Adaptive mean estimation and normalization of data

作者: Steven T. Smith , Thomas J. Green , Eric J. Van Allen , Sanford L. Wilson , William H. Payne

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摘要: A method of determining a mean for data set element values. form probability density function statistical distribution is selected each the set, based on value that element. Then estimated, by, e.g., digital or analog processing technique. The estimated element's then designated as In normalizing values means 10 in processed to normalize value, producing normalized set.

参考文章(4)
Albert M. Bisbee, Stephen K. Johnson, James F. Montgomery, Susan B. Mount, Gerard L. Rafanelli, Philip J. Sementilli, Bobby R. Hunt, Super-resolved full aperture scene synthesis using rotating strip aperture image measurements ,(1996)
Stanley D. Luck, Normalization and error estimation for biomedical expression patterns Microarrays : optical technologies and informatics. Conference. ,vol. 4266, pp. 153- 157 ,(2001) , 10.1117/12.427984
Alexander J. Hartemink, David K. Gifford, Tommi S. Jaakkola, Richard A. Young, Maximum likelihood estimation of optimal scaling factors for expression array normalization Microarrays : optical technologies and informatics. Conference. ,vol. 4266, pp. 132- 140 ,(2001) , 10.1117/12.427981
Jan P. Allebach, Bernd W. Kolpatzik, Charles A. Bouman, Thyagarajan Blasubramanian, Sequential scalar quantization of digital color image using mean squared error-minimizing quantizer density function ,(1993)