单位矩阵属性(I ^ k = I)| 使用Python的线性代数
Prerequisites:
先決條件:
numpy.matmul( ) matrix multiplication
numpy.matmul()矩陣乘法
Identity matrix
身份矩陣
In linear algebra, the identity matrix, of size n is the n × n square matrix with ones on the main diagonal and zeros elsewhere. It is denoted by I. Also known as the unit matrix because its determinant value is 1 irrespective of size. This is the key feature of an Identity matrix and it plays an important role in Linear Algebra.
在線性代數中,大小為n的單位矩陣是n×n方陣,主對角線上為1,其他地方為零。 用I表示。 也稱為單位矩陣,因為其行列式值為1,與大小無關。 這是恒等矩陣的關鍵特征,在線性代數中起著重要的作用。
The identity matrix has the property that, Multiplying k identity matrices gives an identity matrix (Ik = I).
單位矩陣具有以下性質:將k個單位矩陣相乘得到一個單位矩陣( I k = I )。
身份矩陣屬性的Python代碼( IK = I) (Python code for identity matrix property (Ik = I))
# Linear Algebra Learning Sequence # Identity Matrix Property (I^k = I)import numpy as np# identity Matrix I = np.eye(4) print("\n---I(4x4)---\n", I)k = 14 Ik = Ifor i in range(14):Ik = I*Ikprint('\n\n--- I^k ----\n', Ik)Output:
輸出:
---I(4x4)---[[1. 0. 0. 0.][0. 1. 0. 0.][0. 0. 1. 0.][0. 0. 0. 1.]]--- I^k ----[[1. 0. 0. 0.][0. 1. 0. 0.][0. 0. 1. 0.][0. 0. 0. 1.]]翻譯自: https://www.includehelp.com/python/identity-matrix-property-i-k-i.aspx
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