S o l u t i o n : B y d e f i n i t i o n o f k e r n e l A , k e r ( A ) = { x ∈ R 5 ∣ A x = 0 } . ∴ w e s o l v e t h e e q u a t i o n , A x = 0 Solution: By ~definition~ of~ kernel~ A, ker(A)= \{x \in R^5 |Ax=0 \}. \\ \therefore ~we ~solve~ the~ equation,~ Ax=0 S o l u t i o n : B y d e f ini t i o n o f k er n e l A , k er ( A ) = { x ∈ R 5 ∣ A x = 0 } . ∴ w e so l v e t h e e q u a t i o n , A x = 0
∴ [ 2 3 1 2 0 0 3 − 1 2 1 1 − 3 2 4 3 2 3 0 3 0 ] [ x 1 x 2 x 3 x 4 x 5 ] = [ 0 0 0 0 ] , w h e r e A = [ 2 3 1 2 0 0 3 − 1 2 1 1 − 3 2 4 3 2 3 0 3 0 ] , x = [ x 1 x 2 x 3 x 4 x 5 ] a n d 0 = [ 0 0 0 0 ] \therefore \begin{bmatrix}
2 & 3 & 1 & 2 & 0 \\
0 & 3 & -1 & 2 & 1 \\
1 & -3 & 2 & 4 & 3 \\
2&3&0&3&0
\end{bmatrix}
\begin{bmatrix} x_1 \\x_2\\x_3\\x_4\\x_5\end{bmatrix}
=\begin{bmatrix} 0 \\0\\0\\0\end{bmatrix} , \\where ~A=\begin{bmatrix}
2 & 3 & 1 & 2 & 0 \\
0 & 3 & -1 & 2 & 1 \\
1 & -3 & 2 & 4 & 3 \\
2&3&0&3&0
\end{bmatrix}~,x=\begin{bmatrix} x_1 \\x_2\\x_3\\x_4\\x_5\end{bmatrix}~ and~ 0=\begin{bmatrix} 0 \\0\\0\\0\end{bmatrix} ∴ ⎣ ⎡ 2 0 1 2 3 3 − 3 3 1 − 1 2 0 2 2 4 3 0 1 3 0 ⎦ ⎤ ⎣ ⎡ x 1 x 2 x 3 x 4 x 5 ⎦ ⎤ = ⎣ ⎡ 0 0 0 0 ⎦ ⎤ , w h ere A = ⎣ ⎡ 2 0 1 2 3 3 − 3 3 1 − 1 2 0 2 2 4 3 0 1 3 0 ⎦ ⎤ , x = ⎣ ⎡ x 1 x 2 x 3 x 4 x 5 ⎦ ⎤ an d 0 = ⎣ ⎡ 0 0 0 0 ⎦ ⎤
N o w w e w r i t e i n a u g m e n t e d m a t r i x f o r m a s Now ~we~ write ~ in ~ augmented ~ matrix ~ form ~ as N o w w e w r i t e in a ug m e n t e d ma t r i x f or m a s
∴ [ 2 3 1 2 0 ∣ 0 0 3 − 1 2 1 ∣ 0 1 − 3 2 4 3 ∣ 0 2 3 0 3 0 ∣ 0 ] N o w s o l v e t h i s a u g m e n t e d m a t r i x t o g e t s o l u t i o n o f A x = 0 \therefore \begin{bmatrix}
2 & 3 & 1 & 2 & 0 &|0\\
0 & 3 & -1 & 2 & 1&|0 \\
1 & -3 & 2 & 4 & 3&|0 \\
2 & 3 & 0 & 3 & 0 &|0
\end{bmatrix} \\Now ~solve ~ this ~ augmented ~ matrix ~ to ~ get~ solution ~ of ~Ax=0 ∴ ⎣ ⎡ 2 0 1 2 3 3 − 3 3 1 − 1 2 0 2 2 4 3 0 1 3 0 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤ N o w so l v e t hi s a ug m e n t e d ma t r i x t o g e t so l u t i o n o f A x = 0
A p p l y i n g R 1 ⇒ ( 1 2 ) R 1 [ 1 3 2 1 2 1 0 ∣ 0 0 3 − 1 2 1 ∣ 0 1 − 3 2 4 3 ∣ 0 2 3 0 3 0 ∣ 0 ] Applying ~ R_1\Rightarrow(\frac{1}{2})R_1
\\ \begin{bmatrix}
1 & \frac{3}{2} & \frac{1}{2} & 1 & 0 &|0\\
0 & 3 & -1 & 2 & 1&|0 \\
1 & -3 & 2 & 4 & 3&|0 \\
2 & 3 & 0 & 3 & 0 &|0
\end{bmatrix} A ppl y in g R 1 ⇒ ( 2 1 ) R 1 ⎣ ⎡ 1 0 1 2 2 3 3 − 3 3 2 1 − 1 2 0 1 2 4 3 0 1 3 0 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤
A p p l y i n g R 3 ⇒ R 3 − R 1 a n d R 4 ⇒ R 4 − 2 R 1 [ 1 3 2 1 2 1 0 ∣ 0 0 3 − 1 2 1 ∣ 0 0 − 9 2 3 2 3 3 ∣ 0 0 0 − 1 1 0 ∣ 0 ] Applying ~ R_3\Rightarrow ~ R_3-R_1~ and ~R_4\Rightarrow ~ R_4-2R_1
\\ \begin{bmatrix}
1 & \frac{3}{2} & \frac{1}{2} & 1 & 0 &|0\\
0 & 3 & -1 & 2 & 1&|0 \\
0 & -\frac{9}{2} & \frac{3}{2} & 3 & 3&|0 \\
0 & 0 & -1 & 1 & 0 &|0
\end{bmatrix} A ppl y in g R 3 ⇒ R 3 − R 1 an d R 4 ⇒ R 4 − 2 R 1 ⎣ ⎡ 1 0 0 0 2 3 3 − 2 9 0 2 1 − 1 2 3 − 1 1 2 3 1 0 1 3 0 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤
A p p l y i n g R 2 ⇒ ( 1 3 ) R 2 [ 1 3 2 1 2 1 0 ∣ 0 0 1 − 1 3 2 3 1 3 ∣ 0 0 − 9 2 3 2 3 3 ∣ 0 0 0 − 1 1 0 ∣ 0 ] Applying ~ R_2\Rightarrow ~ (\frac{1}{3})R_2
\\ \begin{bmatrix}
1 & \frac{3}{2} & \frac{1}{2} & 1 & 0 &|0\\
0 & 1 & -\frac{1}{3} & \frac{2}{3}&\frac{1}{3}&|0 \\
0 & -\frac{9}{2} & \frac{3}{2} & 3 & 3&|0 \\
0 & 0 & -1 & 1 & 0 &|0
\end{bmatrix} A ppl y in g R 2 ⇒ ( 3 1 ) R 2 ⎣ ⎡ 1 0 0 0 2 3 1 − 2 9 0 2 1 − 3 1 2 3 − 1 1 3 2 3 1 0 3 1 3 0 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤
A p p l y i n g R 3 ⇒ R 3 + ( 9 2 ) R 2 [ 1 3 2 1 2 1 0 ∣ 0 0 1 − 1 3 2 3 1 3 ∣ 0 0 0 0 6 9 2 ∣ 0 0 0 − 1 1 0 ∣ 0 ] Applying ~ R_3\Rightarrow ~R_3+ (\frac{9}{2})R_2
\\ \begin{bmatrix}
1 & \frac{3}{2} & \frac{1}{2} & 1 & 0 &|0\\
0 & 1 & -\frac{1}{3} & \frac{2}{3}&\frac{1}{3}&|0 \\
0 & 0 & 0 & 6 & \frac{9}{2}&|0 \\
0 & 0 & -1 & 1 & 0 &|0
\end{bmatrix} A ppl y in g R 3 ⇒ R 3 + ( 2 9 ) R 2 ⎣ ⎡ 1 0 0 0 2 3 1 0 0 2 1 − 3 1 0 − 1 1 3 2 6 1 0 3 1 2 9 0 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤
A p p l y i n g R 3 ⇔ R 4 [ 1 3 2 1 2 1 0 ∣ 0 0 1 − 1 3 2 3 1 3 ∣ 0 0 0 − 1 1 0 ∣ 0 0 0 0 6 9 2 ∣ 0 ] Applying ~ R_3 \Leftrightarrow R_4
\\ \begin{bmatrix}
1 & \frac{3}{2} & \frac{1}{2} & 1 & 0 &|0\\
0 & 1 & -\frac{1}{3} & \frac{2}{3}&\frac{1}{3}&|0 \\
0&0&-1&1&0&|0\\
0 & 0 & 0 & 6 & \frac{9}{2}&|0 \\
\end{bmatrix} A ppl y in g R 3 ⇔ R 4 ⎣ ⎡ 1 0 0 0 2 3 1 0 0 2 1 − 3 1 − 1 0 1 3 2 1 6 0 3 1 0 2 9 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤
A p p l y i n g R 3 ⇒ ( − 1 ) R 3 a n d R 4 ⇒ ( 1 6 ) R 4 [ 1 3 2 1 2 1 0 ∣ 0 0 1 − 1 3 2 3 1 3 ∣ 0 0 0 1 − 1 0 ∣ 0 0 0 0 1 3 4 ∣ 0 ] Applying ~ R_3 \Rightarrow(-1) R_3~ and ~ R_4 \Rightarrow(\frac{1}{6}) R_4
\\ \begin{bmatrix}
1 & \frac{3}{2} & \frac{1}{2} & 1 & 0 &|0\\
0 & 1 & -\frac{1}{3} & \frac{2}{3}&\frac{1}{3}&|0 \\
0&0&1&-1&0&|0\\
0 & 0 & 0 & 1 & \frac{3}{4}&|0 \\
\end{bmatrix} A ppl y in g R 3 ⇒ ( − 1 ) R 3 an d R 4 ⇒ ( 6 1 ) R 4 ⎣ ⎡ 1 0 0 0 2 3 1 0 0 2 1 − 3 1 1 0 1 3 2 − 1 1 0 3 1 0 4 3 ∣0 ∣0 ∣0 ∣0 ⎦ ⎤
w h i c h i s r o w e c h e l o n f o r m . N o w w e c a n f i n d t h e s o l u t i o n . H e r e x 5 h a s n o l e a d i n g 1. ∴ x 5 i s f r e e v a r i a b l e . ∴ w e p u t x 5 = t { w h e r e t ∈ R } B y b a c k s u b s t i t u t i o n w e g e t t h e e q u a t i o n s which ~ is ~ row ~ echelon~ form. ~Now~ we ~can ~ find ~ the ~ solution.\\Here~ x_5 ~has~ no ~ leading~ 1. \\ \therefore x_5 ~ ~ is ~ free ~ variable.\\ \therefore we~ put ~ x_5 =t ~~~~\{where~ t\in R\} \\ By ~ back ~ substitution~ we ~ get ~ the ~ equations~ w hi c h i s ro w ec h e l o n f or m . N o w w e c an f in d t h e so l u t i o n . Here x 5 ha s n o l e a d in g 1. ∴ x 5 i s f ree v a r iab l e . ∴ w e p u t x 5 = t { w h ere t ∈ R } B y ba c k s u b s t i t u t i o n w e g e t t h e e q u a t i o n s
x 4 + ( 3 4 ) x 5 = 0 ⇒ x 4 = − 3 4 x 5 = − 3 4 t x 3 − x 4 = 0 ⇒ x 3 = x 4 = − 3 4 t x_4+(\frac{3}{4})x_5=0\Rightarrow x_4=-\frac{3}{4}x_5=-\frac{3}{4}t \\x_3-x_4=0\Rightarrow x_3=x_4=-\frac{3}{4}t x 4 + ( 4 3 ) x 5 = 0 ⇒ x 4 = − 4 3 x 5 = − 4 3 t x 3 − x 4 = 0 ⇒ x 3 = x 4 = − 4 3 t
x 2 − 1 3 x 3 + 2 3 x 4 + 1 3 x 5 = 0 ⇒ x 2 = 1 3 x 3 − 2 3 x 4 − 1 3 x 5 = 1 3 ( − 3 4 t ) − 2 3 ( − 3 4 t ) − 1 3 t = ( − 3 12 ) t + 6 12 t − 1 3 t = t ( − 3 12 + 6 12 − 1 3 ) = t ( 3 12 − 1 3 ) = t ( 1 4 − 1 3 ) = t ( 3 − 4 12 ) = t ( − 1 12 ) = − 1 12 t x_2-\frac{1}{3}x_3+\frac{2}{3}x_4+\frac{1}{3}x_5=0\Rightarrow x_2=\frac{1}{3}x_3-\frac{2}{3}x_4-\frac{1}{3}x_5=\frac{1}{3}(-\frac{3}{4}t)-\frac{2}{3}(-\frac{3}{4}t)-\frac{1}{3}t=(-\frac{3}{12})t+\frac{6}{12}t-\frac{1}{3}t=t(-\frac{3}{12}+\frac{6}{12}-\frac{1}{3})=t(\frac{3}{12}-\frac{1}{3})=t(\frac{1}{4}-\frac{1}{3})=t(\frac{3-4}{12})=t(-\frac{1}{12})=-\frac{1}{12}t x 2 − 3 1 x 3 + 3 2 x 4 + 3 1 x 5 = 0 ⇒ x 2 = 3 1 x 3 − 3 2 x 4 − 3 1 x 5 = 3 1 ( − 4 3 t ) − 3 2 ( − 4 3 t ) − 3 1 t = ( − 12 3 ) t + 12 6 t − 3 1 t = t ( − 12 3 + 12 6 − 3 1 ) = t ( 12 3 − 3 1 ) = t ( 4 1 − 3 1 ) = t ( 12 3 − 4 ) = t ( − 12 1 ) = − 12 1 t
∴ x 2 = − 1 12 t \therefore x_2=-\frac{1}{12}t ∴ x 2 = − 12 1 t
a n d l a s t e q u a t i o n x 1 + 3 2 x 2 + 1 2 x 3 + x 4 = 0 and ~last~ equation~ x_1+\frac{3}{2}x_2+\frac{1}{2}x_3+x_4=0 an d l a s t e q u a t i o n x 1 + 2 3 x 2 + 2 1 x 3 + x 4 = 0
∴ x 1 = − 3 2 x 2 − 1 2 x 3 − x 4 = − 3 2 ( − 1 12 t ) − 1 2 ( − 3 4 t ) − ( − 3 4 t ) = 3 24 t + 3 8 t + 3 4 t \therefore x_1=-\frac{3}{2}x_2-\frac{1}{2}x_3-x_4=-\frac{3}{2}(-\frac{1}{12}t)-\frac{1}{2}(-\frac{3}{4}t)-(-\frac{3}{4}t)=\frac{3}{24}t+\frac{3}{8}t+\frac{3}{4}t ∴ x 1 = − 2 3 x 2 − 2 1 x 3 − x 4 = − 2 3 ( − 12 1 t ) − 2 1 ( − 4 3 t ) − ( − 4 3 t ) = 24 3 t + 8 3 t + 4 3 t
x 1 = t ( 3 24 + 3 8 + 3 4 ) = t ( 1 8 + 3 8 + 3 4 ) = t ( 4 8 + 3 4 ) = t ( 4 8 + 3 4 ) = t ( 1 2 + 3 4 ) = 5 4 t x_1=t(\frac{3}{24}+\frac{3}{8}+\frac{3}{4})=t(\frac{1}{8}+\frac{3}{8}+\frac{3}{4})=t(\frac{4}{8}+\frac{3}{4})=t(\frac{4}{8}+\frac{3}{4})=t(\frac{1}{2}+\frac{3}{4})=\frac{5}{4}t x 1 = t ( 24 3 + 8 3 + 4 3 ) = t ( 8 1 + 8 3 + 4 3 ) = t ( 8 4 + 4 3 ) = t ( 8 4 + 4 3 ) = t ( 2 1 + 4 3 ) = 4 5 t
∴ k e r ( A ) = [ x 1 x 2 x 3 x 4 x 5 ] = { [ 5 4 t − 1 12 t − 3 4 t − 3 4 t 1 ] ∣ t ∈ R } = { [ 5 4 − 1 12 − 3 4 − 3 4 1 ] t ∣ t ∈ R } \therefore ker(A)=\begin{bmatrix} x_1 \\x_2\\x_3\\x_4\\x_5\end{bmatrix}=\{\begin{bmatrix} \frac{5}{4}t \\-\frac{1}{12}t \\-\frac{3}{4}t \\-\frac{3}{4}t\\ 1 \end{bmatrix} | t\in R\}=\{\begin{bmatrix} \frac{5}{4}\\-\frac{1}{12} \\-\frac{3}{4}\\-\frac{3}{4}\\ 1 \end{bmatrix} t ~~| t\in R\} ∴ k er ( A ) = ⎣ ⎡ x 1 x 2 x 3 x 4 x 5 ⎦ ⎤ = { ⎣ ⎡ 4 5 t − 12 1 t − 4 3 t − 4 3 t 1 ⎦ ⎤ ∣ t ∈ R } = { ⎣ ⎡ 4 5 − 12 1 − 4 3 − 4 3 1 ⎦ ⎤ t ∣ t ∈ R }
R a n g e ( A ) = c o l u m n s o f l e a d i n g 1 ′ s i n r o w e c h e l o n f o r m ∴ R a n g e ( A ) = { [ 2 0 1 2 ] , [ 3 3 − 3 3 ] , [ 1 − 1 2 0 ] , [ 2 2 4 3 ] } Range(A)=~columns~ of~leading ~1's ~ in ~ row ~ echelon~ form\\ \therefore~ Range(A)=\{ \begin{bmatrix} 2 \\0\\1\\2\end{bmatrix},\begin{bmatrix} 3 \\3\\-3\\3\end{bmatrix},\begin{bmatrix} 1 \\-1\\2\\0\end{bmatrix},\begin{bmatrix} 2 \\2\\4\\3\end{bmatrix}\} R an g e ( A ) = co l u mn s o f l e a d in g 1 ′ s in ro w ec h e l o n f or m ∴ R an g e ( A ) = { ⎣ ⎡ 2 0 1 2 ⎦ ⎤ , ⎣ ⎡ 3 3 − 3 3 ⎦ ⎤ , ⎣ ⎡ 1 − 1 2 0 ⎦ ⎤ , ⎣ ⎡ 2 2 4 3 ⎦ ⎤ }
R a n k ( A ) = n u m b e r o f n o n z e r o r o w s i n r o w e c h e l o n f o r m r a n k ( A ) = 4 Rank (A)= number ~ of ~ non~ zero~ rows~in ~ row ~ echelon~ form \\ rank(A)=4 R ank ( A ) = n u mb er o f n o n zero ro w s in ro w ec h e l o n f or m r ank ( A ) = 4
B y r a n k n u l l i t y t h e o r e m , r a n k ( A ) + n u l l i t y ( A ) = n , w h e r e n i s n u m b e r o f c o l u m n s i n m a t r i x A By ~rank ~ nullity~ theorem,\\rank(A)+nullity(A)=n, ~ where ~ n ~ is ~ number ~ of ~columns ~ in ~matrix ~A B y r ank n u ll i t y t h eore m , r ank ( A ) + n u ll i t y ( A ) = n , w h ere n i s n u mb er o f co l u mn s in ma t r i x A
∴ 4 + n u l l i t y ( A ) = 5 ⇒ n u l l i t y ( A ) = 5 − 4 = 1 ∴ n u l l i t y ( A ) = 1 \therefore 4+nullity(A)=5\Rightarrow~nullity(A)=5-4=1\\ \therefore nullity(A)=1 ∴ 4 + n u ll i t y ( A ) = 5 ⇒ n u ll i t y ( A ) = 5 − 4 = 1 ∴ n u ll i t y ( A ) = 1
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