Topic
QR decomposition
About: QR decomposition is a research topic. Over the lifetime, 3504 publications have been published within this topic receiving 100599 citations. The topic is also known as: QR factorization.
Papers published on a yearly basis
Papers
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01 Sep 1997TL;DR: A fast backward elimination algorithm is introduced based on a QR decomposition and Givens transformations to prune radial-basis-function networks and provides a hybrid supervised centre selection approach.
Abstract: A fast backward elimination algorithm is introduced based on a QR decomposition and Givens transformations to prune radial-basis-function networks. Nodes are sequentially removed using an increment of error variance criterion. The procedure is terminated by using a prediction risk criterion so as to obtain a model structure with good generalisation properties. The algorithm can be used to postprocess radial basis centres selected using a k-means routine and, in this mode, it provides a hybrid supervised centre selection approach.
35 citations
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TL;DR: The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm.
35 citations
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TL;DR: This paper shows why the modified Gram-Schmidt algorithm generates a well-conditioned set of vectors and shows that if two iterations of the algorithm are performed, the resulting algorithm produces a matrix whose columns are orthogonal up to machine precision.
Abstract: In this paper, we show why the modified Gram-Schmidt algorithm generates a well-conditioned set of vectors This result holds under the assumption that the initial matrix is not 'too ill-conditioned' in a way that is quantified As a consequence we show that if two iterations of the algorithm are performed, the resulting algorithm produces a matrix whose columns are orthogonal up to machine precision Finally, we illustrate through a numerical experiment the sharpness of our result
35 citations
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TL;DR: A high-speed space-division multiplexing (SDM) multiple-input-multiple output (MIMO) decoder using efficient candidate searching is proposed by exploiting the characteristics of QR decomposition and sphere decoder for high throughput rate and low hardware-complexity.
Abstract: In this brief, a high-speed space-division multiplexing (SDM) multiple-input-multiple output (MIMO) decoder using efficient candidate searching is proposed by exploiting the characteristics of QR decomposition and sphere decoder for high throughput rate and low hardware-complexity. A process of efficient candidate searching by shifting the center of constellation with scalable radius reduces the processing time and improves the operational frequency. The proposed architecture can operate at a 166-MHz clock frequency, and the core area is smaller than results from using the K-best SD algorithm since large memory is not required to store extreme candidate paths. In our implementation, the core area is 0.675 mm using TSMC 90-nm technology. The average throughput of the proposed SDM-MIMO decoder is 95 Mbps with 64-QAM modulation at 30-dB signal-to-noise ratio.
35 citations
01 Jan 2009
TL;DR: In this paper, the authors applied maximum likelihood detection employing QR decomposition and M-algorithm (QRM-MLD) to the SC signal detection with antenna diversity reception.
Abstract: The frequency-domain received single-carrier (SC) signal can be expressed using the matrix representation similar to the multiple-input multiple-output (MIMO) multiplexing. The signal detection schemes developed for MIMO multiplexing can be applied to the SC transmissions. In this paper, we apply maximum likelihood detection employing QR decomposition and M-algorithm (QRM-MLD) to the SC signal detection with antenna diversity reception. We show that by using antenna diversity reception, the number of surviving symbol candidates can be reduced. We evaluate, by the computer simulation, the bit error rate (BER) performance achievable by QRM-MLD and compare it with that achievable by the Vertical-Bell Laboratories Layered spacetime architecture (V-BLAST) detection.
35 citations