Parallel-form adaptive state-space filtering and its implementation

Abstract

Introduces an adaptive recursive state-space algorithm and its implementation. The adaptive state-space filtering is realized by using the least mean square adaptation algorithm and the gradients for filter parameters are derived directly from the state equations. To reduce the computational complexity, a parallel form of second-order sections is used. The performance of adaptive state-space filters, in terms of stability monitoring, roundoff noise and convergence rate, is given. A possible roundoff noise performance improvement by using adaptive state-space filtering is shown using simulation examples. The stability monitoring is simple since each section is a second-order filter. VLSI array processors are suggested for real-time applications.<>