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The Formal Derivation of a Systolic Array for Recursive Least Squares Estimation (0)
| Content Provider | CiteSeerX |
|---|---|
| Author | Proudler, Ian K. Mcwhirter, John G. Moonen, Marc Hekstra, Gerben |
| Description | A formal proof is presented for a recently presented systolic array for recursive least squares estimation by inverse updates. The derivation of this systolic array is highly non-trivial due to the presence of data contra-flow and feedback loops in the underlying signal flow graph. This would normally prohibit pipelined processing. However, it is shown that suitable delays may be introduced into the signal flow graph by performing a simple algorithmic transformation which compensates for the interference of crossing data flows. The pipelined systolic array is then obtained by retiming the signal flow graph and applying the cut theorem. I. Introduction In this paper we derive a novel systolic array for implementing recursive least squares (RLS) computations based on the method of inverse updates. Recursive least squares estimation is required in a wide range of applications from adaptive beamforming for antenna arrays to data communications, space navigation and system identification. ... IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications |
| File Format | |
| Language | English |
| Access Restriction | Open |
| Subject Keyword | Feedback Loop Underlying Signal Flow Graph Antenna Array Pipelined Systolic Array Cut Theorem Signal Flow Graph Simple Algorithmic Transformation Novel Systolic Array Data Flow Data Communication Recursive Least Square Estimation Suitable Delay Inverse Update Formal Derivation Space Navigation Formal Proof Wide Range Data Contra-flow Systolic Array System Identification Square Estimation Adaptive Beamforming Pipelined Processing |
| Content Type | Text |
| Resource Type | Article |
