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Algorithms and systolic architectures for multidimensional adaptive filtering via McClellan transformations

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2 Author(s)
Shapiro, J.M. ; MIT Lincoln Lab., Lexington, MA, USA ; Staelin, D.H.

Algorithms are developed simultaneously with systolic architectures for multidimensional adaptive filtering Because of the extremely high data rate required for real-time video processing, there is a strong motivation to limit the size of any adaptation problem. Combining the McClellan transformations with systolic arrays to adapt and implement the least-squares filter yields a novel solution to the problem of adapting a large zero-phase finite impulse response (FIR) multidimensional filter, having arbitrary directional biases, with only a few parameters. These filters can be adapted abruptly on a block-by-block basis without causing blocking effects. After developing a basic processing element for a systolic array realization of the Chebyshev structure for the McClellan transformation, it is shown that for a given 2-D transformation function, the adaptation of the 1-D prototype filter becomes a small multichannel adaptation problem similar to adaptive array problems. A similar approach is also taken in developing algorithms to adapt the 2-D transformation function

Published in:

Circuits and Systems for Video Technology, IEEE Transactions on  (Volume:2 ,  Issue: 1 )

Date of Publication:

Mar 1992

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