Abstract :
Analog adaptive filters are an important subset of adaptive-filter theory and practice. They are preferable at high speeds when low power consumption, small integrated area, and moderate linearity are required. In this paper, an analog adaptive-disturbance canceller is presented. The canceller uses the analog least mean square (LMS) algorithm, and its structure is similar to a linear combiner. The operation of the proposed canceller is based on the decomposition of the disturbances into the in-phase and quadrature components by means of a Hilbert transformer, which is used as an analog LMS for the cancellation of each component. Finally, some experimental results, which are obtained from a low-cost discrete-component realization of the proposed canceller, are presented. The proposed structure is also suitable for very large-scale integration designs.
Keywords :
Hilbert transforms; adaptive filters; filtering theory; least mean squares methods; Hilbert transformer; LMS algorithm; analog adaptive filters; analog least mean square algorithm; discrete-component realization; fully analog adaptive-disturbance canceller; large-scale integration designs; Adaptive filters; Biomedical measurements; Convergence; Energy consumption; Filtering; Large scale integration; Least squares approximation; Linearity; Noise cancellation; Nonlinear filters; Adaptive filters; adaptive linear combiner; analog circuits; analog multipliers; disturbance rejection; interference suppression; least mean square (LMS); noise;
