MSGR-based Low Latency Complex Matrix Inversion Architecture

This paper presents a matrix inversion architecture based on the novel Modified Squared Givens Rotations (MSGR) algorithm, which extends the original SGR method to complex valued data, and also corrects erroneous results in the original SGR method when zeros occur on the diagonal of the matrix either initially or during processing. The MSGR algorithm also avoids complex dividers in the matrix inversion, thus minimising the complexity of potential real-time implementations. A systolic array architecture is implemented and FPGA synthesis results indicate a high-throughput low-latency complex matrix inversion solution. © 2008 IEEE.

QR decomposition-based matrix inversion for high performance embedded MIMO receivers

Real-time matrix inversion is a key enabling technology in multiple-input multiple-output (MIMO) communications systems, such as 802.11n. To date, however, no matrix inversion implementation has been devised which supports real-time operation for these standards. In this paper, we overcome this barrier by presenting a novel matrix inversion algorithm which is ideally suited to high performance floating-point implementation. We show how the resulting architecture offers fundamentally higher performance than currently published matrix inversion approaches and we use it to create the first reported architecture capable of supporting real-time 802.11n operation. Specifically, we present a matrix inversion approach based on modified squared Givens rotations (MSGR). This is a new QR decomposition algorithm which overcomes critical limitations in other QR algorithms that prohibits their application to MIMO systems. In addition, we present a novel modification that further reduces the complexity of MSGR by almost 20%. This enables real-time implementation with negligible reduction in the accuracy of the inversion operation, or the BER of a MIMO receiver based on this.

Cholinesterase Inhibitor and Memantine Use in Newly Admitted Nursing Home Residents with Dementia

OBJECTIVES: To quantify the use of cholinesterase inhibitors (ChEIs) and memantine in nursing home (NH) residents with dementia upon NH admission and 3 months later and to examine factors associated with reduction in therapy.

DESIGN: Retrospective cohort study.

SETTING: Nationwide sample of U.S. NHs.

PARTICIPANTS: Three thousand ?ve hundred six NH residents with dementia newly admitted in 2006.

MEASUREMENTS: Data from pharmacy dispensing records were used to determine ChEI and memantine medication use upon NH admission and at 3-month follow-up. The Minimum Data Set was used to determine resident- and facility-level characteristics. Severity of dementia was de?ned using the Cognitive Performance Scale (CPS).

RESULTS: Overall, 40.1% (n51,407) of newly admitted NH residents with dementia received ChEIs and memantine on NH admission. Use of ChEIs and memantine on admission was significantly greater in residents with mild to moderately severe dementia (41.2%) than in those with advanced dementia (33.3%, P5.001). After 3 months, ChEI and memantine use decreased by about half in both groups (48.6% with mild to moderately severe dementia vs 57.0% with advanced dementia, Po.05). NH residents with advanced dementia were significantly more likely reduce their use of ChEIs and memantine than those with mild to moderately severe dementia (odds ratio 51.44, 95% con?dence interval 51.03–2.01, P5.04).

CONCLUSION: Many NH residents with advanced dementia receive ChEIs and memantine upon NH admission, and approximately half of these decrease their medication use over the ensuing months. Further study is required to optimize use of ChEIs and memantine in NH populations and to determine the effects of withdrawing therapy on resident outcomes.