В роботі

FInd smallest eigenvalue of generalized equation in Java

Looking for a function to be written in Java that does not require other libraries to find the smallest eigenvalue that solves this matrix equation Ax = Lambda Mx. X is a eigenvector and Lambda is an eigenvalue. Matrix A is real, symmetric and square. Matrix M is symmetric but can have zeros or negative values on the diagonal. This prevents many standard means of solving equation because M is ill-conditioned.

The best solutions I have found, and are implemented in some commercial softwares, is the Lanczos method and also the Subspace iteration method. There is C and Fortran code online that is implemented in highly respected libraries such as LAPACK.

I don't need all the eigenvalues, nor do I need any eigenvectors. The smallest eigenvalue is required. The Subspace method is claimed to be the best and fastest for this type of work. Once you think you have it completed and tested it, I will provide a few examples to verify.

Навички: Java, Engineering Mathematics

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Про роботодавця:
( 0 відгуки(-ів) ) MIDDLE SACKVILLE, Canada

ID Проекту: #21674725

Доручено:

khoddam

Hello, I have taught numerical analysis, familiar with LAPACK, C, and Fortran. Also I know the basics of different method for eigen value problems. What is the maximum size of your matrices? (order of 10, 100 , or 100 Більше

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11 фрілансерів(-и) у середньому готові виконати цю роботу за $459

progcgstar

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paulprabhakarand

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vedant2910

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ZhangHuaQiang

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ayeilyurt

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2.1
ammaraunitech

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