Numerical properties of the linearly constrained QRD-RLS adaptive filter
نویسندگان
چکیده
Shepherd and McWhirter proposed a QRD-RLS algorithm for adaptive filtering with linear constraints. In this paper, the numerical properties of this algorithm are considered. In particular, it is shown that the computed weight vector satisfies a set of constraints which are perturbed from the original ones, the amount of perturbation being dependent on the wordlength. The linearly constrained FLS algorithm of Resende ef al is also studied. Simulation results show that this algorithm is numerically unstable, even in the absence of explosive divergence.
منابع مشابه
An inverse QRD-RLS algorithm for linearly constrained minimum variance adaptive filtering
In this paper an inverse QR decomposition based recursive least-squares algorithm for linearly constrained minimum variance filtering is proposed. The proposed algorithm is numerically stable in finite precision environments and is suitable for implementation in systolic arrays or DSP vector architectures. Its performance is illustrated by simulations of a blind receiver for a multicarrier CDMA...
متن کاملNovel Method of Realization of Scalable VLSI Adaptive Digital Beamforming Architecture for Phased Array Radar
This This paper describes a novel method for the hardware Design and realization of adaptive filter for the application of Adaptive Digital beam former suitable for FPGAs. The planar phased array configuration considered in this case is sixteen element array. Design approach followed is modular design and each one of the modules is reused to make the sixteen element planar array configuration. ...
متن کاملA Family of Recursive Least-squares Adaptive Algorithms Suitable for Fixed-point Implementation
The main feature of the least-squares adaptive algorithms is their high convergence rate. Unfortunately, they encounter numerical problems in finite precision implementation and especially in fixed-point arithmetic. The objective of this paper is twofold. First, an analysis of the finite precision effects of the recursive least-squares (RLS) algorithm is performed, outlining some specific probl...
متن کاملA class of square root and division free algorithms and architectures for QRD-based adaptive signal processing
The least squares (LS) minimization problem constitutes the core of many real-time signal processing problems, such as adaptive filtering, system identification and adaptive beamforming. Recently efficient implementations of the recursive least squares (IUS) algorithm and the constrained recursive least squares (CRLS) algorithm based on the numerically stable QR decomposition (QRD) have been of...
متن کاملA Multi-layer 2-D Adaptive Filtering Architecture Based on McClellan Transformation
A fully pipelined systolic array structure for multidimensional adaptive filtering is proposed. I t utilizes the wellknown McClellan Transformation (MT) to reduce the total number of parameters used in the 2-D filter. A new multilayer triangular array, which is based on QR-decomposition RLS (QRD-RLS) as well as the projection method, is d e rived for the “1-D prototype filter’’ of MT. The hardw...
متن کامل