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gibson:teaching:fall-2014:math445:hw5

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====== Math 445 HW5 ====== Main concept for this homework: the ''for'' loop. 1. Write a function ''mymean'' that uses a ''for'' loop to compute the mean of the elements of its input vector. Test that it's correct by comparing to Matlab's built-in ''mean'' function on a random vector. 2. Write a function ''mystd'' that uses a ''for'' loop to computes the standard deviation of the elements of its input vector. Test by comparison Matlab's built-in ''std'' function on a random vector. 3. Write a script that produces a 10 x 10 multiplication table whose first three lines are <code> 1 2 3 4 5 6 7 8 9 10 2 4 6 8 10 12 14 16 18 20 3 6 9 12 15 18 21 24 27 30 . . . </code> Try to get the output in **exactly** this form. 4. Write a function ''y = matvecmult(A,x)'' that uses nested ''for'' loops to compute the matrix-vector product //y = Ax// according to the formula \begin{eqnarray*} y_i = sum_{j=1^N} A_{ij} x_j \end{eqnarray*} where //N// is the number of columns of //A//. Be sure to check for compatibility between //A// and //x//. For an //M x N// matrix //A//, //x// must be an //N//-dimensional column vector, and //y// will be an //M//-dimensional column vector. If //A// and //x// do not have compatible dimensions, print an error message and return //0//-dimensional vector (a null vector). 5. Write a function ''C = matmatmult(A,B)'' that uses nested ''for'' loops to compute the matrix-vector product //C=AB// according to the formula \begin{eqnarray*} C_{ij} = sum_{j=1^N} A_{ik} C_{kj} \end{eqnarray*} where //N// is the number of columns of //A//. If A is //M x N// and //B// is //N x P//, then //C// is //M x P//. If //A// and //B// do not have compatible dimensions, print an error message and return a //0 x 0// matrix.

gibson/teaching/fall-2014/math445/hw5.1413229669.txt.gz · Last modified: 2014/10/13 12:47 by gibson