Section 6.2: THE KERNEL AND RANGE OF A LINEAR TRANSFORMATIONS

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1 Section 6.2: THE KERNEL AND RANGE OF A LINEAR TRANSFORMATIONS When you are done with your homework you should be able to Find the kernel of a linear transformation Find a basis for the range, the rank, and the nullity of a linear transformation Determine whether a linear transformation is one-to-one or onto Determine whether vector spaces are isomorphic THE KERNEL OF A LINEAR TRANSFORMATION We know from Theorem 6.1 that for any linear transformation, the zero vector in maps to the vector in. That is,. In this section, we will consider whether there are other vectors such that. The collection of all such is called the of. Note that the zero vector is denoted by the symbol in both and, even though these two zero vectors are often different. DEFINITION OF KERNEL OF A LINEAR TRANSFORMATION W be a linear transformation. Then the set of all vectors v in V that satisfy is called the of T and is denoted by. CREATED BY SHANNON MARTIN GRACEY 166

2 Example 1: Find the kernel of the linear transformation. a. T : R 3 R 3, T x, y, z x, 0, z T : P P, T a a x a x a x a 2a x 3a x b. c. T : P R, 2 1 T p p x dx 0 CREATED BY SHANNON MARTIN GRACEY 167

3 THEOREM 6.3: THE KERNEL IS A SUBSPACE OF V The kernel of a linear transformation T : V Proof: W is a subspace of the domain V. THEOREM 6.3: COROLLARY n Let T : R R m be the linear transformation given by T x Ax. Then the kernel of T is equal to the solution space of. THEOREM 6.4: THE RANGE OF T IS A SUBSPACE OF W The range of a linear transformation T : V W is a subspace of W. CREATED BY SHANNON MARTIN GRACEY 168

4 THEOREM 6.4: COROLLARY n Let T : R R m be the linear transformation given by T x Ax. Then the Column space of is equal to the of. Example 2: Let T v for the kernel of T and the range of T. Av represent the linear transformation T. Find a basis A CREATED BY SHANNON MARTIN GRACEY 169

5 DEFINITION OF RANK AND NULLITY OF A LINEAR TRANSFORMATION W be a linear transformation. The dimension of the kernel of T is called the of T and is denoted by. The dimension of the range of T is called the of T and is denoted by. THEOREM 6.5: SUM OF RANK AND NULLITY W be a linear transformation from an n-dimensional vector space V into a vector space W. Then the of the of the and is equal to the dimension of the. That is, Proof: CREATED BY SHANNON MARTIN GRACEY 170

6 Example 3: Define the linear transformation T by nullity T, range T, and rank T. T x Ax. Find ker T, A CREATED BY SHANNON MARTIN GRACEY 171

7 3 3 Example 4: Let T : R R be a linear transformation. Use the given information to find the nullity of T and give a geometric description of the kernel and range of T. T is the reflection through the yz-coordinate plane:,,,, T x y z x y z ONE-TO-ONE AND ONTO LINEAR TRANSFORMATIONS If the vector is the only vector such that, then is. A function is called one-to-one when the of every in the range consists of a vector. This is equivalent to saying that is one-to-one if and only if, for all and in, implies that. CREATED BY SHANNON MARTIN GRACEY 172

8 THEOREM 6.6: ONE-TO-ONE LINEAR TRANSFORMATIONS W be a linear transformation. Then T is one-to-one if and only if. Proof: THEOREM 6.7: LINEAR TRANSFORMATIONS W be a linear transformation, where W is finite dimensional. Then T is onto if and only if the of T is equal to the of W. Proof: CREATED BY SHANNON MARTIN GRACEY 173

9 THEOREM 6.8: ONE-TO-ONE AND ONTO LINEAR TRANSFORMATIONS W be a linear transformation with vector spaces V and W, of dimension n. Then T is one-to-one if and only if it is. Example 5: Determine whether the linear transformation is one-to-one, onto, or neither. 2 2 T : R R, T x, y T x y, y x CREATED BY SHANNON MARTIN GRACEY 174

10 DEFINITION: ISOMORPHISM A linear transformation T : V W that is and is called an. Moreover, if V and W are vector spaces such that there exists an isomorphism from V to W, then V and W are said to be to each other. THEOREM 6.9: ISOMORPHIC SPACES AND DIMENSION Two finite dimensional vector spaces V and W are if and only if they are of the same. Example 6: Determine a relationship among m, n, j, and k such that M m, n is isomorphic to M j, k. CREATED BY SHANNON MARTIN GRACEY 175

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