Posts Tagged ‘scalar’
Friday, November 6th, 2009
Introduction to Scalars
Description
A detailed tutorial on what a scalar is. Step by step tutorial including several examples of scalars and how they relate to vectors for reference.
Overview
A scalar is a number that relates vectors on a vector space through the process of scalar multiplication. A scalar can be taken from any set of numbers, including rational, algebraic, real, and complex sets of numbers. The scalar is always a real number. A scalar is a single component, and things such as vectors, matrices, and tensors can be reduced to a scalar.
Tags: algebra, algebraic, complex, component, compound, matrices, matrix, number, quaternions, rational, real, scalar, single, space, tensor, vector
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Thursday, November 5th, 2009
Linear Subspaces Explained
Description
A detailed tutorial on linear subspaces and how to identify linear subspaces. Step by step tutorial including several examples of linear subspaces for reference.
Overview
A linear subspace is usually referred to as simply a subspace, when it needs to be distinguished from other types of subspaces. Linear subspaces are also sometimes referred to as vector subspaces. In mathematical terms, to identify a linear subspace, we say that K is a field (or a set, like of real numbers), and V is a vector space over K. Elements of V are vectors and elements of K are scalars. W is said to be a subset of V. If W is a vector space itself, with the same vector space operations as V, then it has a subspace of V.
Tags: algebra, element, field, k, linear, number, operations, real, scalar, set, space, subset, subspace, v, vector, W
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Thursday, November 5th, 2009
Introduction to Linear Transformations
Description
A detailed tutorial on linear transformations. Step by step tutorial including several examples of linear transformations for reference.
Overview
A linear transformation takes place between two vector spaces. For two vector spaces V and W, there is a map T such that T(v_1 + v_2) = T(v_1) + T(v_2) for any vectors v_1 and v_2 in V, and T(a v) = a T(v) for any scalar a. Examples of linear transformation are often obtained through matrix multiplication. Linear transformations can also be injective or surjective
Tags: algebra, injective, linear, map, matrix, multiplication, scalar, space, surjective, transformation, vector
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Thursday, November 5th, 2009
Transpose of a Matrix Explained
Description
A detailed tutorial on the transpose of a matrix. Step by step tutorial including several examples of the transpose of a matrix for reference.
Overview
When you transpose a matrix, it is simply a way of saying that you write the matrix in a different way – this creates a new matrix. There are three ways you can transpose a matrix. The first way is to write the rows of your matrix as columns instead. The second way is to write the columns of your matrix as rows instead. And the third way is to reflect your matrix by its main diagonal. All of these actions accomplish the same thing, so it does not matter which method you use. When people talk about transposing something, they are usually referring to matrices.
Tags: algebra, columns, diagonal, element, equivalent, main, matrices, matrix, method, reflect, rows, scalar, transpose
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Tuesday, October 27th, 2009
Definition of a Scalar Triple Product
Description
A detailed tutorial on scalar triple products. Step by step tutorial including several examples of scalar triple products for reference.
Overview
A scalar triple product is a way of applying other multiplication operators to three vectors. Quite often, the scalar triple product is denoted as (a, b, c). It can also be defined as (a b c) = a(b x c). The scalar triple product has three main properties. The first one is that the absolute value of the scalar triple product is the volume of the three dimensional figure that is formed by the three vectors. The second one is the scalar triple product is only zero if the three vectors are linearly independent. The three vectors must lie in the same plane for this to be true. The third one is that the scalar triple product is only positive if all three of the vectors are considered right-handed.
A simple way to write the scalar triple product is to line up the coordinates of the vectors in this form: 
This is the same as saying 
Tags: absolute, algebra, box, coordinates, figure, independent, linear, mixed, multiplication, operator, parallelpiped, positive, product, properties, right-handed, scalar, three-dimensional, triple, value, zero
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Tuesday, October 27th, 2009
The Cross Product of Vectors
Description
A detailed tutorial on the cross product of two vectors. Step by step tutorial including several examples of how to find the cross product for reference.
Overview
A cross product is very similar to a dot product. However, the result of a cross product is a vector, and the result of a dot product is a scalar. In mathematical terms, the cross product can be defined as 
. Theta represents the meausre of the angle between a and b, and n is a unit vector perpendicular to both a and b. The vector this forms is a right-handed system.
Tags: a, algebra, b, cross, dot, n!, outer, perpendicular, product, right-handed, rule, scalar, system, unit, vector
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Friday, October 23rd, 2009
Overview of the Dot Product
Description
A detailed tutorial of the dot product. Step by step tutorial including several examples of the dot product of a vector for reference.
Overview
The dot product of two vectors always ends up being a scalar. In mathematical terms, this is ![<span style="font-size: x-small;">\mathbf{a}\cdot\mathbf{b}=\left\|\mathbf{a}\right\|\left\|\mathbf{b}\right\|\cos\theta[</span>/latex]. In this case, theta is the measure of the angle between a and b. The definition of a dot product given geometrically is that a and b have a common starting point and that the length of a is multiplied by the component in b that points in the same direction as a. Algebraically, it can be said that [latex]<span style="font-size: x-small;">\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3.</span>](http://s.wordpress.com/latex.php?latex=%3Cspan%20style%3D%22font-size%3A%20x-small%3B%22%3E%5Cmathbf%7Ba%7D%5Ccdot%5Cmathbf%7Bb%7D%3D%5Cleft%5C%7C%5Cmathbf%7Ba%7D%5Cright%5C%7C%5Cleft%5C%7C%5Cmathbf%7Bb%7D%5Cright%5C%7C%5Ccos%5Ctheta%5B%3C%2Fspan%3E%2Flatex%5D.%20In%20this%20case%2C%20theta%20is%20the%20measure%20of%20the%20angle%20between%20a%20and%20b.%20The%20definition%20of%20a%20dot%20product%20given%20geometrically%20is%20that%20a%20and%20b%20have%20a%20common%20starting%20point%20and%20that%20the%20length%20of%20a%20is%20multiplied%20by%20the%20component%20in%20b%20that%20points%20in%20the%20same%20direction%20as%20a.%20Algebraically%2C%20it%20can%20be%20said%20that%20%5Blatex%5D%3Cspan%20style%3D%22font-size%3A%20x-small%3B%22%3E%5Cmathbf%7Ba%7D%20%5Ccdot%20%5Cmathbf%7Bb%7D%20%3D%20a_1%20b_1%20%2B%20a_2%20b_2%20%2B%20a_3%20b_3.%3C%2Fspan%3E&bg=ffffff&fg=000000&s=0 "<span style=\"font-size: x-small;\">\mathbf{a}\cdot\mathbf{b}=\left\|\mathbf{a}\right\|\left\|\mathbf{b}\right\|\cos\theta[</span>/latex]. In this case, theta is the measure of the angle between a and b. The definition of a dot product given geometrically is that a and b have a common starting point and that the length of a is multiplied by the component in b that points in the same direction as a. Algebraically, it can be said that [latex]<span style=\"font-size: x-small;\">\mathbf{a} \cdot \mathbf{b} = a_1 b_1 + a_2 b_2 + a_3 b_3.</span>")
Tags: algebra, algebraically, angle, common, component, cosine, direction, dot, geometrically, initial, inner, length, mulitplied, point, product, scalar, starting, vector
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Friday, October 23rd, 2009
How to Solve Vectors Using Scalar Multiplication
Description
A detailed tutorial on how to solve vectors using scalar multiplication. Step by step tutorial including several examples on scalar multiplication for reference.
Overview
Scalar multiplication is when you multiply, or re-scale, vectors by a real number. These real numbers are referred to as scalars, so that they can be distinguished from vectors. So, scalar multiplication is when you multiply a vector by a scalar. When you multiply a scalar and a vector, you will get another vector. Your resulting vector will be:
When a vector is multiplied by a scalar, the vector is getting stretched out by a factor of the scalar. If the scalar is negative, then the vector changes direction. A property of scalar multiplication is that it is distributive.
Tags: algebra, direction, distributive, flippied, multiplication, multiply, negatve, number, property, real, rescale, scalar, stretched, vector
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Friday, October 23rd, 2009
Introduction to Vector Space
Description
A detailed tutorial on vector space. Step by step tutorial including several examples of vector space and how to solve for vector space for reference.
Overview
Vector space is simply a structure in mathematics that is formed by a collection of vectors. Vector space can be calculated using vector addition and scalar multiplication. Vector space is very dependent on the definition of a vector. Some vectors are simply arrows on a fixed plane. But in general, the term vector just means there is an object for which two operations can be performed. The definition of vector space is defined in algebraic terms, as opposed to the geometric terms that can sometimes be applied.
Tags: addition, algebra, arrow, collection, definition, Geometry, multiplication, object, operation, plane, scalar, space, vector
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