week03 - Rutgers University School of Engineering Spring...

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Rutgers University School of Engineering Spring 2012 14:440:127 - Introduction to Computers for Engineers Sophocles J. Orfanidis ECE Department orfanidi@ece.rutgers.edu week 3
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Week 1 - Basics – variables, arrays, matrices, plotting (ch. 2 & 3) Week 2 - Basics – operators, functions, program flow (ch. 2 & 3) Week 3 - Matrices (ch. 4) Week 4 - Plotting – 2D and 3D plots (ch. 5) Week 5 - User-defined functions (ch. 6) – Exam 1 Week 6 - Input-output formatting – fprintf, fscanf (ch. 7) Week 7 - Program flow control & relational operators (ch. 8 & 9) Week 8 - Program flow control & relational operators (ch. 8 & 9) Week 9 - Matrix algebra – solving linear equations (ch. 10) Week 10 - Cell arrays and structures (ch. 11) – Exam 2 Week 11 - Numerical methods – part I (ch. 13) Week 12 - Numerical methods – part II (ch. 13) Week 13 - Symbolic toolbox (ch. 12) Week 14 - Exam 3 Weekly Topics Textbook: H. Moore, MATLAB for Engineers , 3 d ed., Prentice Hall, 2011
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Matrix Manipulation defining matrices accessing matrix elements colon operator, submatrices transposing a matrix changing/adding/deleting entries concatenating matrices special matrices diagonals, block-diagonal matrices replicating and reshaping matrices element-wise operations functions of matrices (element & column operations) meshgrid, ndgrid examples: DTMF keypad, Taylor series, polynomials
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>> A = [1 2 3; 2 0 4; 0 8 5] A = 1 2 3 2 0 4 0 8 5 >> size(A) % [N,M] = size(A), NxM matrix ans = 3 3 matrix indexing convention defining matrices column row dimension dimension no. rows no. columns NxM matrix M N
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accessing matrix elements >> A(1,1) % 11 matrix element ans = 1 >> A(2,3) % 23 matrix element ans = 4 >> A(:,2) % second column ans = 2 0 8 >> A(3,:) % third row ans = 0 8 5
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concatenating columns >> A = [1 2 3; 2 0 4; 0 8 5] A = 1 2 3 2 0 4 0 8 5 >> A(:) % concatenate columns ans = 1 2 0 2 0 8 3 4 5 A(6) A(9) concatenating rows B = A'; B(:) column-wise indexing
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building a matrix column-wise >> A = zeros(3,3); >> A(:) = [1 2 0 2 0 8 3 4 5] A = 1 2 3 2 0 4 0 8 5 define desired size enter elements in a row (or column) elements are re-arranged column-wise
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sub-matrices A = [ 2 4 1 3 5 8 6 7 4 9 3 2 5 2 1 5 6 1 8 4 ]; A(3:4, 2:4) ans = 2 5 2 6 1 8 A(1:3, [1,5]) ans = 2 5 8 9 3 1
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>> A = [1 2 3 4; 2 0 5 6; 0 8 7 9] % size 3x4 A = 1 2 3 4 2 0 5 6 0 8 7 9 >> A' % size 4x3 ans = 1 2 0 2 0 8 3 5 7 4 6 9 transposing a matrix => transposition operation
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adding/deleting rows or columns >> A = [1 2 3; 2 0 4; 0 8 5] >> A(5,:) = [7 8 9] % add a fifth row A = 1 2 3 2 0 4 0 8 5 0 0 0 7 8 9 >> A(:,2) = [] % delete second column A = 1 3 2 4 0 5 0 0 7 9 4 th row is automatically allocated [ ] denotes an empty 0x0 matrix alternatively, redefine A by omitting its second column: >> A = A([1,3],:);
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replacing rows or columns >> A = [1 2 3; 2 0 4; 0 8 5] A = 1 2 3 2 0 4 0 8 5 >> A(:,2) = [20 30 40]' % replace second column A = 1 20 3 2 30 4 0 40 5 >> A(3,:) = [50 60 70] % replace third row A = 1 20 3 2 30 4 50 60 70
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inserting rows or columns >> A = [1 2 3; 2 0 4; 0 8 5] A = 1 2 3 2 0 4 0 8 5 % insert new column between columns 2 & 3 A = [A(:,1:2), [10 20 30]', A(:,3)] A = 1 2 10 3 2 0 20 4 0 8 30 5 % insert new row between rows 1 & 2 A = [A(1,:); [60 70 80 90]; A(2:3,:)] A = 1 2 10 3 60 70 80 90 2 0 20 4 0 8 30 5
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concatenating matrices >> A = [1 2; 3 4]; >> B = [5 6; 7 8]; >> C = [A, B] C = 1 2 5 6 3 4 7 8 >> C = [A; B] C = 1 2 3 4 5 6 7 8 A,B must have same number of rows A,B must have same number of columns
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