发明名称 |
ESTIMATION OF WATER INTERFERENCE FOR SPECTRAL CORRECTION |
摘要 |
A method includes decomposing a training set to obtain a principal component matrix having a plurality of principal component vectors. The method also includes variably rejecting portions of a sample spectrum vector that do not correspond to a selected one of the plurality of principal component vectors by incrementally providing a coefficient indicative of the weighting of the selected principal component vector for selected sub-regions. A corrected spectrum vector can be obtained by excluding certain sub-regions of the sample spectrum vector and corresponding principal component vector, multiplying the sample spectrum vector with the principal component matrix for non-excluded sub-regions, providing a predicted interference vector, and subtracting the predicted interference vector from the sample spectrum vector. |
申请公布号 |
US2016033394(A1) |
申请公布日期 |
2016.02.04 |
申请号 |
US201414446473 |
申请日期 |
2014.07.30 |
申请人 |
Smiths Detection Inc. |
发明人 |
Judge Kevin;Andersson Greger;Zou Peng |
分类号 |
G01N21/27;G01N21/35 |
主分类号 |
G01N21/27 |
代理机构 |
|
代理人 |
|
主权项 |
1. A computer-implemented method comprising:
decomposing a training set to obtain a principal component matrix having a plurality of principal component vectors; variably rejecting portions of a sample spectrum vector that do not correspond to a selected one of the plurality of principal component vectors by incrementally:
selecting a sub-region of the sample spectrum vector and a corresponding sub-region of the selected principal component vector; andmultiplying the selected sub-region of the sample spectrum vector with the corresponding sub-region of the selected principal component vector to provide a coefficient indicative of the weighting of the selected principal component vector for the selected sub-regions; excluding sub-regions of the sample spectrum vector and corresponding principal component vector based on the incrementally provided coefficients; multiplying the sample spectrum vector with the principal component matrix for the non-excluded sub-regions to provide a weighting vector indicative of the contribution of the principal component matrix; multiplying the weighting vector by the principal component matrix to provide a predicted interference vector; and subtracting the predicted interference vector from the sample spectrum vector to provide a corrected spectrum vector. |
地址 |
Edgewood MD US |