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Let \({y_k} = {k^2}\)and \({z_k} = 2k\left| k \right|\). Are the signals \(\left\{ {{y_k}} \right\}\) and \(\left\{ {{z_k}} \right\}\) linearly independent? Evaluate the associated Casorati matrix \(C\left( k \right)\) for \(k = 0\), \(k = - 1\), and \(k = - 2\), and discuss your results.

Short Answer

Expert verified

No conclusion can be drawn about the signals \({y_k}\) and \({z_k}\), whether these are linearly independent or not.

\(C\left( 0 \right) = \left( {\begin{array}{*{20}{c}}0&0\\1&1\end{array}} \right)\), \(C\left( { - 1} \right) = \left( {\begin{array}{*{20}{c}}1&2\\0&0\end{array}} \right)\), \(C\left( { - 2} \right) = \left( {\begin{array}{*{20}{c}}4&{ - 8}\\1&{ - 2}\end{array}} \right)\), and the Casorati matrix is non invertible.

Step by step solution

01

Define Casorati matrix \(C\left( k \right)\) for \({y_k}\),\({z_k}\)

It is given that \({y_k} = {k^2}\) and \({z_k} = 2k\left| k \right|\).

\(C\left( k \right)\)can be evaluated as shown below:

\(\begin{aligned} C\left( k \right) &= \left( {\begin{array}{*{20}{c}}{{y_k}}&{{z_k}}\\{{y_{k + 1}}}&{{z_{k + 1}}}\end{array}} \right)\\ &= \left( {\begin{array}{*{20}{c}}{{k^2}}&{2k\left| k \right|}\\{{{\left( {k + 1} \right)}^2}}&{2\left( {k + 1} \right)\left| {k + 1} \right|}\end{array}} \right)\end{aligned}\)

02

Find \(C\left( 0 \right)\), \(C\left( { - 1} \right)\), \(C\left( { - 2} \right)\)

\(\begin{aligned} C\left( 0 \right) &= \left( {\begin{array}{*{20}{c}}{{{\left( 0 \right)}^2}}&{2\left( 0 \right)\left| 0 \right|}\\{{{\left( {0 + 1} \right)}^2}}&{2\left( {0 + 1} \right)\left| {0 + 1} \right|}\end{array}} \right)\\ &= \left( {\begin{array}{*{20}{c}}0&0\\1&1\end{array}} \right)\end{aligned}\)

\(\begin{aligned} C\left( 0 \right) &= \left( {\begin{array}{*{20}{c}}{{{\left( { - 1} \right)}^2}}&{2\left( { - 1} \right)\left| { - 1} \right|}\\{{{\left( { - 1 + 1} \right)}^2}}&{2\left( { - 1 + 1} \right)\left| { - 1 + 1} \right|}\end{array}} \right)\\ &= \left( {\begin{array}{*{20}{c}}1&2\\0&0\end{array}} \right)\end{aligned}\)

\(\begin{aligned} C\left( { - 2} \right) &= \left( {\begin{array}{*{20}{c}}{{{\left( { - 2} \right)}^2}}&{2\left( { - 2} \right)\left| { - 2} \right|}\\{{{\left( { - 2 + 1} \right)}^2}}&{2\left( { - 2 + 1} \right)\left| { - 2 + 1} \right|}\end{array}} \right)\\ &= \left( {\begin{array}{*{20}{c}}4&{ - 8}\\1&{ - 2}\end{array}} \right)\end{aligned}\)

03

Find the determinant of the Casorati matrix

The determinant of the Casorati matrix \(C\left( k \right)\)is evaluated below:

\(\begin{aligned} C\left( k \right) &= \left( {\begin{array}{*{20}{c}}{{k^2}}&{2k\left| k \right|}\\{{{\left( {k + 1} \right)}^2}}&{2\left( {k + 1} \right)\left| {k + 1} \right|}\end{array}} \right)\\ &= {k^2}\left( {2\left( {k + 1} \right)\left| {k + 1} \right|} \right) - \left( {2k\left| k \right|} \right){\left( {k + 1} \right)^2}\\ &= 2k\left( {k + 1} \right)\left( {k\left| {k + 1} \right| - \left( {k + 1} \right)\left| k \right|} \right)\end{aligned}\)

04

Discuss the cases for all values of \(k\)

There are three factors in the determinant expression.

The determinant is 0 if all or either of the three factors is zero.

So, if either \(k = 0\) or \(k = - 1\), the determinant is 0.

If \(k > 0\) or \(k > - 1\), the third factor simplifies as

\(\begin{array}{c}k\left| {k + 1} \right| - \left( {k + 1} \right)\left| k \right| = k\left( {k + 1} \right) - \left( {k + 1} \right)k\\ = 0.\end{array}\)

If \(k + 1 < 0\)or \(k < - 1\), the third factor simplifies as

\(\begin{array}{c}k\left| {k + 1} \right| - \left( {k + 1} \right)\left| k \right| = - k\left( {k + 1} \right) + \left( {k + 1} \right)k\\ = 0.\end{array}\)

05

Draw a conclusion

For all the natural values \(k\), the value of the determinant of \(C\left( k \right)\)is 0. Thus, the Casorati matrix cannot be inverted. It implies that no information can be extracted about signals \({y_k}\) and \({z_k}\), whether these are linearly independent or not.

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Most popular questions from this chapter

In Exercises 19 and 20, \(V\) is a vector space. Mark each statement True or False. Justify each answer.

19.

a. The number of pivot columns of a matrix equals the dimension of its column space.

b. A plane in \({\mathbb{R}^3}\) is a two-dimensional subspace of \({\mathbb{R}^3}\).

c. The dimension of the vector space \({{\mathop{\rm P}\nolimits} _4}\) is 4.

d. If \(\dim V = n\) and \(S\) is a linearly independent set in \(V\), then \(S\) is a basis for \(V\).

e. If a set \(\left\{ {{{\mathop{\rm v}\nolimits} _1},...,{{\mathop{\rm v}\nolimits} _p}} \right\}\) spans a finite-dimensional vector space \(V\) and if \(T\) is a set of more than p vectors in \(V\), then \(T\) is linearly dependent.

In Exercises 7-10, let \(B = \left\{ {{{\mathop{\rm b}\nolimits} _1},{{\mathop{\rm b}\nolimits} _2}} \right\}\) and \(C = \left\{ {{{\mathop{\rm c}\nolimits} _1},{{\mathop{\rm c}\nolimits} _2}} \right\}\) be bases for \({\mathbb{R}^2}\). In each exercise, find the change-of-coordinates matrix from \(B\) to \(C\) and the change-of-coordinates matrix from \(C\) to \(B\).

10. \({{\mathop{\rm b}\nolimits} _1} = \left( {\begin{array}{*{20}{c}}7\\{ - 2}\end{array}} \right),{{\mathop{\rm b}\nolimits} _2} = \left( {\begin{array}{*{20}{c}}2\\{ - 1}\end{array}} \right),{{\mathop{\rm c}\nolimits} _1} = \left( {\begin{array}{*{20}{c}}4\\1\end{array}} \right),{{\mathop{\rm c}\nolimits} _2} = \left( {\begin{array}{*{20}{c}}5\\2\end{array}} \right)\).

If a \({\bf{3}} \times {\bf{8}}\) matrix A has a rank 3, find dim Nul A, dim Row A, and rank \({A^T}\).

(M) Determine whether w is in the column space of \(A\), the null space of \(A\), or both, where

\({\mathop{\rm w}\nolimits} = \left( {\begin{array}{*{20}{c}}1\\1\\{ - 1}\\{ - 3}\end{array}} \right),A = \left( {\begin{array}{*{20}{c}}7&6&{ - 4}&1\\{ - 5}&{ - 1}&0&{ - 2}\\9&{ - 11}&7&{ - 3}\\{19}&{ - 9}&7&1\end{array}} \right)\)

In Exercises 29 and 30, V is a nonzero finite-dimensional vector space, and the vectors listed belong to V. Mark each statement True or False. Justify each answer. (These questions are some difficult than those 19 and 20.)

30.

a. If there exists a linearly dependent set \(\left\{ {{{\mathop{\rm v}\nolimits} _1},...,{{\mathop{\rm v}\nolimits} _p}} \right\}\) in \(V\), then \(\dim V \le p\).

b. If every set of \(p\) elements in \(V\) fails to span \(V\), then \(\dim V > p\).

c. If \(p \ge 2\), and \(\dim V = p\), then every set of \(p - 1\) nonzero vectors is linearly independent.

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