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What is the order of the following difference equation? Explain your answer\({y_{k + 3}} + {a_1}{y_{k + 2}} + {a_2}{y_{k + 1}} + {a_3}{y_k} = 0\).

Short Answer

Expert verified

If \({a_3} = 0\) and \({a_2} \ne 0\), the order is 2.

If \({a_3} \ne 0\), the order is 3.

If \({a_3} = {a_2} = 0\) and \({a_1} \ne 0\), the order is 1.

If \({a_3} = {a_2} = {a_1} = 0\), the order is 0.

Step by step solution

01

Discuss the attributes of a difference equation

The given difference equation is \({y_{k + 3}} + {a_1}{y_{k + 2}} + {a_2}{y_{k + 1}} + {a_3}{y_k} = 0\). The order of a difference equation depends on the values of the coefficients \({a_1}\), \({a_2}\), and \({a_3}\).

02

Discuss the cases corresponding to the values of the coefficients

If \({a_3} = 0\) and \({a_2} \ne 0\), then the difference equation can be reduced to \({y_{k + 2}} + {a_1}{y_{k + !}} + {a_2}{y_k} = 0\), which implies that its order is 2.

If \({a_3} \ne 0\), then the difference equation cannot be reduced further, which implies that its order is 3.

If \({a_3} = {a_2} = 0\) and \({a_1} \ne 0\), then the difference equation can be reduced to \({y_{k + 1}} + {a_1}{y_k} = 0\), which implies that its order is 1.

If all the coefficients are zero, that is, \({a_3} = {a_2} = {a_1} = 0\), then the difference equation does not possess any signal value, which implies that its order is 0.

03

Draw a conclusion

If \({a_3} = 0\) and \({a_2} \ne 0\), the order is 2.

If \({a_3} \ne 0\), the order is 3.

If \({a_3} = {a_2} = 0\) and \({a_1} \ne 0\), the order is 1.

If \({a_3} = {a_2} = {a_1} = 0\), the order is 0.

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Most popular questions from this chapter

Let S be a maximal linearly independent subset of a vector space V. In other words, S has the property that if a vector not in S is adjoined to S, the new set will no longer be linearly independent. Prove that S must be a basis of V. [Hint: What if S were linearly independent but not a basis of V?]

Exercises 23-26 concern a vector space V, a basis \(B = \left\{ {{{\bf{b}}_{\bf{1}}},....,{{\bf{b}}_n}\,} \right\}\)and the coordinate mapping \({\bf{x}} \mapsto {\left( {\bf{x}} \right)_B}\).

Given vectors, \({u_{\bf{1}}}\),….,\({u_p}\) and w in V, show that w is a linear combination of \({u_{\bf{1}}}\),….,\({u_p}\) if and only if \({\left( w \right)_B}\) is a linear combination of vectors \({\left( {{{\bf{u}}_{\bf{1}}}} \right)_B}\),….,\({\left( {{{\bf{u}}_p}} \right)_B}\).

In Exercise 2, find the vector x determined by the given coordinate vector \({\left( x \right)_{\rm B}}\) and the given basis \({\rm B}\).

2. \({\rm B} = \left\{ {\left( {\begin{array}{*{20}{c}}{\bf{4}}\\{\bf{5}}\end{array}} \right),\left( {\begin{array}{*{20}{c}}{\bf{6}}\\{\bf{7}}\end{array}} \right)} \right\},{\left( x \right)_{\rm B}} = \left( {\begin{array}{*{20}{c}}{\bf{8}}\\{ - {\bf{5}}}\end{array}} \right)\)

(M) Let \(H = {\mathop{\rm Span}\nolimits} \left\{ {{{\mathop{\rm v}\nolimits} _1},{{\mathop{\rm v}\nolimits} _2}} \right\}\) and \(K = {\mathop{\rm Span}\nolimits} \left\{ {{{\mathop{\rm v}\nolimits} _3},{{\mathop{\rm v}\nolimits} _4}} \right\}\), where

\({{\mathop{\rm v}\nolimits} _1} = \left( {\begin{array}{*{20}{c}}5\\3\\8\end{array}} \right),{{\mathop{\rm v}\nolimits} _2} = \left( {\begin{array}{*{20}{c}}1\\3\\4\end{array}} \right),{{\mathop{\rm v}\nolimits} _3} = \left( {\begin{array}{*{20}{c}}2\\{ - 1}\\5\end{array}} \right),{{\mathop{\rm v}\nolimits} _4} = \left( {\begin{array}{*{20}{c}}0\\{ - 12}\\{ - 28}\end{array}} \right)\)

Then \(H\) and \(K\) are subspaces of \({\mathbb{R}^3}\). In fact, \(H\) and \(K\) are planes in \({\mathbb{R}^3}\) through the origin, and they intersect in a line through 0. Find a nonzero vector w that generates that line. (Hint: w can be written as \({c_1}{{\mathop{\rm v}\nolimits} _1} + {c_2}{{\mathop{\rm v}\nolimits} _2}\) and also as \({c_3}{{\mathop{\rm v}\nolimits} _3} + {c_4}{{\mathop{\rm v}\nolimits} _4}\). To build w, solve the equation \({c_1}{{\mathop{\rm v}\nolimits} _1} + {c_2}{{\mathop{\rm v}\nolimits} _2} = {c_3}{{\mathop{\rm v}\nolimits} _3} + {c_4}{{\mathop{\rm v}\nolimits} _4}\) for the unknown \({c_j}'{\mathop{\rm s}\nolimits} \).)

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 \({P^{ - 1}}\left( {PA} \right)\).)

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