Kardi Teknomo
Kardi Teknomo Kardi Teknomo Kardi Teknomo
   
 
  Research
  Publications
  Tutorials
  Resume
  Personal
  Contact

Matrix Size & Validation
Vector Algebra
What is Vector?
Vector Norm
Unit Vector
Vector Addition
Vector Subtraction
Vector Scalar Multiple
Vector Multiplication
Vector Inner Product
Vector Outer Product
Vector Cross Product
Vector Triple Cross Product
Vector Triple Dot Product
Scalar Triple Product
Orthogonal & Orthonormal Vector
Cos Angle of Vectors
Scalar and Vector Projection
Matrix Algebra
What is a matrix?
Special Matrices
Matrix One
Null Matrix
Matrix Diagonal Is Diagonal Matrix?
Identity Matrix
Matrix Determinant
Matrix Sum
Matrix Trace
Matrix Basic Operation
Is Equal Matrix?
Matrix Transpose
Matrix Addition
Matrix Subtraction
Matrix Multiplication
Matrix Scalar Multiple
Hadamard Product
Horizontal Concatenation
Vertical Concatenation
Elementary Row Operations
Matrix RREF
Finding inverse using RREF (Gauss-Jordan)
Finding Matrix Rank using RREF
Matrix Inverse
Is Singular Matrix?
Linear Transformation
Matrix Generalized Inverse
Solving System of Linear Equations
Linear combination, Span & Basis Vector
Linearly Dependent & Linearly Independent
Change of basis
Matrix Rank
Matrix Range
Matrix Nullity & Null Space
Eigen System
Matrix Eigen Value & Eigen Vector
Symmetric Matrix
Matrix Eigen Value & Eigen Vector for Symmetric Matrix
Similarity Transformation and Matrix Diagonalization
Matrix Power
Orthogonal Matrix
Spectral Decomposition
Singular Value Decomposition
Resources on Linear Algebra

Cosine Angle of Vectors

By Kardi Teknomo, PhD.
LinearAlgebra

<Next | Previous | Index>

Cosine angle between two vectors is equal to their dot product divided by the product of their normsVector Cos Angle.

Example:
Suppose we have Vector Cos AngleandVector Cos Angle, the vector inner product is
Vector Cos Angle
Their norms are Vector Cos AngleandVector Cos Angle.
Therefore, the cosine angle is Vector Cos Angleand the angle isVector Cos Angle.

The interactive program below produces cosine angle between two vectors of the same dimension and also specify the angle in both radians and degrees. Random Example button will generate random vectors at the right format.

vector x vector y

Properties

Some important properties of related to cosine angle are

  • Two vectors are orthogonal if their dot product is zeroVector Cos Angle, which means the cosine angle is zeroVector Cos Angle
  • Two vectors are parallel if the absolute value of their dot product is equal to the product of their normsVector Cos Angle, which means the absolute cosine angle is oneVector Cos Angle.
  • Two vectors are in the same direction if their dot product is equal to the product of their normsVector Cos Angle, which mean the cosine angle is exactly oneVector Cos Angle.
  • Since the value of Cosine is between -1 and +1, the absolute value of vector dot product is always less than or equal to the product of their normsVector Cos Angle. This is called Cauchy-Schwartz inequality.

<Next | Previous | Index>

Rate this tutorial or give your comments about this tutorial

This tutorial is copyrighted.

Preferable reference for this tutorial is

Teknomo, Kardi (2011) Linear Algebra tutorial. http:\\people.revoledu.com\kardi\ tutorial\LinearAlgebra\

 

 
© 2007 Kardi Teknomo. All Rights Reserved.
Designed by CNV Media