Generalized matrix inverse approach for automatic balancing of chemical equations

1978 ◽  
Vol 9 (3) ◽  
pp. 323-328 ◽  
Author(s):  
E.V. Krishnamurthy
Keyword(s):  
Matrix Inverse ◽  
Inverse Approach ◽  
Chemical Equations ◽  
Generalized Matrix ◽  
Automatic Balancing ◽  
Generalized Matrix Inverse

scholarly journals Weighted Moore–Penrose generalized matrix inverse: MySQL vs. Cassandra database storage system

Sadhana ◽  
2016 ◽  
Vol 41 (8) ◽  
pp. 837-846
Author(s):  
Danijela Milošević ◽  
Selver Pepić ◽  
Muzafer Saračević ◽  
Milan Tasić
Keyword(s):  
Storage System ◽  
Matrix Inverse ◽  
Generalized Matrix ◽  
Generalized Matrix Inverse ◽  
Database Storage

scholarly journals Computing Generalized Matrix Inverse on Spiking Neural Substrate

2018 ◽  
Vol 12 ◽  
Author(s):  
Rohit Shukla ◽  
Soroosh Khoram ◽  
Erik Jorgensen ◽  
Jing Li ◽  
Mikko Lipasti ◽  
...  
Keyword(s):  
Matrix Inverse ◽  
Neural Substrate ◽  
Generalized Matrix ◽  
Generalized Matrix Inverse

Remark to an unambiguity of estimators in the universal linear statistical models with the type ii constraints

2010 ◽  
Vol 60 (3) ◽  
Author(s):  
Lubomír Kubáček
Keyword(s):  
Mean Value ◽  
Linear Functions ◽  
Type Ii ◽  
Matrix Inverse ◽  
Estimable Functions ◽  
Linear Estimators ◽  
Generalized Matrix ◽  
Type Ii Constraints ◽  
Linear Statistical Models ◽  
Generalized Matrix Inverse

AbstractIn the universal linear statistical model with the type II constraints, estimates of the unbiasedly estimable linear functions of the parameters of the mean value vector are given by special types of generalized matrix inverse. Since there exists many versions of such matrix inverse it is of some interest to check the unambiguity of obtained estimators. The aim of the paper is to find the best unbiased linear estimators of unbiasedly estimable functions and to show that they do not depend on the choice of the used generalized inverse of the matrices.

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