A NOVEL GIVENS ROTATION BASED FAST SQR - RLSALGORITHMAlberto
نویسنده
چکیده
A novel Fast RLS Algorithm based on the Givens Rotation and developed from an UDU T square-root fac-torization of autocorrelation matrix is discussed. The algorithm presents excellent numerical properties and requires 14N multiplications and 6N divisions per sampling interval, where N is the linear lter order.
منابع مشابه
Givens and Householder Reductions for Linear Least Squares on aCluster of Workstations
We report on the properties of implementations of fast-Givens rotation and Householder reeector based parallel algorithms for the solution of linear least squares problems on a cluster of workstations. Givens rotations enable communication hiding and take greater advantage of parallelism than House-holder reeectors, provided the matrices are suuciently large.
متن کاملEecient Implementations of Pipelined Cordic Based Iir Digital Filters Using Fast Orthonormal -rotations
CORDIC based IIR digital lters possess desirable properties for VLSI implementations such as regularity, local connection, low sensitivity to nite word-length implementation, and elimination of limit cycles. Recently, ne-grain pipelined CORDIC based IIR digital lter architectures which can perform the ltering operations at arbitrarily high sample rates at the cost of linear increase in hardware...
متن کاملEfficient implementations of pipelined CORDIC based IIR digital filters using fast orthonormal μ-rotations
CORDIC based IIR digital lters are orthogonal lters whose internal computations consist of orthogonal transformations. These lters possess desirable properties for VLSI implementations such as regularity, local connection, low sensitivity to nite word-length implementation, and elimination of limit cycles. Recently, ne-grain pipelined CORDIC based IIR digital lter architectures which can perfor...
متن کاملCoordinate-descent for learning orthogonal matrices through Givens rotations
Optimizing over the set of orthogonal matrices is a central component in problems like sparsePCA or tensor decomposition. Unfortunately, such optimization is hard since simple operations on orthogonal matrices easily break orthogonality, and correcting orthogonality usually costs a large amount of computation. Here we propose a framework for optimizing orthogonal matrices, that is the parallel ...
متن کاملA minimal, rotation-based FRLS lattice algorithm
We propose an alternate Givens rotation-based least-squares lattice algorithm. Based on spherical trigonometry principles, this algorithm turns out to be a normalized version of the fast QRD-based least-squares lattice filter, introduced independently by Ling and by Proudler et al. In constrast with that algorithm, the storage requirements of the new algorithm are minimal (in the system theory ...
متن کامل