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Conjugate gradient techniques for adaptive filtering

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2 Author(s)
G. K. Boray ; Bell Northern Res., Richardson, TX, USA ; M. D. Srinath

The application of the conjugate gradient technique for the solution of the adaptive filtering problem is discussed. An algorithm that does not require a line search or a knowledge of the Hessian is developed based on the conjugate gradient method. The choice of the gradient average window in the algorithm is shown to provide a trade-off between computational complexity and convergence performance. The method is capable of providing convergence comparable to recursive least squares (RLS) schemes at a computational complexity that is intermediate between the least mean square (LMS) and the RLS methods and does not suffer from any known instability problems

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IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications  (Volume:39 ,  Issue: 1 )