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Show that the signals in Exercises 3-6 form a basis for the solution set of the accompanying difference equation.

The signals and equation in Exercise 1.

Short Answer

Expert verified

\(\left\{ {{2^k},{{\left( { - 4} \right)}^k}} \right\}\) forms a basis for the difference equation.

Step by step solution

01

Check the dependence of the solution

For any scalar \({c_1}\) and \({c_2}\),

\({c_1}{\left( 2 \right)^k} + {c_2}{\left( { - 4} \right)^k} = 0\).

Write the above equation in the matrix form.

\(\begin{aligned} \left[ {\begin{array}{*{20}{c}}{{2^k}}&{{{\left( { - 4} \right)}^k}}\\{{2^{k + 1}}}&{{{\left( { - 4} \right)}^{k + 1}}}\end{array}} \right]\left[ {\begin{array}{*{20}{c}}{{c_1}}\\{{c_2}}\end{array}} \right] &= \left[ {\begin{array}{*{20}{c}}0\\0\end{array}} \right]\\{A_k}c &= 0\end{aligned}\)

So, \({3^k}\) is the solution of the given difference equation.

02

Write the augmented matrix for the matrix equation

For \(k = 0\), you get

\(\begin{aligned} \left[ {\begin{array}{*{20}{c}}{{2^k}}&{{{\left( { - 4} \right)}^k}}\\{{2^{k + 1}}}&{{{\left( { - 4} \right)}^{k + 1}}}\end{array}} \right] &= \left[ {\begin{array}{*{20}{c}}{{2^0}}&{{{\left( { - 4} \right)}^0}}\\{{2^1}}&{{{\left( { - 4} \right)}^1}}\end{array}} \right]\\ &= \left[ {\begin{array}{*{20}{c}}1&1\\2&{ - 4}\end{array}} \right]\\ &= \left[ {\begin{array}{*{20}{c}}1&1\\0&{ - 6}\end{array}} \right].\end{aligned}\)

There is a pivot column in each row, and the system has a trivial solution. So, the signals \(\left\{ {{2^k},\,\,{{\left( { - 4} \right)}^k}} \right\}\) are linearly independent.

03

Check whether the solution is the basis of the difference equation

The solution set of the equation \({y_{k + 2}} + 2{y_{k + 1}} - 8{y_k} = 0\) is two dimensional and linearly independent.

Therefore, by the basis theorem, the set \(\left\{ {{2^k},{{\left( { - 4} \right)}^k}} \right\}\) forms a basis for the difference equation \({y_{k + 2}} + 2{y_{k + 1}} - 8{y_k} = 0\).

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Most popular questions from this chapter

In Exercise 7, find the coordinate vector \({\left( x \right)_{\rm B}}\) of x relative to the given basis \({\rm B} = \left\{ {{b_{\bf{1}}},...,{b_n}} \right\}\).

7. \({b_{\bf{1}}} = \left( {\begin{array}{*{20}{c}}{\bf{1}}\\{ - {\bf{1}}}\\{ - {\bf{3}}}\end{array}} \right),{b_{\bf{2}}} = \left( {\begin{array}{*{20}{c}}{ - {\bf{3}}}\\{\bf{4}}\\{\bf{9}}\end{array}} \right),{b_{\bf{3}}} = \left( {\begin{array}{*{20}{c}}{\bf{2}}\\{ - {\bf{2}}}\\{\bf{4}}\end{array}} \right),x = \left( {\begin{array}{*{20}{c}}{\bf{8}}\\{ - {\bf{9}}}\\{\bf{6}}\end{array}} \right)\)

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

13. Show that if \(P\) is an invertible \(m \times m\) matrix, then rank\(PA\)=rank\(A\).(Hint: Apply Exercise12 to \(PA\) and \({P^{ - 1}}\left( {PA} \right)\).)

Suppose a nonhomogeneous system of nine linear equations in ten unknowns has a solution for all possible constants on the right sides of the equations. Is it possible to find two nonzero solutions of the associated homogeneous system that are not multiples of each other? Discuss.

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: 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).

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