Orthogonal vector projection and Components in Orthogonal Directions ....

In summary: Thank you!In summary, Peter is asking about the difference between Theorem 1.6 and the scalar projection. Theorem 1.6 states that a_v = a \cdot v / \| v \|^2, while the scalar projection is \| \text{ proj}_v a \| = a \cdot v / \| v \|. However, Peter's intuition is that the two formulae should be equal, and it appears that this is due to the fact that $v$ is not assumed to be a unit vector. If $v$ were a unit
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I am reading Miroslav Lovric's book: Vector Calculus ... and am currently focused n Section 1.3: The Dot Product ...

I need help with an apparently simple matter involving Theorem 1.6 and the section on the orthogonal vector projection and the scalar projection ...My question is as follows:

It seems to me that \(\displaystyle a_v\) in Lovric's Theorem 1.6 should be equal to the scalar projection, \(\displaystyle \| \text{ proj}_v a \|\) ... BUT ... they are not given as equal ...'

... indeed ...

\(\displaystyle a_v = a \cdot v / \| v \|^2\)

while

\(\displaystyle \| \text{ proj}_v a \| = a \cdot v / \| v \|\)BUT ... ... geometrically they seem to be referring to the same quantity ... what then accounts for the difference in the formulae ...?Hope someone can help ...

Peter========================================================================================
The above post refers to Theorem 1.6 so I am providing the text of the same ... as follows:
View attachment 8677
View attachment 8678
The above post also refers to the text on the orthogonal vector projection and the scalar projection ... so I am providing the text of the same ... as follows:

View attachment 8679
View attachment 8680
Hope someone can clarify the issue in the above post ...

Peter
 

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  • #2
Hi Peter,

Peter said:
It seems to me that \(\displaystyle a_v\) in Lovric's Theorem 1.6 should be equal to the scalar projection, \(\displaystyle \| \text{ proj}_v a \|\) ... BUT ... they are not given as equal ...'

... indeed ...

\(\displaystyle a_v = a \cdot v / \| v \|^2\)

while

\(\displaystyle \| \text{ proj}_v a \| = a \cdot v / \| v \|\)BUT ... ... geometrically they seem to be referring to the same quantity ... what then accounts for the difference in the formulae ...?

Your intuition is certainly on the right track, nicely done. The reason for the confusion stems from the fact that $v$ is not assumed to be a unit vector. If $v$ were a unit vector, then $a_{v}$ and $\|\text{Proj}_{v} a\|$ would, as you suspect, be equal.

Take a quick example. Suppose $a = (2, 2)$ and $v= (4, 0).$ Then $\|\text{Proj}_{v} a\| = 2.$ Now, by definition, $\text{Proj}_{v} a$ is the vector in the direction of $v$ with length $2$. Since $v$ itself has length $4$, this vector is not $2v$. Instead, we must scale $v$ down to a unit vector (i.e. $v\mapsto v/4$) and then multiply is by 2. This leads to $\text{Proj}_{v} a = 2\cdot\frac{v}{4}.$ Hence $2/4 = a_{v}\neq \|\text{Proj}_{v} a\| = 2.$

In short, the relationship between $a_{v}$ and $\|\text{Proj}_{v} a\|$ is given by $$a_{v}=\frac{\|\text{Proj}_{v} a\|}{\|v\|},$$ because $a_{v}$ accounts for the scaling "fudge factor" we must employ when $v$ is not a unit vector. From this we can see that $a_{v}=\|\text{Proj}_{v} a\|$ in the case when $v$ is a unit vector.

Edit. If it helps, the only information $v$ conveys to the function $\|\text{Proj}_{v} a\|$ is a direction relative to $a$. In other words, the length of $v$ is not an input variable that $\|\text{Proj}_{v} a\|$ utilizes, that job is left for $a_{v}$. This can be seen explicitly in the formula $$\|\text{Proj}_{v} a\| = \|a\|\cos\theta,$$ where $\theta$ is the angle between $a$ and $v$. Indeed, in the above example, $v$ can be replaced with $v(x) = (x,0)$ where $x>0$. Then $\|\text{Proj}_{v(x)} a\| = 2$ for all $x>0.$ However, $a_{v(x)} = 2/x$ for $x>0$.
 
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  • #3
GJA said:
Hi Peter,
Your intuition is certainly on the right track, nicely done. The reason for the confusion stems from the fact that $v$ is not assumed to be a unit vector. If $v$ were a unit vector, then $a_{v}$ and $\|\text{Proj}_{v} a\|$ would, as you suspect, be equal.

Take a quick example. Suppose $a = (2, 2)$ and $v= (4, 0).$ Then $\|\text{Proj}_{v} a\| = 2.$ Now, by definition, $\text{Proj}_{v} a$ is the vector in the direction of $v$ with length $2$. Since $v$ itself has length $4$, this vector is not $2v$. Instead, we must scale $v$ down to a unit vector (i.e. $v\mapsto v/4$) and then multiply is by 2. This leads to $\text{Proj}_{v} a = 2\cdot\frac{v}{4}.$ Hence $2/4 = a_{v}\neq \|\text{Proj}_{v} a\| = 2.$

In short, the relationship between $a_{v}$ and $\|\text{Proj}_{v} a\|$ is given by $$a_{v}=\frac{\|\text{Proj}_{v} a\|}{\|v\|},$$ because $a_{v}$ accounts for the scaling "fudge factor" we must employ when $v$ is not a unit vector. From this we can see that $a_{v}=\|\text{Proj}_{v} a\|$ in the case when $v$ is a unit vector.

Edit. If it helps, the only information $v$ conveys to the function $\|\text{Proj}_{v} a\|$ is a direction relative to $a$. In other words, the length of $v$ is not an input variable that $\|\text{Proj}_{v} a\|$ utilizes, that job is left for $a_{v}$. This can be seen explicitly in the formula $$\|\text{Proj}_{v} a\| = \|a\|\cos\theta,$$ where $\theta$ is the angle between $a$ and $v$. Indeed, in the above example, $v$ can be replaced with $v(x) = (x,0)$ where $x>0$. Then $\|\text{Proj}_{v(x)} a\| = 2$ for all $x>0.$ However, $a_{v(x)} = 2/x$ for $x>0$.
Well ... that's a VERY helpful explanation ...

Thanks so much for such a helpful post ...

Peter
 

1. What is orthogonal vector projection?

Orthogonal vector projection refers to the process of projecting a vector onto another vector that is perpendicular or "orthogonal" to the first vector. This creates a new vector that is a component of the original vector in the direction of the second vector.

2. How is orthogonal vector projection calculated?

The formula for calculating orthogonal vector projection is (⟨u, v⟩ / ||v||²) * v, where u is the original vector and v is the vector onto which u is being projected. This formula uses the dot product and the magnitude of the second vector to determine the magnitude and direction of the projected vector.

3. What are the applications of orthogonal vector projection?

Orthogonal vector projection has many applications in mathematics, physics, and engineering. It is commonly used in vector analysis, geometry, and mechanics to break down a vector into its component parts. It is also used in fields such as computer graphics and signal processing for tasks like image compression and noise reduction.

4. What are orthogonal components in orthogonal directions?

Orthogonal components in orthogonal directions refer to the individual parts of a vector that are perpendicular to each other. When a vector is projected onto another vector, the resulting components are orthogonal to each other, meaning they are at 90-degree angles. This allows for a simpler representation of the original vector and can be useful in solving equations and analyzing physical systems.

5. How does orthogonal vector projection differ from parallel vector projection?

Orthogonal vector projection is used to find the component of a vector in the direction of another vector, while parallel vector projection is used to find the component of a vector in the same direction as another vector. In other words, orthogonal projection creates a new vector that is perpendicular to the original vector, while parallel projection creates a new vector that is parallel to the original vector.

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