A least squares algorithm for fitting additive trees to proximity data

Geert De Soete

doi:10.1007/bf02293884

A least squares algorithm for fitting additive trees to proximity data

Psychometrika ◽

10.1007/bf02293884 ◽

1983 ◽

Vol 48 (4) ◽

pp. 621-626 ◽

Cited By ~ 287

Author(s):

Geert De Soete

Keyword(s):

Least Squares ◽

Proximity Data ◽

Additive Trees ◽

Least Squares Algorithm

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Computer programs for fitting ultrametric and additive trees to proximity data by least squares methods

Behavior Research Methods Instruments &amp Computers ◽

10.3758/bf03200842 ◽

1984 ◽

Vol 16 (6) ◽

pp. 551-552 ◽

Cited By ~ 3

Author(s):

Geert De Soete

Keyword(s):

Least Squares ◽

Computer Programs ◽

Proximity Data ◽

Additive Trees

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Analysis of a Linearly Constrained Least Squares Algorithm for Adaptive Beamforming

10.21236/ada255017 ◽

1992 ◽

Author(s):

Franklin T. Luk ◽

Sanzheng Qiao

Keyword(s):

Least Squares ◽

Adaptive Beamforming ◽

Constrained Least Squares ◽

Linearly Constrained ◽

Least Squares Algorithm

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Prediction of human triglyceride concentration based on quantum genetic-partial least squares algorithm and fluorescence spectroscopy

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy ◽

10.1016/j.saa.2021.119461 ◽

2021 ◽

Vol 251 ◽

pp. 119461

Author(s):

De-kang Le ◽

Wei-hua Zhu ◽

Feng Zhu ◽

Hong-bing Yao ◽

Ying Geng ◽

...

Keyword(s):

Fluorescence Spectroscopy ◽

Least Squares ◽

Partial Least Squares ◽

Triglyceride Concentration ◽

Least Squares Algorithm

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Kernel Recursive Least Squares Algorithm for Transmitter-Induced Self-Interference Cancellation

2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring) ◽

10.1109/vtc2021-spring51267.2021.9449025 ◽

2021 ◽

Author(s):

C. Auer ◽

T. Paireder ◽

M. Huemer

Keyword(s):

Least Squares ◽

Interference Cancellation ◽

Recursive Least Squares ◽

Recursive Least Squares Algorithm ◽

Least Squares Algorithm

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A Novel Resonant Frequency Estimation Method Based on Recursive Least Squares Algorithm for Linear Compressor

2020 IEEE 9th International Power Electronics and Motion Control Conference (IPEMC2020-ECCE Asia) ◽

10.1109/ipemc-ecceasia48364.2020.9367828 ◽

2020 ◽

Author(s):

Qizhe Wang ◽

Wei Xu ◽

Xiang Li ◽

Yi Liu

Keyword(s):

Resonant Frequency ◽

Least Squares ◽

Frequency Estimation ◽

Estimation Method ◽

Recursive Least Squares ◽

Linear Compressor ◽

Recursive Least Squares Algorithm ◽

Least Squares Algorithm

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Deep kernel recursive least-squares algorithm

Nonlinear Dynamics ◽

10.1007/s11071-021-06416-0 ◽

2021 ◽

Author(s):

Hossein Mohamadipanah ◽

Mahdi Heydari ◽

Girish Chowdhary

Keyword(s):

Least Squares ◽

Recursive Least Squares ◽

Recursive Least Squares Algorithm ◽

Least Squares Algorithm

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Application of the two dimensional frequency domain least squares algorithm to airborne surveillance radar detection

Conference Record of Thirty-Fifth Asilomar Conference on Signals, Systems and Computers (Cat.No.01CH37256) ◽

10.1109/acssc.2001.986878 ◽

2001 ◽

Author(s):

Qingwen Zhang ◽

W.B. Mikhael

Keyword(s):

Least Squares ◽

Frequency Domain ◽

Two Dimensional ◽

Radar Detection ◽

Least Squares Algorithm

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A novel extended kernel recursive least squares algorithm

Neural Networks ◽

10.1016/j.neunet.2011.12.006 ◽

2012 ◽

Vol 32 ◽

pp. 349-357 ◽

Cited By ~ 18

Author(s):

Pingping Zhu ◽

Badong Chen ◽

José C. Príncipe

Keyword(s):

Least Squares ◽

Recursive Least Squares ◽

Recursive Least Squares Algorithm ◽

Least Squares Algorithm

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An alternating least-squares algorithm for approximate joint diagonalization and its application to blind source separation

2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) ◽

10.1109/icassp.2014.6853970 ◽

2014 ◽

Cited By ~ 1

Author(s):

Shinya Saito ◽

Kunio Oishi ◽

Toshihiro Furukawa

Keyword(s):

Least Squares ◽

Blind Source Separation ◽

Source Separation ◽

Alternating Least Squares ◽

Joint Diagonalization ◽

Alternating Least Squares Algorithm ◽

Least Squares Algorithm

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Effects of signal to noise and parametric limitations on fitting biexponential magnetic resonance (MR) inversion-recovery curves using a constrained nonlinear least-squares algorithm

Proceedings of the IEEE 24th Annual Northeast Bioengineering Conference (Cat. No.98CH36210) ◽

10.1109/nebc.1998.664869 ◽

2002 ◽

Author(s):

M.D. Silva ◽

S.S. Han ◽

C.H. Sotak

Keyword(s):

Magnetic Resonance ◽

Least Squares ◽

Nonlinear Least Squares ◽

Inversion Recovery ◽

Signal To Noise ◽

Recovery Curves ◽

Least Squares Algorithm

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