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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 \({{\mathop{\rm x}\nolimits} _4} = {\mathop{\rm v}\nolimits} \).

Given \(T:V \to W\) as in Exercise 35, and given a subspace \(Z\) of \(W\), let \(U\) be the set of all \({\mathop{\rm x}\nolimits} \) in \(V\) such that \(T\left( {\mathop{\rm x}\nolimits} \right)\) is in \(Z\). Show that \(U\) is a subspace of \(V\).

Question: Exercises 12-17 develop properties of rank that are sometimes needed in applications. Assume the matrix \(A\) is \(m \times n\).

17. A submatrix of a matrix A is any matrix that results from deleting some (or no) rows and/or columns of A. It can be shown that A has rank \(r\) if and only if A contains an invertible \(r \times r\) submatrix and no longer square submatrix is invertible. Demonstrate part of this statement by explaining (a) why an \(m \times n\) matrix A of rank \(r\) has an \(m \times r\) submatrix \({A_1}\) of rank \(r\), and (b) why \({A_1}\) has an invertible \(r \times r\) submatrix \({A_2}\).

The concept of rank plays an important role in the design of engineering control systems, such as the space shuttle system mentioned in this chapterโ€™s introductory example. A state-space model of a control system includes a difference equation of the form

\({{\mathop{\rm x}\nolimits} _{k + 1}} = A{{\mathop{\rm x}\nolimits} _k} + B{{\mathop{\rm u}\nolimits} _k}\)for \(k = 0,1,....\) (1)

Where \(A\) is \(n \times n\), \(B\) is \(n \times m\), \(\left\{ {{{\mathop{\rm x}\nolimits} _k}} \right\}\) is a sequence of โ€œstate vectorsโ€ in \({\mathbb{R}^n}\) that describe the state of the system at discrete times, and \(\left\{ {{{\mathop{\rm u}\nolimits} _k}} \right\}\) is a control, or input, sequence. The pair \(\left( {A,B} \right)\) is said to be controllable if

\({\mathop{\rm rank}\nolimits} \left( {\begin{array}{*{20}{c}}B&{AB}&{{A^2}B}& \cdots &{{A^{n - 1}}B}\end{array}} \right) = n\) (2)

The matrix that appears in (2) is called the controllability matrix for the system. If \(\left( {A,B} \right)\) is controllable, then the system can be controlled, or driven from the state 0 to any specified state \({\mathop{\rm v}\nolimits} \) (in \({\mathbb{R}^n}\)) in at most \(n\) steps, simply by choosing an appropriate control sequence in \({\mathbb{R}^m}\). This fact is illustrated in Exercise 18 for \(n = 4\) and \(m = 2\). For a further discussion of controllability, see this textโ€™s website (Case study for Chapter 4).

Question 11: Let \(S\) be a finite minimal spanning set of a vector space \(V\). That is, \(S\) has the property that if a vector is removed from \(S\), then the new set will no longer span \(V\). Prove that \(S\) must be a basis for \(V\).

Let \(B = \left\{ {\left( {\begin{array}{*{20}{c}}{\bf{1}}\\{ - {\bf{4}}}\end{array}} \right),\,\left( {\begin{array}{*{20}{c}}{ - {\bf{2}}}\\{\bf{9}}\end{array}} \right)\,} \right\}\). Since the coordinate mapping determined by B is a linear transformation from \({\mathbb{R}^{\bf{2}}}\) into \({\mathbb{R}^{\bf{2}}}\), this mapping must be implemented by some \({\bf{2}} \times {\bf{2}}\) matrix A. Find it. (Hint: Multiplication by A should transform a vector x into its coordinate vector \({\left( {\bf{x}} \right)_B}\)).

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