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Double-pipelined architecture of a real-time recurrent noise filtering

DOI 10.18127/j20700784-201812-23

Keywords:

A.V. Sokolovskiy – Research Scientist, Siberian Federal University (Krasnoyarsk)
E-mail: sokolovskii_a@mail.ru
I.V. Tyapkin – Teacher of Faculty, Siberian Federal University (Krasnoyarsk)
E-mail: Aronakss@yandex.ru
E.A. Veisov – Professor, Siberian Federal University (Krasnoyarsk)
E-mail: eveisov@sfu-kras.ru


In this paper, a real-time noise filtering architecture is investigated. Several aspects of the noise filtering algorithm implemented in the hardware has described. Compared to a standard compute architecture of a recurrent solving algorithm the proposed architecture have performance and computation speed-up advantages. Based idea of the novel architecture is an augmentation of a general compute architecture by the simple function calculus for prediction. This prediction functions does extrapolation in a linear region of the filter coefficients convergence graph. The prediction functions is a simpler in a computation sense than a filter coefficients computa-tion block. Therefore, while computation block is busy by a computing at non-linear region a prediction block does a several compute iterations to the new non-linear region of the filter coefficients convergence graph. To get a uniform behavior of a filter coefficients calculation the second background compute pipeline is added. When a first compute pipeline result will ready the second compute pipeline is started to compute filter coefficients with new parameters. The simulation of a double-pipelined architecture has a signifi-cant advantages in a speed of a convergence to the optimal filter coefficients values.

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