电子产品世界 » 论坛首页 » 嵌入式开发 » FPGA » 【应用手册】QR Matrix Decomposition

共1条 1/1 1 跳转至

【应用手册】QR Matrix Decomposition

2012-05-14 10:49:28    评分
【应用手册】QR Matrix Decomposition
QR matrix decomposition (QRD), sometimes referred to as orthogonal
matrix triangularization, is the decomposition of a matrix (A) into an
orthogonal matrix (Q) and an upper triangular matrix (R). QRD is useful
for solving least squares’ problems and simultaneous equations.
In wireless applications, there are prevalent cases where QRD is useful.
Multiple-input multiple-output (MIMO) orthogonal frequency-division
multiplexing (OFDM) systems often require small multiple matrix (for
example, 4 × 4) inversions. These systems typically use a non-recursive
technique, such as QRD. Digital predistortion (DPD) and joint detection
applications often require large single matrix (for example, 20 × 20)
inversions. DPD often also requires a recursive technique, such as the
QRD recursive least squares (QRD-RLS) algorithm, because the equations
are overspecified—matrix A has more rows than there are unknowns (N)
to calculate.an506.pdf

关键词: 应用     手册     Matrix     Decompositio    

共1条 1/1 1 跳转至


匿名不能发帖!请先 [ 登陆 注册 ]