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Consider an n 脳 m matrix A with rank(A) = r < m. Explain how you can write ker(A) as the span of m 鈭 r vectors.

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01

Step 1:The kernel of a linear transformation

ThekernelofalineartransformationTx=AxfrommtonisthesoluctionsetofthelinersystemAx=0.

02

Proving ker(A) as the span of m − r vectors.

Consider an nxm matrix A with; rank (A)=r<m. By the definition of the kernel of a linear transformation, ker(A) is the solution set of the linear system

Since A is an nxm matrix with rank (A)=r<m.

Therefore, the solution set of A must have non-leading or free variables. Since, the kernel consists of zero-valued variables (vectors). Therefore, any vector in ker (A) can be expressed as a linear combination of them-n non-leading or free variables.

Hence, the definition of spanker(A) can be written as a span of m-r vectors.

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