Pengguna:Kekavigi/bak pasir: Perbedaan antara revisi
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{{Short description|Perubahan koordinat di aljabar linear}} |
{{Short description|Perubahan koordinat di aljabar linear}} |
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[[Berkas:3d basis transformation2.svg|jmpl|[[Ruang vektor]] pada yang dibangun dari [[Basis (aljabar linear)|basis]] berisi vektor-vektor berwarna ungu, dapat dibangun pula dari basis berisi vektor-vektor berwarna merah. |
[[Berkas:3d basis transformation2.svg|jmpl|[[Ruang vektor]] pada yang dibangun dari [[Basis (aljabar linear)|basis]] berisi vektor-vektor berwarna ungu, dapat dibangun pula dari basis berisi vektor-vektor berwarna merah. Dengan menyusun setiap vektor berwarna ungu menjadi [[kombinasi linear]] vektor-vektor berwarna merah (dan sebaliknya), pernyataan yang disampaikan menggunakan basis ungu juga dapat disampaikan menggunakan basis merah (dan sebaliknya). ]] |
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⚫ | Dalam [[aljabar linear]], [[Basis (aljabar linear)|basis terurut]] memungkinkan setiap elemen pada sebarang [[ruang vektor]] [[dimensi|berdimensi]] <math>n</math> dinyatakan dalam bentuk vektor koordinat, yakni suatu [[barisan]] <math>n</math>-[[Skalar (matematika)|skalar]] yang disebut [koordinat]. Untuk dua basis berbeda dari suatu ruang vektor, vektor koordinat yang menyatakan elemen <math>v</math> atas basis pertama, umumnya berbeda dengan vektor koordinat yang menyatakan elemen yang sama, namun atas basis yang kedua. '''Perubahan basis''' adalah tindakan mengubah penyataan-pernyataan matematika pada suatu basis, ke pernyataan-pernyataan yang sepadan pada basis yang lain.<ref>{{harvtxt|Anton|1987|pp=221–237}}</ref><ref>{{harvtxt|Beauregard|Fraleigh|1973|pp=240–243}}</ref><ref>{{harvtxt|Nering|1970|pp=50–52}}</ref> |
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A [[linear combination]] of one basis of vectors (purple) obtains new vectors (red). If they are [[linearly independent]], these form a new basis. The linear combinations relating the first basis to the other extend to a [[linear transformation]], called the change of basis. |
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⚫ | Dalam [[aljabar linear]], [[Basis (aljabar linear)|basis terurut]] memungkinkan setiap elemen pada sebarang [[ruang vektor]] [[dimensi|berdimensi]] <math>n</math> dinyatakan dalam bentuk vektor koordinat, yakni suatu [[barisan]] <math>n</math>-[[Skalar (matematika)|skalar]] yang disebut [koordinat]. Untuk dua basis berbeda dari suatu ruang vektor, vektor koordinat yang menyatakan elemen <math>v</math> |
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Perubahan basis tersebut dihasilkan dari ''rumus perubahan-basis'' yang menyatakan koordinat-koordinat relatif pada satu basis dalam bentuk koordinat-koordinat relatif basis yang lainnya. Menggunakan [[Matriks (matematika)|matriks]], rumus ini dapat dituliskan sebagai |
Perubahan basis tersebut dihasilkan dari ''rumus perubahan-basis'' yang menyatakan koordinat-koordinat relatif pada satu basis dalam bentuk koordinat-koordinat relatif basis yang lainnya. Menggunakan [[Matriks (matematika)|matriks]], rumus ini dapat dituliskan sebagai |
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Artikel ini fokus membahas ruang vektor dimensi hingga. Akan tetapi, banyak prinsip yang disampaikan disini juga berlaku pada ruang vektor dimensi tak-hingga. |
Artikel ini fokus membahas ruang vektor dimensi hingga. Akan tetapi, banyak prinsip yang disampaikan disini juga berlaku pada ruang vektor dimensi tak-hingga. |
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== Contoh == |
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Misalkan kita ingin menentukan vektor koordinat pada [[Ruang Euklides|ruang vektor Euklides]] <math>\mathbb R^2,</math> yang dihasilkan dari rotasi sebesar <math>t.</math> Ruang vektor sebelum dirotasi memiliki [[Basis (aljabar linear)|basis standar]] <math>v_1= (1,0)</math> dan <math>v_2= (0,1);</math> sebut ini sebagai basis "lama". Setelah ruang vektor dirotasi, basis tersebut ikut berotasi, dan berubah menjadi <math>w_1=(\cos t, \sin t)</math> dan <math>w_2=(-\sin t, \cos t);</math> sebut ini sebagai basis "baru". Lalu, matriks perubahan basis akibat rotasi dapat dituliskan sebagai<math display="block">\begin{bmatrix} |
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So, the change-of-basis matrix is <math>\begin{bmatrix} |
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\cos t& -\sin t\\ |
\cos t& -\sin t\\ |
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\sin t& \cos t |
\sin t& \cos t |
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\end{bmatrix}.</math>Rumus perubahan basis menyatakan bahwa, jika <math display="inline">(y_1,\, y_2)</math> adalah koordinat baru hasil rotasi dari vektor koordinat <math>(x_1,\, x_2),</math> maka |
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\end{bmatrix}.</math> |
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The change-of-basis formula asserts that, if <math>y_1, y_2</math> are the new coordinates of a vector <math>(x_1, x_2),</math> then one has |
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: <math>\begin{bmatrix}x_1\\x_2\end{bmatrix}=\begin{bmatrix} |
: <math>\begin{bmatrix}x_1\\x_2\end{bmatrix}=\begin{bmatrix} |
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\cos t& -\sin t\\ |
\cos t& -\sin t\\ |
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\end{bmatrix}\,\begin{bmatrix}y_1\\y_2\end{bmatrix}.</math> |
\end{bmatrix}\,\begin{bmatrix}y_1\\y_2\end{bmatrix}.</math> |
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Sehingga, |
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That is, |
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: <math>x_1=y_1\cos t - y_2\sin t \qquad\text{ |
: <math>x_1=y_1\cos t - y_2\sin t \qquad\text{dan}\qquad x_2=y_1\sin t + y_2\cos t. </math> |
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Hubungan tersebut dapat dibuktikan dengan menunjukkan <math>(x_1,\, x_2)</math> dan <math display="inline">(y_1,\, y_2)</math> merujuk pada objek yang sama, |
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This may be verified by writing |
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: <math>\begin{align} |
: <math>\begin{align} |
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== Rumus perubahan basis == |
== Rumus perubahan basis == |
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Misalkan <math>B_\mathrm{lama}=(v_1,\, \ldots,\, v_n)</math> adalah basis dari suatu [[ruang vektor]] dimensi hingga {{mvar|V}} atas suatu [[Lapangan (matematika)|lapangan]] {{mvar|F}}.{{efn|Although a basis is generally defined as a set of vectors (for example, as a spanning set that is linearly independent), the [[tuple]] notation is convenient here, since the indexing by the first positive integers makes the basis an [[ordered basis]].}} Seorang dapat mendefinisikan <math>n</math> vektor baru <math>w_j;</math> (dengan <math>j=1,\,\dots,\, n</math>) berdasarkan koordinat vektor tersebut <math>a_{i,j}</math> atas <math>B_\mathrm{lama}\colon </math> |
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For {{math|1=''j'' = 1, ..., ''n''}}, one can define a vector {{math|''w''{{sub|''j''}}}} by its coordinates <math>a_{i,j}</math> over <math>B_\mathrm {old}\colon</math> |
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: <math>w_j=\sum_{i=1}^n a_{i,j}v_i.</math> |
: <math>w_j=\sum_{i=1}^n a_{i,j}v_i.</math> |
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Misalkan |
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Let |
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: <math>A=\left(a_{i,j}\right)_{i,j}</math> |
: <math>\mathbf{A}=\left(a_{i,j}\right)_{i,j}</math> |
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sebagai [[Matriks (matematika)|matriks]] yang kolom ke-{{mvar|j}}-nya dibentuk dari koordinat <math>w_j</math>. (Di bagian ini dan seterusnya, indeks {{mvar|i}} selalu digunakan untuk merujuk baris di <math>\mathbf{A}</math> dan <math>v_i,</math> sedangkan indeks {{mvar|j}} selalu digunakan untuk merujuk kolom di <math>\mathbf{A}</math> dan <math>w_j;</math> konvensi ini berguna untuk menghindari kesalahan dalam perhitungan.) |
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Barisan terurut <math>B_\mathrm {baru}=(w_1, \ldots, w_n) </math> disebut basis dari {{mvar|V}} jika dan hanya jika matriks <math>\mathbf{A}</math> [[Matriks terbalikkan|terbalikkan]], atau setara dengan itu, jika [[Determinan|determinannya]] tidak bernilai nol. Dalam kasus ini, <math>\mathbf{A}</math> disebut ''matriks perubahan basis'' dari basis <math>B_\mathrm{lama} </math> ke basis <math>B_\mathrm {baru}</math>. |
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(One could take the same summation index for the two sums, but choosing systematically the indexes {{mvar|i}} for the old basis and {{mvar|j}} for the new one makes clearer the formulas that follows, and helps avoiding errors in proofs and explicit computations.) |
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The ''change-of-basis formula'' expresses the coordinates over the old basis in term of the coordinates over the new basis. With above notation, it is |
The ''change-of-basis formula'' expresses the coordinates over the old basis in term of the coordinates over the new basis. With above notation, it is |
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{{linear algebra}} |
{{linear algebra}} |
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Revisi per 15 Maret 2024 02.53
Dalam aljabar linear, basis terurut memungkinkan setiap elemen pada sebarang ruang vektor berdimensi dinyatakan dalam bentuk vektor koordinat, yakni suatu barisan -skalar yang disebut [koordinat]. Untuk dua basis berbeda dari suatu ruang vektor, vektor koordinat yang menyatakan elemen atas basis pertama, umumnya berbeda dengan vektor koordinat yang menyatakan elemen yang sama, namun atas basis yang kedua. Perubahan basis adalah tindakan mengubah penyataan-pernyataan matematika pada suatu basis, ke pernyataan-pernyataan yang sepadan pada basis yang lain.[1][2][3]
Perubahan basis tersebut dihasilkan dari rumus perubahan-basis yang menyatakan koordinat-koordinat relatif pada satu basis dalam bentuk koordinat-koordinat relatif basis yang lainnya. Menggunakan matriks, rumus ini dapat dituliskan sebagai
dengan "lama" dan "baru" masing-masing merujuk pada basis lama dan basis baru, dan adalah vektor kolom dari koordinat vektor yang sama menurut kedua basis, dan adalah matriks perubahan-basis (juga disebut matriks transisi) yang kolom-kolomnya menyatakan koordinat vektor-vektor basis lama di basis baru.
Artikel ini fokus membahas ruang vektor dimensi hingga. Akan tetapi, banyak prinsip yang disampaikan disini juga berlaku pada ruang vektor dimensi tak-hingga.
Contoh
Misalkan kita ingin menentukan vektor koordinat pada ruang vektor Euklides yang dihasilkan dari rotasi sebesar Ruang vektor sebelum dirotasi memiliki basis standar dan sebut ini sebagai basis "lama". Setelah ruang vektor dirotasi, basis tersebut ikut berotasi, dan berubah menjadi dan sebut ini sebagai basis "baru". Lalu, matriks perubahan basis akibat rotasi dapat dituliskan sebagai
Sehingga,
Hubungan tersebut dapat dibuktikan dengan menunjukkan dan merujuk pada objek yang sama,
Rumus perubahan basis
Misalkan adalah basis dari suatu ruang vektor dimensi hingga V atas suatu lapangan F.[a] Seorang dapat mendefinisikan vektor baru (dengan ) berdasarkan koordinat vektor tersebut atas
Misalkan
sebagai matriks yang kolom ke-j-nya dibentuk dari koordinat . (Di bagian ini dan seterusnya, indeks i selalu digunakan untuk merujuk baris di dan sedangkan indeks j selalu digunakan untuk merujuk kolom di dan konvensi ini berguna untuk menghindari kesalahan dalam perhitungan.)
Barisan terurut disebut basis dari V jika dan hanya jika matriks terbalikkan, atau setara dengan itu, jika determinannya tidak bernilai nol. Dalam kasus ini, disebut matriks perubahan basis dari basis ke basis .
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Lebih lanjut, untuk sebarang vektor misalkan adalah koordinat atas , dan adalah koordinatnya atas , kita memiliki hubungan
The change-of-basis formula expresses the coordinates over the old basis in term of the coordinates over the new basis. With above notation, it is
In terms of matrices, the change of basis formula is
where and are the column vectors of the coordinates of z over and respectively.
Proof: Using the above definition of the change-of basis matrix, one has
As the change-of-basis formula results from the uniqueness of the decomposition of a vector over a basis.
In terms of linear maps
Normally, a matrix represents a linear map, and the product of a matrix and a column vector represents the function application of the corresponding linear map to the vector whose coordinates form the column vector. The change-of-basis formula is a specific case of this general principle, although this is not immediately clear from its definition and proof.
When one says that a matrix represents a linear map, one refers implicitly to bases of implied vector spaces, and to the fact that the choice of a basis induces an isomorphism between a vector space and Fn, where F is the field of scalars. When only one basis is considered for each vector space, it is worth to leave this isomorphism implicit, and to work up to an isomorphism. As several bases of the same vector space are considered here, a more accurate wording is required.
Let F be a field, the set of the n-tuples is a F-vector space whose addition and scalar multiplication are defined component-wise. Its standard basis is the basis that has as its ith element the tuple with all components equal to 0 except the ith that is 1.
A basis of a F-vector space V defines a linear isomorphism by
Conversely, such a linear isomorphism defines a basis, which is the image by of the standard basis of
Let be the "old basis" of a change of basis, and the associated isomorphism. Given a change-of basis matrix A, one could consider it the matrix of an endomorphism of Finally, define
(where denotes function composition), and
A straightforward verification shows that this definition of is the same as that of the preceding section.
Now, by composing the equation with on the left and on the right, one gets
It follows that, for one has
which is the change-of-basis formula expressed in terms of linear maps instead of coordinates.
Function defined on a vector space
A function that has a vector space as its domain is commonly specified as a multivariate function whose variables are the coordinates on some basis of the vector on which the function is applied.
When the basis is changed, the expression of the function is changed. This change can be computed by substituting the "old" coordinates for their expressions in terms of the "new" coordinates. More precisely, if f(x) is the expression of the function in terms of the old coordinates, and if x = Ay is the change-of-base formula, then f(Ay) is the expression of the same function in terms of the new coordinates.
The fact that the change-of-basis formula expresses the old coordinates in terms of the new one may seem unnatural, but appears as useful, as no matrix inversion is needed here.
As the change-of-basis formula involves only linear functions, many function properties are kept by a change of basis. This allows defining these properties as properties of functions of a variable vector that are not related to any specific basis. So, a function whose domain is a vector space or a subset of it is
- a linear function,
- a polynomial function,
- a continuous function,
- a differentiable function,
- a smooth function,
- an analytic function,
if the multivariate function that represents it on some basis—and thus on every basis—has the same property.
This is specially useful in the theory of manifolds, as this allows extending the concepts of continuous, differentiable, smooth and analytic functions to functions that are defined on a manifold.
Linear maps
Consider a linear map T: W → V from a vector space W of dimension n to a vector space V of dimension m. It is represented on "old" bases of V and W by a m×n matrix M. A change of bases is defined by an m×m change-of-basis matrix P for V, and an n×n change-of-basis matrix Q for W.
On the "new" bases, the matrix of T is
This is a straightforward consequence of the change-of-basis formula.
Endomorphisms
Endomorphisms, are linear maps from a vector space V to itself. For a change of basis, the formula of the preceding section applies, with the same change-of-basis matrix on both sides of the formula. That is, if M is the square matrix of an endomorphism of V over an "old" basis, and P is a change-of-basis matrix, then the matrix of the endomorphism on the "new" basis is
As every invertible matrix can be used as a change-of-basis matrix, this implies that two matrices are similar if and only if they represent the same endomorphism on two different bases.
Bilinear forms
A bilinear form on a vector space V over a field F is a function V × V → F which is linear in both arguments. That is, B : V × V → F is bilinear if the maps and are linear for every fixed
The matrix B of a bilinear form B on a basis (the "old" basis in what follows) is the matrix whose entry of the ith row and jth column is B(i, j). It follows that if v and w are the column vectors of the coordinates of two vectors v and w, one has
where denotes the transpose of the matrix v.
If P is a change of basis matrix, then a straightforward computation shows that the matrix of the bilinear form on the new basis is
A symmetric bilinear form is a bilinear form B such that for every v and w in V. It follows that the matrix of B on any basis is symmetric. This implies that the property of being a symmetric matrix must be kept by the above change-of-base formula. One can also check this by noting that the transpose of a matrix product is the product of the transposes computed in the reverse order. In particular,
and the two members of this equation equal if the matrix B is symmetric.
If the characteristic of the ground field F is not two, then for every symmetric bilinear form there is a basis for which the matrix is diagonal. Moreover, the resulting nonzero entries on the diagonal are defined up to the multiplication by a square. So, if the ground field is the field of the real numbers, these nonzero entries can be chosen to be either 1 or –1. Sylvester's law of inertia is a theorem that asserts that the numbers of 1 and of –1 depends only on the bilinear form, and not of the change of basis.
Symmetric bilinear forms over the reals are often encountered in geometry and physics, typically in the study of quadrics and of the inertia of a rigid body. In these cases, orthonormal bases are specially useful; this means that one generally prefer to restrict changes of basis to those that have an orthogonal change-of-base matrix, that is, a matrix such that Such matrices have the fundamental property that the change-of-base formula is the same for a symmetric bilinear form and the endomorphism that is represented by the same symmetric matrix. The Spectral theorem asserts that, given such a symmetric matrix, there is an orthogonal change of basis such that the resulting matrix (of both the bilinear form and the endomorphism) is a diagonal matrix with the eigenvalues of the initial matrix on the diagonal. It follows that, over the reals, if the matrix of an endomorphism is symmetric, then it is diagonalizable.
See also
- Active and passive transformation
- Covariance and contravariance of vectors
- Integral transform, the continuous analogue of change of basis.
Notes
- ^ Although a basis is generally defined as a set of vectors (for example, as a spanning set that is linearly independent), the tuple notation is convenient here, since the indexing by the first positive integers makes the basis an ordered basis.
References
- ^ (Anton 1987, hlm. 221–237)
- ^ (Beauregard & Fraleigh 1973, hlm. 240–243)
- ^ (Nering 1970, hlm. 50–52)
Bibliography
- Anton, Howard (1987), Elementary Linear Algebra (edisi ke-5th), New York: Wiley, ISBN 0-471-84819-0
- Beauregard, Raymond A.; Fraleigh, John B. (1973), A First Course In Linear Algebra: with Optional Introduction to Groups, Rings, and Fields, Boston: Houghton Mifflin Company, ISBN 0-395-14017-X
- Nering, Evar D. (1970), Linear Algebra and Matrix Theory (edisi ke-2nd), New York: Wiley, LCCN 76091646
External links
- MIT Linear Algebra Lecture on Change of Basis, from MIT OpenCourseWare
- Khan Academy Lecture on Change of Basis, from Khan Academy