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April 2019 – Seyyed Ali Pourmousavi Kani
Seyyed Ali Pourmousavi Kani
Seyyed Ali Pourmousavi Kani
Ph.D. Electrical Engineering | Member, IEEE (S'07, M'15) | Secretary, IEEE Joint Chapter of PE/IE/IA Societies | MIEAust, The Institution of Engineers Australia | Electric Energy Society of Australia (EESA), Engineers Australia (EA)
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April 2019

There were 3 posts published in April 2019 (this is page 1 of 1).

MATLAB Vectorization Demystified – Part 3: Preallocation

“MATLAB Vectorization Demystified”: In this series, I try to explain vectorization operation in MATLAB in details step-by-step through several examples. This is part 3 in which “preallocation” of variables/parameters are explained. Preallocation You probably have seen this MATLAB warning when coding for or while loops: This is the fact that for and while loops that […]

in Learning, MATLAB | April 29, 2019 | Comment

MATLAB Vectorization Demystified – Part 2: Matrices and Indexing

“MATLAB Vectorization Demystified”: In this series, I try to explain vectorization operation in MATLAB in details step-by-step through several examples. This is part 2 in which “Matrices and Indexing” are explained. Matrix definition Every variable in MATLAB is an array that can hold many numbers, characters, strings, date and times, and so on. Arrays in […]

in Learning, MATLAB | April 15, 2019 | Comment

MATLAB Vectorization Demystified – Part 1: Vectors and Indexing

“MATLAB Vectorization Demystified”: In this series, I try to explain vectorization operation in MATLAB in details step-by-step through several examples. This is part 1 in which “Vectors and Indexing” are explained. Vector Definition in MATLAB In MATLAB, a vector is a matrix with either one row or one column. sampleVector1 =       1    2 […]

in Learning, MATLAB | April 11, 2019 | Comment

Recent Posts

  • MATLAB Vectorization Demystified – Part 3: Preallocation
  • MATLAB Vectorization Demystified – Part 2: Matrices and Indexing
  • MATLAB Vectorization Demystified – Part 1: Vectors and Indexing
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  • PAPER: Improving predictability of renewable generation through optimal battery sizing

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