On the derivation of parallel filter structures for adaptive eigenvalue and singular value decompositions
نویسندگان
چکیده
A graphical derivation is presented for a recently developed parallel lter structure (systolic array) for updating eigen-value and singular value decompositions. The derivation of this array is non-trivial due to the presence of feedback loops and data contra-ow in the underlying signal ow graph (SFG). This would normally prohibit pipelined processing. However, it is shown that suitable delays may be introduced to the SFG by performing simple algorith-mic transformations which compensate for the interference of crossing data ows and eliminate the critical feedback loops. The pipelined array is then obtained either by 2-slowing and retiming the SFG or by means of dependence graph scheduling and assignment, and turns out to be an improved version of the arrray presented in 6].
منابع مشابه
Adaptive Line Enhancement Using a Parallel IIR Filter with A Step-By-step Algorithm
A step-by-step algorithm for enhancement of periodic signals that are highly corrupted by additive uncorrelated white gausian noise is proposed. In each adaptation step a new parallel second-order section is added to the previous filters. Every section has only one adjustable parameter, i.e., the center frequency of the self-tuning filter. The bandwidth and the convergence factor of each secti...
متن کاملSubspace-Based Noise Reduction for Speech Signals via Diagonal and Triangular Matrix Decompositions∗
We survey the definitions and use of rank-revealing matrix decompositions in single-channel noise reduction algorithms for speech signals. Our algorithms are based on the rank-reduction paradigm and, in particular, signal subspace techniques. The focus is on practical working algorithms, using both diagonal (eigenvalue and singular value) decompositions and rankrevealing triangular decompositio...
متن کاملUsing Zolotarev’s Rational Approximation for Computing the Polar, Symmetric Eigenvalue, and Singular Value Decompositions
The polar decomposition A = UpH finds many uses in applications, and it is a fundamental tool for computing the symmetric eigenvalue decomposition and the singular value decomposition via a spectral divide-and-conquer process. Conventional algorithms for these decompositions are suboptimal in view of recent trends in computer architectures, which require minimizing communication together with a...
متن کاملAn Adaptive Subspace Filter for Noise Reduction
In this paper, we present a novel structure for adap-tive noise ltering based on subspace methods. Our approach requires no eigenvalue or singular value decomposition to obtain the principal signal components. In addition, only the noisy signal, and no reference signal is needed. A modiied RLS adaptive algorithm is proposed which approximately performs the principal component analysis of the no...
متن کاملOrthogonal Matrix Decompositions in Systemsand
In this paper we present several types of orthogonal matrix decompositions used in systems and control. We focus on those related to eigenvalue and singular value problems and include generalizations to several matrices.
متن کامل