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{{expert-subject|Mathematics|ex2=Systems|date=February 2010}}
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By the term '''multidimensional systems''' or '''m-D systems''' we mean the branch of (mathematical) [[systems theory]] where not only one [[Variable (mathematics)|variable]] exists (like time), but several independent variables.  
Important problems like [[factorization]] and [[Stability theory|stability]] have recently attracted the interest of many researchers and practitioners.


The reason is that the factorization and stability of m-D systems (''m''&nbsp;>&nbsp;1) is not a straightforward extension of the factorization and stability of 1-D systems because for example the [[fundamental theorem of algebra]] does not exist in the [[Ring (mathematics)|ring]] of m-D (''m''&nbsp;>&nbsp;1) [[polynomials]].
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== Applications ==
Multidimensional systems or m-D systems are the necessary mathematical background for modern [[digital image processing]] with many applications in [[biomedicine]], [[X-ray technology]] and [[satellite communications]]<ref>{{cite book|editor-last=Bose|editor-first=N.K.|title=Multidimensional Systems Theory, Progress, Directions and Open Problems in Multidimensional Systems|publisher=D. Reidel Publishing Company|location=Dordrecht, Holland|year=1985}}</ref>
.<ref>{{cite book|editor-last=Bose|editor-first=N.K.|title=Multidimensional Systems: Theory and Applications|publisher=IEEE Press|year=1979}}</ref>
There are also some studies combining m-D systems with [[partial differential equations]] (PDEs).
 
== Linear Multidimensional State-Space Model ==
 
A state-space model is a representation of a system in which the effect of all "prior" input values is contained by a state vector. In the case of an m-d system, each dimension has a state vector that contains the effect of prior inputs relative to that dimension. The collection of all such dimensional state vectors at a point constitutes the total state vector at the point.
 
Consider a uniform discrete space linear two-dimensional (2d) system that is space invariant and causal. It can be represented in matrix-vector form as follows:<ref name=Tzafestas>{{cite book|editor-last=Tzafestas|editor-first=S.G.|title=Multidimensional Systems: Techniques and Applications|publisher=Marcel-Dekker|location=New York|year=1986}}</ref><ref name=Kaczorek>{{cite book|last=Kaczorek|first=T.|title=Two-Dimensional Linear Systems|publisher=Springer-Verlag|series=Lecture Notes Contr. and Inform. Sciences|volume=68|year=1985}}</ref>
 
Represent the input vector at each point <math>(i,j)</math> by <math>u(i,j)</math>, the output vector by <math>y(i,j)</math> the horizontal state vector by <math>R(i,j)</math> and the vertical state vector by <math>S(i,j)</math>. Then the operation at each point is defined by:
 
<math>
\begin{array}{rcl}
R(i+1,j) = A_1R(i,j) + A_2S(i,j) + B_1u(i,j) \\
S(i,j+1) = A_3R(i,j) + A_4S(i,j) + B_2u(i,j) \\
y(i,j) = C_1R(i,j) +C_2S(i,j) + Du(i,j)
\end{array}
</math>
 
where <math>A_1, A_2, A_3, A_4, B_1, B_2, C_1, C_2</math> and <math>D</math> are matrices of appropriate dimensions.
 
These equations can be written more compactly by combining the matrices:
 
<math>
\begin{bmatrix}
R(i+1,j) \\
S(i,j+1) \\
y(i,j) \\
\end{bmatrix}
=
\begin{bmatrix}
A_1 & A_2 & B_1 \\
A_3 & A_4 & B_2 \\
C_1 & C_2 & D \\
\end{bmatrix}
\begin{bmatrix}
R(i,j) \\
S(i,j) \\
u(i,j) \\
\end{bmatrix}
</math>
 
Given input vectors <math>u(i,j)</math> at each point and initial state values, the value of each output vector can be computed by recursively performing the operation above.
 
== Multidimensional Transfer Function ==
 
A discrete linear two-dimensional system is often described by a partial difference equation in the form:
<math>\sum_{p,q=0,0}^{m,n}a_{p,q}y(i-p,j-q) = \sum_{p,q=0,0}^{m,n}b_{p,q}x(i-p,j-q)</math>
 
where <math>x(i,j)</math> is the input and <math>y(i,j)</math> is the output at point <math>(i,j)</math> and <math>a_{p,q}</math> and <math>b_{p,q}</math> are constant coefficients.
 
To derive a transfer function for the system the 2d '''Z'''-transform is applied to both sides of the equation above.
 
<math>\sum_{p,q=0,0}^{m,n}a_{p,q}z_1^{-p}z_2^{-q}Y(z_1,z_2) = \sum_{p,q=0,0}^{m,n}b_{p,q}z_1^{-p}z_2^{-q}X(z_1,z_2)</math>
 
Transposing yields the transfer function <math>T(z_1,z_2)</math>:
 
<math>T(z_1,z_2) = {Y(z_1,z_2) \over X(z_1,z_2)} = {\sum_{p,q=0,0}^{m,n}b_{p,q}z_1^{-p}z_2^{-q} \over \sum_{p,q=0,0}^{m,n}a_{p,q}z_1^{-p}z_2^{-q}}</math>
 
So given any pattern of input values, the 2d '''Z'''-transform of the pattern is computed and then multiplied by the transfer function <math>T(z_1,z_2)</math> to produce the '''Z'''-transform of the system output.
 
== Realization of a 2d Transfer Function ==
 
Often an image processing or other md computational task is described by a transfer function that has certain filtering properties, but it is desired to convert it to state-space form for more direct computation. Such conversion is referred to as realization of the transfer function.
 
Consider a 2d linear spatially invariant causal system having an input-output relationship described by:
 
<math>Y(z_1,z_2) = {\sum_{p,q=0,0}^{m,n}b_{p,q}z_1^{-p}z_2^{-q} \over \sum_{i,j=0,0}^{m,n}a_{p,q}z_1^{-p}z_2^{-q}}X(z_1,z_2)</math>
 
Two cases are individually considered 1) the bottom summation is simply the constant '''1'''  2)the top summation is simply a constant <math>k</math>. Case 1 is often called the “all-zero” or “finite impulse response” case, whereas case 2 is called the “all-pole” or “infinite impulse response” case. The general situation can be implemented as a cascade of the two individual cases. The solution for case 1 is considerably simpler than case 2 and is shown below.
 
=== Case 1 - all zero or finite impulse response<ref name=Tzafestas /><ref name=Kaczorek /> ===
 
<math>Y(z_1,z_2) = \sum_{p,q=0,0}^{m,n}b_{p,q}z_1^{-p}z_2^{-q}X(z_1,z_2)</math>
 
The state-space vectors will have the following dimensions:
 
<math>R (1 \times m), S (1 \times n), x (1 \times 1)</math> and <math>y (1 \times 1)</math>
 
Each term in the summation involves a negative (or zero) power of <math>z_1</math> and of <math>z_2</math> which correspond to a delay (or shift) along the respective dimension of the input <math>x(i,j)</math>. This delay can be effected by placing <math>1</math>’s along the super diagonal in the <math>A_1</math>. and <math>A_4</math> matrices and the multiplying coefficients <math>b_{i,j}</math> in the proper positions in the <math>A_2</math>. The value <math>b_{0,0}</math> is placed in the upper position of the <math>B_1</math> matrix, which will multiply the input <math>x(i,j)</math> and add it to the first component of the <math>R_{i,j}</math> vector. Also, a value of <math> b_{0,0}</math> is placed in the <math>D</math> matrix which will multiply the input <math>x(i,j)</math> and add it to the output <math>y</math>.
The matrices then appear as follows:
 
<math>A_1 = \begin{bmatrix}0 & 0 & 0 & \cdots & 0 & 0 \\
1 & 0 & 0 & \cdots & 0 & 0 \\
0 & 1 & 0 & \cdots & 0 & 0 \\
\vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\
0 & 0 & 0 & \cdots & 0 & 0 \\
0 & 0 & 0 & \cdots & 1 & 0 \\
\end{bmatrix}</math>
 
<math>A_2 = \begin{bmatrix}0 & 0 & 0 & \cdots & 0 & 0 \\
0 & 0 & 0 & \cdots & 0 & 0 \\
0 & 0 & 0 & \cdots & 0 & 0 \\
\vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\
0 & 0 & 0 & \cdots & 0 & 0 \\
0 & 0 & 0 & \cdots & 0 & 0 \\
\end{bmatrix}</math>
 
<math>A_3 = \begin{bmatrix}
b_{1,n} & b_{2,n} & b_{3,n} & \cdots & b_{m-1,n} & b_{m,n} \\
b_{1,n-1} & b_{2,n-1} & b_{3,n-1} & \cdots & b_{m-1, n-1} & b_{m,n-1} \\
b_{1,n-2} & b_{2,n-2} & b_{3,n-2} & \cdots & b_{m-1, n-2} & b_{m,n-2} \\
\vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\
b_{1,2} & b_{2,2} & b_{3,2} & \cdots & b_{m-1,2} & b_{m,2} \\
b_{1,1} & b_{2,1} & b_{3,1} & \cdots & b_{m-1,1} & b_{m,1} \\
\end{bmatrix}</math>
 
<math>A_4 = \begin{bmatrix}0 & 0 & 0 & \cdots & 0 & 0 \\
1 & 0 & 0 & \cdots & 0 & 0 \\
0 & 1 & 0 & \cdots & 0 & 0 \\
\vdots & \vdots & \vdots & \vdots & \vdots & \vdots \\
0 & 0 & 0 & \cdots & 0 & 0 \\
0 & 0 & 0 & \cdots & 1 & 0 \\
\end{bmatrix}</math>
 
<math>B_1 = \begin{bmatrix}1 \\
0 \\
0\\
0\\
\vdots \\
0 \\
0 \\
\end{bmatrix}</math>
 
<math>B_2 = \begin{bmatrix}
b_{0,n} \\
b_{0,n-1} \\
b_{0,n-2} \\
\vdots \\
b_{0,2} \\
b_{0,1} \\
\end{bmatrix}</math>
 
<math>C_1 = \begin{bmatrix} b_{1,0} & b_{2,0} & b_{3,0} & \cdots & b_{m-1,0} & b_{m,0} \\
\end{bmatrix}</math>
 
<math>C_2 = \begin{bmatrix}0 & 0 & 0 & \cdots & 0 & 1 \\
\end{bmatrix}</math>
 
<math>D = \begin{bmatrix}b_{0,0} \end{bmatrix}</math>
 
== References ==
{{reflist}}
 
[[Category:Digital imaging]]
[[Category:Partial differential equations]]
[[Category:Stability theory]]

Latest revision as of 04:07, 16 December 2014

This gives them much more shock absorption than hard-tail mountain bikes and allows them to be ridden on some of the rougher terrains you may wish to try with your mountain bike. Macaskill is tackling the Cuillin Ridge in Scotland, not far from where this two-wheeling genius hails from on the Isle of Skye. These bikes are very popular with the sport of mountain biking. It's really cool to ride on a bike that is not just efficient but also very trendy. Certain Haro mountain bike models worth mentioning right here consist of BMX Black trail X1, BMX Haro Partial 16, BMX Haro FIC and so forth.

Once you are sure that this is what you want to do, it is now time for you to decide on the bike. By just taking a few minutes to make sure your bike is well-tuned before you set out, you can keep from spending hours on issues later. Each rider has lanes, but some others only have a single lane. Should you have just about any queries regarding where in addition to tips on how to use Choosing the right ride for you mountain bike sizing., you'll be able to call us at the internet site. Now please continue on additionally so you can get added info for this topic. It is a choice you make that determines the level of commitment you have.

Some also use the liner as a size aid, for example BMX helmets can come as one-size, with optional liner kits to change the helmets size. Mulberry Gap Mountain Bike Get-A-Way is located 12 miles from downtown Ellijay in the Chattahoochee National Forest with some of the best single track mountain bike trails including the Georgia Pinhoti trail system. But when it comes to mountain biking it is not enough that you own a bike. Another way to classify brakes is by mounting style. These are stable forks whose weights are directly in proportion to their durability.

It works great unless you have some physical issue. The more bikes you can test drive, you better you'll understand what works and what doesn't. But older children may have more adventurous tastes, and want for toys that are - well, still miniatures, but are flashier, more expensive, and more functional. Instead of having fun playing with him (like a child with a favorite playmate), they evaluate his potential as a father. But that wasn't the bad part 'cause, see, those two almost invisible grey hairs were only a distraction from the real culprit.

A small spot of rust can quickly grow and cause weak areas on your frame. The correct quill stems are sized down with the inside diameter of the fork's steer tube. This may be related to a muscle imbalance between opposing muscle groups in the leg and is commonly related to excessive foot pronation (collapsing arch). It is also easier to hold the handlebars if they are covered with rubber than exposed handlebars, especially if it is too hot because steel absorbs heat and makes it difficult for you to hold. If they connect with the wrong part, it could cause you to stop on a dime, which will most likely result in you taking a tumble over the handlebars.