infinite matrix

(noun)

Related Terms

  • empty matrix
  • square matrix
  • column vectors
  • row vectors
  • matrix
  • elements

Examples of infinite matrix in the following topics:

  • Matrix Equations

    • It is possible to solve this system using the elimination or substitution method, but it is also possible to do it with a matrix operation.
    • Solving a system of linear equations using the inverse of a matrix requires the definition of two new matrices: $X$ is the matrix representing the variables of the system, and $B$ is the matrix representing the constants.
    • Using matrix multiplication, we may define a system of equations with the same number of equations as variables as:
    • To solve a system of linear equations using an inverse matrix, let $A$ be the coefficient matrix, let $X$ be the variable matrix, and let $B$ be the constant matrix.
    • If the coefficient matrix is not invertible, the system could be inconsistent and have no solution, or be dependent and have infinitely many solutions.
  • Finding Limits Algebraically

    • $\displaystyle{\begin{matrix} \lim\limits_{x \to p} & (f(x) + g(x)) & = & \lim\limits_{x \to p} f(x) + \lim\limits_{x \to p} g(x) \\ \lim\limits_{x \to p} & (f(x) - g(x)) & = & \lim\limits_{x \to p} f(x) - \lim\limits_{x \to p} g(x) \\ \lim\limits_{x \to p} & (f(x)\cdot g(x)) & = & \lim\limits_{x \to p} f(x) \cdot \lim\limits_{x \to p} g(x) \\ \lim\limits_{x \to p} & \left ( \frac{f(x)}{g(x)} \right ) & = & \frac{\lim\limits_{x \to p} f(x)} {\lim\limits_{x \to p} g(x)} \end{matrix}}$
    • These rules are also valid for one-sided limits, for the case $p = \pm$, and also for infinite limits using the following rules:
    • $\displaystyle{\begin{matrix} &q + \infty &=& \infty \text{ for } q \neq - \infty \\ &q \cdot \infty &=& \infty \text{ if } q > 0 \\ &q \cdot \infty &=& -\infty \text{ if } q < 0 \\& \frac{q}{\infty} &=& 0 \text{ if } q \neq \pm \infty \end{matrix}}$
  • Solving Systems of Equations in Three Variables

    • Solve a system of equations in three variables, differentiating between systems that have no solutions and ones that have infinitely many solutions
  • Inconsistent and Dependent Systems in Three Variables

    • Dependent systems have an infinite number of solutions.
    • An infinite number of solutions can result from several situations.
    • $\left\{\begin{matrix} \begin {aligned} 2x + y - 3z &= 0 \\ 4x + 2y - 6z &= 0 \\ x - y + z &= 0 \end {aligned} \end{matrix} \right.$
    • $\left\{\begin{matrix} \begin {aligned} x - 3y + z &= 4\\ -x + 2y - 5z &= 3 \\ 5x - 13y + 13z &= 8 \end {aligned} \end{matrix} \right.$
    • $\left\{\begin{matrix} \begin {aligned} -y - 4z &= 7 \\ 2y + 8z &= -12 \end {aligned} \end {matrix} \right.$
  • Inconsistent and Dependent Systems

    • $egin{matrix} x-2y &= &-1\ 3x+5y &= &8\ 4x+3y &=& 7 nd{matrix} $
    • $egin{matrix} x+y &= &1\ 2x+y &= &1\ 3x+2y &=& 3 nd{matrix} $
  • Matrix Inverses

    • A left inverse of a matrix $A\in \mathbf{R}^{n \times m}$ is defined to be a matrix $B$ such that
    • You can readily verify that any matrix of the form
    • But there are infinitely many other left inverses.
    • Here you can readily verify that any matrix of the form
    • So there is an infinite set of solutions $x_3$ .
  • Applications and Mathematical Models

    • $\left[\begin{matrix} 7x & =&7z\\ 8x+y & =&5z+2w\\ y & = & 3z\\ 3y &= & 6z+w \end{matrix} \right].$
    • $\left[ {\begin{matrix} 8z+y & =&5z+2w\\ y & = & 3z\\ 3y &= & 6z+w \end{matrix} } \right]$
    • Since these two equations are equivalent, we have an infinite number of solutions.
    • So we'll simply choose one solution, and know that there are infinitely many multiples of this one solution.
  • Superposition and orthogonal projection

    • where $X$ is the matrix whose columns are the $\mathbf{x}_i$$\mathbf{c}$ vectors and $\mathbf{c}$ is the vector of unknown expansion coefficients.
    • As you well know, matrix equation has a unique solution $\mathbf{c}$ if and only if the $\mathbf{x}_i$ are linearly independent.
    • We have emphasized throughout this course that functions are vectors too, they just happen to live in an infinite dimensional vector space (for instance, the space of square integrable functions).
    • In general, the sum will require an infinite number of coefficients $c_i$ , since a function has an infinite amount of information.
    • So, let us define a dot (or inner) product for functions on an interval $[-l,l]$ (this could be an infinite interval)
  • More on coupled spring/mass lattices

    • First let's look at the $2\times 2$ matrix formulation of the problem:
    • (For a 2 by 2 matrix $\left[ \begin{array}{cc} a & b \\ c & d \end{array} \right]$ the determinant is . ) In our case the matrix whose determinant must be zero is which equals
    • Remember, $\omega_0 ^2$ is fixed, as are the elements of the matrix $T$ .
    • This is a rather unusual thing for a matrix to do.
    • The only way to make the high frequency modes be purely sinusoidal is to let there be a continuously infinite number of springs and masses.
  • Summing an Infinite Series

    • Infinite sequences and series can either converge or diverge.
    • If the limit of is infinite or does not exist, the series is said to diverge.
    • An easy way that an infinite series can converge is if all the $a_{n}$ are zero for sufficiently large $n$s.
    • Such a series can be identified with a finite sum, so it is only infinite in a trivial sense.
    • An infinite sequence of real numbers shown in blue dots.
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