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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

Question 18: Suppose A is a \(4 \times 4\) matrix and B is a \(4 \times 2\) matrix, and let \({{\mathop{\rm u}\nolimits} _0},...,{{\mathop{\rm u}\nolimits} _3}\) represent a sequence of input vectors in \({\mathbb{R}^2}\).

  1. Set \({{\mathop{\rm x}\nolimits} _0} = 0\), compute \({{\mathop{\rm x}\nolimits} _1},...,{{\mathop{\rm x}\nolimits} _4}\) from equation (1), and write a formula for \({{\mathop{\rm x}\nolimits} _4}\) involving the controllability matrix \(M\) appearing in equation (2). (Note: The matrix \(M\) is constructed as a partitioned matrix. Its overall size here is \(4 \times 8\).)
  2. Suppose \(\left( {A,B} \right)\) is controllable and v is any vector in \({\mathbb{R}^4}\). Explain why there exists a control sequence \({{\mathop{\rm u}\nolimits} _0},...,{{\mathop{\rm u}\nolimits} _3}\) in \({\mathbb{R}^2}\) such that \({{\mathop{\rm x}\nolimits} _4} = {\mathop{\rm v}\nolimits} \).

Question: Determine if the matrix pairs in Exercises 19-22 are controllable.

21. (M) \(A = \left( {\begin{array}{*{20}{c}}0&1&0&0\\0&0&1&0\\0&0&0&1\\{ - 2}&{ - 4.2}&{ - 4.8}&{ - 3.6}\end{array}} \right),B = \left( {\begin{array}{*{20}{c}}1\\0\\0\\{ - 1}\end{array}} \right)\).

(M) Show thatis a linearly independent set of functions defined on. Use the method of Exercise 37. (This result will be needed in Exercise 34 in Section 4.5.)

In Exercise 17, Ais an \(m \times n\] matrix. Mark each statement True or False. Justify each answer.

17. a. The row space of A is the same as the column space of \({A^T}\].

b. If B is any echelon form of A, and if B has three nonzero rows, then the first three rows of A form a basis for Row A.

c. The dimensions of the row space and the column space of A are the same, even if Ais not square.

d. The sum of the dimensions of the row space and the null space of A equals the number of rows in A.

e. On a computer, row operations can change the apparent rank of a matrix.

Consider the polynomials \({p_{\bf{1}}}\left( t \right) = {\bf{1}} + {t^{\bf{2}}},{p_{\bf{2}}}\left( t \right) = {\bf{1}} - {t^{\bf{2}}}\). Is \(\left\{ {{p_{\bf{1}}},{p_{\bf{2}}}} \right\}\) a linearly independent set in \({{\bf{P}}_{\bf{3}}}\)? Why or why not?

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