanina, Lukáš (vedoucí práce)
This Master's thesis deals with approximate implementations of arithmetic operations in image filters. In particular, it uses approximation techniques to adjust the multiplication operations in a non-trivial image filter. Several methods are employed, such as converting the floating-point multiplication to fixed-point multiplication, applying evolutionary algorithms, especially Cartesian genetic programming, to create new approximate multipliers that have an acceptable level of error, and at the same time, reduced filtering complexity. The result is a collection of approximate multipliers evolved with respect to the data distribution retrieved from the image filter. Approximate image filters that use evolved approximate multipliers are compared with the standard image filter on a set of images.
Approximate Implementation of Arithmetic Operations in Image Filters
Válek, Matěj ; Vašíček, Zdeněk (oponent) ; Sekanina, Lukáš (vedoucí práce)
This Master's thesis deals with approximate implementations of arithmetic operations in image filters. In particular, it uses approximation techniques to adjust the multiplication operations in a non-trivial image filter. Several methods are employed, such as converting the floating-point multiplication to fixed-point multiplication, applying evolutionary algorithms, especially Cartesian genetic programming, to create new approximate multipliers that have an acceptable level of error, and at the same time, reduced filtering complexity. The result is a collection of approximate multipliers evolved with respect to the data distribution retrieved from the image filter. Approximate image filters that use evolved approximate multipliers are compared with the standard image filter on a set of images.

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