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Estimation of Multiple Sinusoidal Frequencies Using Truncated Least-Squares Methods
(1991)
Tufts and Kumaresan (1982) first proposed using a SVD-based method to solve the forward-backward linear prediction (FBLP) least-squares problem for resolving closely spaced frequencies of multiple sinusoids from limited ...
Dual-State Systolic Architectures for Adaptive Filtering Using Up/Downdating RLS
(1991)
We propose a dual-state systolic structure to perform joint up/down-dating operations encountered in windowed recursive least squares (RLS) estimation problems. It is derived by successively performing Givens rotations for ...
Multi-phase Systolic Algorithms for Spectral Decomposition
(1991)
In this paper, we propose two multi-phase systolic algorithms to solve the spectral decomposition problem based on the QR algorithm. The spectral decomposition is one of the most computationally intensive modern signal ...
Systolic Implementations of Up/Down-dating Cholesky Factorization Using Vectorized Gram-Schmidt Pseudo Orthogonalization
(1991)
We propose a new class of hyperbolic Gram-Schmidt methods to simultaneously update and downdate the Cholesky factor of a sample covariance matrix efficiently with applications to sliding window recursive least squares (RLS) ...
Real-Time Algorithm-Based Fault-Tolerance for QRD Recursive Least-Squares Systolic Array: A Graceful Degradation Approach
(1991)
In this paper, we propose a new algorithm-based fault-tolerant method derived from the inherent nature of the QR lease-squares systolic algorithm. Since the residuals of different desired responses can be computed ...
VLSI Algorithms and Architectures for Complex Householder Transformation with Applications to Array Processing
(1991)
The Householder transformation is considered to be desirable among various unitary transformations due to its superior computational efficiency and robust numerical stability. Specifically, the Householder transformation ...
A Unified Approach for QRD-Based Recursive Least-Squres Estimation without Square Roots
(1991)
The QR-decomposition (QRD)-based recursive least-squares (RLS) methods have been shown to be useful and effective towards adaptive signal processing in modern communications, radar, and sonar systems implementable with ...