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Section 6.3

Section 6.3. Orthonormal Bases; Gram-Schmidt Process; QR -Decomposition. ORTHONORMAL SETS OF VECTORS.

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Section 6.3

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  1. Section 6.3 Orthonormal Bases; Gram-Schmidt Process; QR-Decomposition

  2. ORTHONORMAL SETS OF VECTORS A set of vectors in an inner product space is called an orthogonal set if all pairs of distinct vectors in the set are orthogonal. An orthogonal set in which each vector has norm 1 is called orthonormal.

  3. ORTHOGONAL AND ORTHONORMAL BASES • In an inner product space, a basis consisting of orthogonal vectors is called an orthogonal basis. • In an inner product space, a basis consisting of orthonormal vectors is called an orthonormal basis.

  4. COORDINATES RELATIVE TO AN ORTHONORMAL BASES Theorem 6.3.1: If S = {v1, v2, . . . , vn} is an orthonormal basis for an inner product space V, and if u is any vector in V, then u = ‹u, v1› v1 + ‹u, v2› v2 + . . . + ‹u, vn› vn

  5. THEOREM Theorem 6.3.2: If S is an orthonormal basis for an n-dimensional inner product space, and if (u)S = (u1, u2, . . . , un)and (v)S = (v1, v2, . . . , vn) then:

  6. THEOREM Theorem 6.3.3: If S = {v1, v2, . . . , vn} is an orthogonal set of nonzero vectors in an inner product space, then S is linearly independent.

  7. THE PROJECTION THEOREM Theorem 6.3.4: If W is a finite-dimensional subspace of an inner product space V, then every vector u in V can be expressed inexactly one way as u = w1 + w2 where w1 is in W and w2 in W┴. NOTE: w1 is called the orthogonal projection of u on W and is denoted by projW u. The vector w2 is called the complement of u orthogonal to W and is denoted by projW┴u.

  8. THEOREM Theorem 6.3.5: Let W be a finite-dimensional subspace of an inner product space V. (a) If {v1, v2, . . . , vr} is an orthonormal basis for W, and u is any vector in V, then projWu = ‹u, v1› v1 + ‹u, v2› v2 + . . . + ‹u, vr› vr (b) If {v1, v2, . . . , vr} is an orthogonal basis for W, and u is any vector in V, then

  9. THEOREM Theorem 6.3.6: Every nonzero finite-dimensional inner product space has an orthonormal basis.

  10. THE GRAM-SCHMIDT PROCESS Let V be a finite-dimensional inner product space, with a basis {u1, u2, . . . , un} These steps produce an orthogonal basis. STEP 1: Let v1 = u1. STEP 2: .Construct the vector v2 orthogonal to v1 by finding the complement of u2 that is orthogonal to W1 = span{v1}. STEP 3: Construct the vector v3 which is orthogonal to v1 and v2 by constructing the complement of u3 that is orthogonal to W2 = span{v1, v2}.

  11. G-S PROCESS (CONCLUDED) STEP 4: Construct the vector v4 which is orthogonal to v1, v2, v3 by constructing the complement of u4 that is orthogonal to W2 = span{v1, v2, v3}. Continue the process for n steps until all ui are exhausted.

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