Algorithms and systolic architectures for multidimensional adaptive filtering via McClellan transformations

The concurrent development of algorithms and systolic architectures for adaptive filtering purposes is presented. It details how the McClellan transformation is used for parametrization of a least squares filter and presented as a solution to the problem of adapting a large zero-phase finite impulse response multidimensional filter with limited parameters and arbitary directional biases.