Adaptive line enhancers on the basis of least-squares algorithm for a single sinusoid detection

This paper proposes adaptive line enhancers with new coefficient update alg orithms on the basis of least-square-error criteria. Adaptive algorithms by least-squares are known to converge faster than stochastic-gradient ones. However they have high computational complexity due to matrix inversion. To avoid matrix inversion the proposed algorithms adapt only one coefficient to detect one sinusoid. Both FIR and IIR types of adaptive algorithm are pr esented, and the techniques to reduce the influence of additive noise is de scribed in this paper. The proposed adaptive line enhancers have simple str uctures and show excellent convergence characteristics. While the convergen ce of gradient-based algorithms largely depend on their stepsize parameters , the proposed ones are free from them.