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In MATHEMATICS , a ((((( linear DIFFERENTIAL EQUATION ))))) is of the form ..
{{Petició de traducció|en|Linear differential equation|Usuari:Amical-bot/Matemàtiques/en|--[[Usuari:Gomà|Gomà]] ([[Usuari Discussió:Gomà|disc.]]) 11:11, 14 març 2010 (CET)}}
..
: <math> Ly = f \ ,</math> ..
..
where the DIFFERENTIAL OPERATOR (( L )) is a LINEAR OPERATOR , (( y )) is the unknown function (such as a function of time y(t)) , and the RIGHT HAND SIDE &fnof ; is a given function of the same nature as (( y )) (called the ((((( source term )))))). For a function dependent on time we may write the equation more expressively as ..
..
: <math> L y(t) = f(t) \ ,</math> ..
and , even more precisely by bracketing ..
: <math> L [y(t)] = f(t) \ ,</math> ..
..
The linear operator (( L )) may be considered to be of the form <ref>. Gershenfeld 1999 , p.9 </ref>. ..
..
: <math>L_n(y) \equiv \frac{d^n y}{dt^n} + A_1(t)\frac{d^{n-1}y}{dt^{n-1}} + \cdots + ..
A_{n-1}(t)\frac{dy}{dt} + A_n(t)y \ ,</math> ..
..
The linearity condition on (( L )) rules out operations such as taking the square of the DERIVATIVE of (( y )) ; but permits , for example , taking the second derivative of (( y )) . ..
It is convenient to rewrite this equation in an operator form ..
..
: <math> L_n(y) \equiv \left[\ ,D^n + A_{1}(t)D^{n-1} + \cdots + A_{n-1}(t) D + A_n(t)\right] y</math> ..
..
where (( D )) is the differential operator (( d/dt )) (i.e. (( Dy = y' )) , (( D )) <sup>2</sup>(( y = y" ,... )) ) , and the (( A<sub>n</sub> )) are given functions. ..
<!-- and the source term is considered to be a function of time &fnof ;(((( t )))) .--> ..
..
Such an equation is said to have ((((( order ))))) (( n )) , the index of the highest derivative of (( y )) that is involved. <!-- (Assuming a possibly existing coefficient (( a<sub>n</sub> )) of this derivative to be non zero , it is eliminated by dividing through it. In case it can become zero , different cases must be considered separately for the analysis of the equation.)--> ..
..
A typical simple example is the linear differential equation used to model radioactive decay <ref>. Robinson 2004 , p.5 </ref>. . Let N(t) denote the number of radioactive atoms in some sample of material (such as a portion of the cloth of the SHROUD OF TURIN <ref>. Robinson 2004 , p.7 </ref>. ) at time t. Then for some constant k > 0 , ..
the number of radioactive atoms which decay can be modelled by ..
: <math> \frac{dN}{dt} = -k N\ ,</math> ..
..
..
If (( y )) is assumed to be a function of only one variable , one speaks about an ORDINARY DIFFERENTIAL EQUATION , else the derivatives and their coefficients must be understood as (CONTRACTED) vectors , matrices or TENSORS of higher rank , and we have a (linear) PARTIAL DIFFERENTIAL EQUATION. ..
..
The case where &fnof ; = 0 is called a ((((( homogeneous equation ))))) and its solutions are called ((((( complementary functions ))))). It is particularly important to the solution of the general case , since any complementary function can be added to a solution of the inhomogeneous equation to give another solution (by a method traditionally called (( particular integral and complementary function )) ). When the (( A<sub>i</sub> )) are numbers , the equation is said to have (( CONSTANT COEFFICIENTS )) . ..
..
(==) Homogeneous equations with constant coefficients (==) ..
..
The first method of solving linear ordinary differential equations with constant coefficients is due to EULER , who realized that solutions have the form <math>e^{z x}</math> , for possibly-complex values of <math>z</math>. The exponential function is one of the few functions that keep its shape even after differentiation. In order for the sum of multiple derivatives of a function to sum up to zero , the derivatives must cancel each other out and the only way for them to do so is for the derivatives to have the same form as the initial function. Thus , to solve ..
..
: <math>y^{(n)} + A_{1}y^{(n-1)} + \cdots + A_{n}y = 0</math> ..
..
we set <math>y=e^{z x}</math> , leading to ..
..
: <math>z^n e^{zx} + A_1 z^{n-1} e^{zx} + \cdots + A_n e^{zx} = 0.</math> ..
..
Division by (( e )) <sup>&nbsp ;(( zx )) </sup> gives the (( n )) th-order polynomial ..
..
: <math>F(z) = z^{n} + A_{1}z^{n-1} + \cdots + A_n = 0.\ ,</math> ..
..
This algebraic equation (( F )) (((( z )))) = 0 , is the ((((( characteristic equation ))))) considered later by MONGE and CAUCHY. ..
..
Formally , the terms ..
..
: <math>y^{(k)}\quad\quad(k = 1 , 2 , \dots , n).</math> ..
..
of the original differential equation are replaced by (( z )) <sup>(( k )) </sup>. ROOT-FINDING ALGORITHM#FINDING ROOTS OF POLYNOMIALS .3. SOLVING .3. Solving]] the polynomial gives (( n )) values of (( z )) , (( z )) <sub>1</sub> ,&nbsp ;... ,&nbsp ;(( z )) <sub>(( n )) </sub>. Substitution of any of those values for (( z )) into (( e )) <sup>&nbsp ;(( zx )) </sup> gives a solution (( e )) <sup>&nbsp ;(( z )) <sub>(( i )) </sub>(( x )) </sup>. Since homogeneous linear differential equations obey the SUPERPOSITION PRINCIPLE , any LINEAR COMBINATION of these functions also satisfies the differential equation. ..
..
When these roots are all DISTINCT , we have (( n )) distinct solutions to the differential equation. It can be shown that these are LINEARLY INDEPENDENT , by applying the VANDERMONDE DETERMINANT , and together they form a BASIS of the space of all solutions of the differential equation. ..
..
{{ ExampleSidebar .3. 35 % .3. ..
: <math>y((((( '-2y )))))+2y''-2y'+y=0 \ ,</math> ..
has the characteristic equation ..
..
: <math>z^4-2z^3+2z^2-2z+1=0. \ ,</math> ..
..
This has zeroes , (( i )) , &minus ;(( i )) , and 1 (multiplicity 2). The solution basis is then ..
..
: <math>e^{ix} ,\ , e^{-ix} ,\ , e^x ,\ , xe^x \ ,.</math> ..
..
This corresponds to the real-valued solution basis ..
..
: <math>\cos x ,\ , \sin x ,\ , e^x ,\ , xe^x \ ,.</math>}} ..
..
The preceding gave a solution for the case when all zeros are distinct , that is , each has MULTIPLICITY#MULTIPLICITY OF A ROOT OF A POLYNOMIAL .3. MULTIPLICITY .3. multiplicity]] 1. For the general case , if (( z )) is a (possibly complex) ZERO (or root) of (( F )) (((( z )))) having multiplicity (( m )) , then , for <math>k\in\{0 ,1 ,\dots ,m-1\} \ ,</math> , <math>y=x^ke^{zx} \ ,</math> is a solution of the Ode. Applying this to all roots gives a collection of (( n )) distinct and linearly independent functions , where (( n )) is the degree of (( F )) (((( z )))) . As before , these functions make up a basis of the solution space. ..
..
If the coefficients (( A<sub>i</sub> )) of the differential equation are real , then real-valued solutions are generally preferable. Since non-real roots (( z )) then come in CONJUGATE pairs , so do their corresponding basis functions {{ nowrap .3. (( x )) <sup>(( k )) </sup>e<sup>(( zx )) </sup>}} , and the desired result is obtained by replacing each pair with their real-valued LINEAR COMBINATIONS RE(((( Y )))) and IM(((( Y )))) , where (( y )) is one of the pair. ..
..
A case that involves complex roots can be solved with the aid of EULER'S FORMULA. ..
..
(===) Examples (===) ..
..
Given <math>y(( -4y'+5y=0 \ ,</math>. The characteristic equation is <math>z^2-4z+5=0 \ ,</math> which has zeroes 2+ )) i(( and 2&#8722; )) i(( . Thus the solution basis <math>\{y_1 ,y_2\}</math> is <math>\{e^{(2+i)x} ,e^{(2-i)x}\} \ ,</math>. Now )) y'' is a solution IF AND ONLY IF <math>y=c_1y_1+c_2y_2 \ ,</math> for <math>c_1 ,c_2\in\mathbb C</math>. ..
..
Because the coefficients are real , ..
* we are likely not interested in the complex solutions ..
* our basis elements are mutual conjugates ..
The linear combinations ..
..
: <math>u_1=\mbox{Re}(y_1)=\frac{y_1+y_2}{2}=e^{2x}\cos(x) \ ,</math> and ..
..
: <math>u_2=\mbox{Im}(y_1)=\frac{y_1-y_2}{2i}=e^{2x}\sin(x) \ ,</math> ..
..
will give us a real basis in <math>\{u_1 ,u_2\}</math>. ..
..
(====) Simple harmonic oscillator (====) ..
..
The second order differential equation ..
..
: <math> D^2 y = -k^2 y , </math> ..
..
which represents a simple HARMONIC OSCILLATOR , can be restated as ..
..
: <math> (D^2 + k^2) y = 0. </math> ..
..
The expression in parenthesis can be factored out , yielding ..
..
: <math> (D + i k) (D - i k) y = 0 ,</math> ..
..
which has a pair of linearly independent solutions , one for ..
..
: <math> (D - i k) y = 0 </math> ..
..
and another for ..
..
: <math> (D + i k) y = 0. </math> ..
..
The solutions are , respectively , ..
..
: <math> y_0 = A_0 e^{i k x} </math> ..
..
and ..
..
: <math> y_1 = A_1 e^{-i k x}. </math> ..
..
These solutions provide a basis for the two-dimensional "SOLUTION SPACE" of the second order differential equation: meaning that linear combinations of these solutions will also be solutions. In particular , the following solutions can be constructed ..
..
: <math> y_{0'} = {A_0 e^{i k x} + A_1 e^{-i k x} \over 2} = C_0 \cos (k x) </math> ..
..
and ..
..
: <math> y_{1'} = {A_0 e^{i k x} - A_1 e^{-i k x} \over 2 i} = C_1 \sin (k x). </math> ..
..
These last two trigonometric solutions are linearly independent , so they can serve as another basis for the solution space , yielding the following general solution: ..
..
: <math> y_H = C_0 \cos (k x) + C_1 \sin (k x). </math> ..
..
(====) Damped harmonic oscillator (====) ..
Given the equation for the damped HARMONIC OSCILLATOR: ..
..
: <math> \left(D^2 + {b \over m} D + \omega_0^2\right) y = 0 , </math> ..
..
the expression in parentheses can be factored out: first obtain the characteristic equation by replacing (( D )) with &lambda ;. This equation must be satisfied for all (( y )) , thus: ..
..
: <math> \lambda^2 + {b \over m} \lambda + \omega_0^2 = 0. </math> ..
..
Solve using the QUADRATIC FORMULA: ..
..
: <math> \lambda = {-b/m \pm \sqrt{b^2 / m^2 - 4 \omega_0^2} \over 2}. </math> ..
..
Use these data to factor out the original differential equation: ..
..
: <math> \left(D + {b \over 2 m} - \sqrt{{ b^2 \over 4 m^2} - \omega_0^2} \right) \left(D + {b \over 2m} + \sqrt{{ b^2 \over 4 m^2} - \omega_0^2}\right) y = 0. </math> ..
..
This implies a pair of solutions , one corresponding to ..
..
: <math> \left(D + {b \over 2 m} - \sqrt{{ b^2 \over 4 m^2} - \omega_0^2} \right) y = 0 </math> ..
..
and another to ..
..
: <math> \left(D + {b \over 2m} + \sqrt{{ b^2 \over 4 m^2} - \omega_0^2}\right) y = 0 </math> ..
..
The solutions are , respectively , ..
..
: <math> y_0 = A_0 e^{-\omega x + \sqrt{\omega^2 - \omega_0^2} x} = A_0 e^{-\omega x} e^{\sqrt{\omega^2 - \omega_0^2} x} </math> ..
..
and ..
..
: <math> y_1 = A_1 e^{-\omega x - \sqrt{\omega^2 - \omega_0^2} x} = A_1 e^{-\omega x} e^{-\sqrt{\omega^2 - \omega_0^2} x} </math> ..
..
where &omega ; = (( b )) / 2(( m )) . From this linearly independent pair of solutions can be constructed another linearly independent pair which thus serve as a basis for the two-dimensional solution space: ..
..
: <math> y_H (A_0 , A_1) (x) = \left(A_0 \sinh \sqrt{\omega^2 - \omega_0^2} x + A_1 \cosh \sqrt{\omega^2 - \omega_0^2} x\right) e^{-\omega x}. </math> ..
..
However , if .3. &omega ; .3. < .3. &omega ;<sub>0</sub> .3. then it is preferable to get rid of the consequential imaginaries , expressing the general solution as ..
..
: <math> y_H (A_0 , A_1) (x) = \left(A_0 \sin \sqrt{\omega_0^2 - \omega^2} x + A_1 \cos \sqrt{\omega_0^2 - \omega^2} x\right) e^{-\omega x}. </math> ..
..
This latter solution corresponds to the underdamped case , whereas the former one corresponds to the overdamped case: the solutions for the underdamped case OSCILLATE whereas the solutions for the overdamped case do not. ..
..
(==) Nonhomogeneous equation with constant coefficients (==) ..
..
To obtain the solution to the ((((( non-homogeneous equation ))))) (sometimes called ((((( inhomogeneous equation )))))) , find a particular solution (( y )) <sub>(( P )) </sub>(((( x )))) by either the METHOD OF UNDETERMINED COEFFICIENTS or the METHOD OF VARIATION OF PARAMETERS ; the general solution to the linear differential equation is the sum of the general solution of the related homogeneous equation and the particular solution. ..
..
Suppose we face ..
..
: <math>\frac {d^{n}y(x)} {dx^{n}} + A_{1}\frac {d^{n-1}y(x)} {dx^{n-1}} + \cdots + A_{n}y(x) = f(x).</math> ..
..
For later convenience , define the characteristic polynomial ..
..
: <math>P(v)=v^n+A_1v^{n-1}+\cdots+A_n.</math> ..
..
We find the solution basis <math>\{y_1(x) ,y_2(x) ,\ldots ,y_n(x)\}</math> as in the homogeneous (((( f(x)=0 )))) case. We now seek a ((((( particular solution ))))) (( y<sub>p</sub>(x) )) by the ((((( variation of parameters ))))) method. Let the coefficients of the linear combination be functions of (( x )) : ..
..
: <math>y_p(x) = u_1(x) y_1(x) + u_2(x) y_2(x) + \cdots + u_n(x) y_n(x).</math> ..
..
For ease of notation we will drop the dependency on (( x )) (i.e. the various ((( x ))) ). Using the "operator" notation <math>D=d/dx</math> and a broad-minded use of notation , the Ode in question is <math>P(D)y=f</math> ; so ..
..
: <math>f=P(D)y_p=P(D)(u_1y_1)+P(D)(u_2y_2)+\cdots+P(D)(u_ny_n).</math> ..
..
With the constraints ..
..
: <math>0=u'_1y_1+u'_2y_2+\cdots+u'_ny_n</math> ..
: <math>0=u'_1y'_1+u'_2y'_2+\cdots+u'_ny'_n</math> ..
: <math> \cdots</math> ..
: <math>0=u'_1y^{(n-2)}_1+u'_2y^{(n-2)}_2+\cdots+u'_ny^{(n-2)}_n</math> ..
..
the parameters commute out , with a little "dirt": ..
..
: <math>f=u_1P(D)y_1+u_2P(D)y_2+\cdots+u_nP(D)y_n+u'_1y^{(n-1)}_1+u'_2y^{(n-1)}_2+\cdots+u'_ny^{(n-1)}_n.</math> ..
..
But <math>P(D)y_j=0</math> , therefore ..
..
: <math>f=u'_1y^{(n-1)}_1+u'_2y^{(n-1)}_2+\cdots+u'_ny^{(n-1)}_n.</math> ..
..
This , with the constraints , gives a linear system in the <math>u'_j</math>. This much can always be solved ; in fact , combining CRAMER'S RULE with the WRONSKIAN , ..
..
: <math>u'_j=(-1)^{n+j}\frac{W(y_1 ,\ldots ,y_{j-1} ,y_{j+1}\ldots ,y_n)_{0 \choose f}}{W(y_1 ,y_2 ,\ldots ,y_n)}.</math> <!-- caution: check my sign --> ..
..
The rest is a matter of integrating <math>u'_j.</math> ..
..
The particular solution is not unique ; <math>y_p+c_1y_1+\cdots+c_ny_n</math> also satisfies the Ode for any set of constants (( c<sub>j</sub> )) . ..
..
(===) Example (===) ..
Suppose <math>y''-4y'+5y=sin(kx)</math>. We take the solution basis found above <math>\{e^{(2+i)x} ,e^{(2-i)x}\}</math>. ..
: { .3. ..
.3. - ..
.3. <math>W\ ,</math> ..
.3. <math>= \begin{vmatrix}e^{(2+i)x}&e^{(2-i)x} \\ (2+i)e^{(2+i)x}&(2-i)e^{(2-i)x} \end{vmatrix}</math> ..
.3. - ..
.3. ..
.3. <math>=e^{4x}\begin{vmatrix}1&1\\ 2+i&2-i\end{vmatrix}</math> ..
.3. - ..
.3. ..
.3. <math>=-2ie^{4x}\ ,</math> ..
.3. } ..
..
: { .3. ..
.3. - ..
.3. <math>u'_1\ ,</math> ..
.3. <math>=\frac{1}{W}\begin{vmatrix}0&e^{(2-i)x}\\ \sin(kx)&(2-i)e^{(2-i)x}\end{vmatrix}</math> ..
.3. - ..
.3. ..
.3. <math>=-\frac{i}2\sin(kx)e^{(-2-i)x}</math> ..
.3. } ..
..
: { .3. ..
.3. - ..
.3. <math>u'_2\ ,</math> ..
.3. <math>=\frac{1}{W}\begin{vmatrix}e^{(2+i)x}&0\\ (2+i)e^{(2+i)x}&\sin(kx)\end{vmatrix}</math> ..
.3. - ..
.3. ..
.3. <math> =\frac{i}{2}\sin(kx)e^{(-2+i)x}.</math> ..
.3. } ..
..
Using the LIST OF INTEGRALS OF EXPONENTIAL FUNCTIONS ..
..
: { .3. ..
.3. - ..
.3. <math>u_1\ ,</math> ..
.3. <math>=-\frac{i}{2}\int\sin(kx)e^{(-2-i)x}\ ,dx</math> ..
.3. - ..
.3. ..
.3. <math>=\frac{ie^{(-2-i)x}}{2(3+4i+k^2)}\left((2+i)\sin(kx)+k\cos(kx)\right)</math> ..
.3. } ..
..
: { .3. ..
.3. - ..
.3. <math>u_2\ ,</math> ..
.3. <math>=\frac i2\int\sin(kx)e^{(-2+i)x}\ ,dx</math> ..
.3. - ..
.3. ..
.3. <math>=\frac{ie^{(i-2)x}}{2(3-4i+k^2)}\left((i-2)\sin(kx)-k\cos(kx)\right).</math> ..
.3. } ..
..
And so ..
: { .3. ..
.3. - ..
.3. <math>y_p\ ,</math> ..
.3. <math>=\frac{i}{2(3+4i+k^2)}\left((2+i)\sin(kx)+k\cos(kx)\right) ..
+\frac{i}{2(3-4i+k^2)}\left((i-2)\sin(kx)-k\cos(kx)\right)</math> ..
.3. - ..
.3. ..
.3. <math>=\frac{(5-k^2)\sin(kx)+4k\cos(kx)}{(3+k^2)^2+16}.</math> ..
.3. } ..
(Notice that (( u )) <sub>1</sub> and (( u )) <sub>2</sub> had factors that canceled (( y )) <sub>1</sub> and (( y )) <sub>2</sub> ; that is typical.) ..
..
For interest's sake , this Ode has a physical interpretation as a driven damped HARMONIC OSCILLATOR ; (( y<sub>p</sub> )) represents the steady state , and <math>c_1y_1+c_2y_2</math> is the transient. ..
..
== Equation with variable coefficients== ..
..
A linear Ode of order (( n )) with variable coefficients has the general form ..
: <math>p_{n}(x)y^{(n)}(x) + p_{n-1}(x) y^{(n-1)}(x) + \cdots + p_0(x) y(x) = r(x).</math> ..
..
(===) Examples (===) ..
..
A simple example is the CAUCHY–EULER EQUATION often used in engineering ..
..
: <math>x^n y^{(n)}(x) + a_{n-1} x^{n-1} y^{(n-1)}(x) + \cdots + a_0 y(x) = 0.</math> ..
..
(==) First order equation (==) ..
{{ ExampleSidebar .3. 35 % .3. Solve the equation ..
..
: <math>y'(x)+3y(x)=2 \ ,</math> ..
..
with the initial condition ..
..
: <math>y\left(0\right)=2. \ ,</math> ..
..
Using the general solution method: ..
..
: <math>y=e^{-3x}\left(\int 2 e^{3x}\ , dx + \kappa\right). \ ,</math> ..
..
The indefinite integral is solved to give: ..
..
: <math>y=e^{-3x}\left(2/3 e^{3x} + \kappa\right). \ ,</math> ..
..
Then we can reduce to: ..
..
: <math>y=2/3 + \kappa e^{-3x}. \ ,</math> ..
..
where (( &kappa ; )) is 4/3 from the initial condition.}} ..
A linear Ode of order 1 with variable coefficients has the general form ..
..
: <math>Dy(x) + f(x) y(x) = g(x).</math> ..
..
Equations of this form can be solved by multiplying the INTEGRATING FACTOR ..
..
: <math>e^{\int f(x)\ ,dx}</math> ..
..
throughout to obtain ..
..
: <math> Dy(x)e^{\int f(x)\ ,dx}+f(x)y(x)e^{\int f(x)\ ,dx}=g(x)e^{\int f(x) \ , dx} ,</math> ..
..
which simplifies due to the PRODUCT RULE to ..
..
: <math> D (y(x)e^{\int f(x)\ ,dx})=g(x)e^{\int f(x)\ ,dx}</math> ..
..
which , on integrating both sides , yields ..
..
: <math> y(x)e^{\int f(x)\ ,dx}=\int g(x)e^{\int f(x)\ ,dx} \ ,dx+c ~ ,</math> ..
..
: <math> y(x) = {\int g(x)e^{\int f(x)\ ,dx} \ ,dx+c \over e^{\int f(x)\ ,dx}} ~.</math> ..
..
In other words: The solution of a first-order linear Ode ..
..
: <math>y'(x) + f(x) y(x) = g(x) ,</math> ..
..
with coefficients that may or may not vary with (( x )) , is: ..
..
: <math>y=e^{-a(x)}\left(\int g(x) e^{a(x)}\ , dx + \kappa\right)</math> ..
..
where (( <math>\kappa</math> )) is the constant of integration , and ..
..
: <math>a(x)=\int{f(x)\ ,dx}.</math> ..
..
(===) Examples (===) ..
Consider a first order differential equation with CONSTANT COEFFICIENTS: ..
..
: <math>\frac{dy}{dx} + b y = 1.</math> ..
..
This equation is particularly relevant to first order systems such as RC CIRCUITS and MASS-DAMPER systems. ..
..
In this case , (( p )) (((( x )))) = b , (( r )) (((( x )))) = 1. ..
..
Hence its solution is ..
..
: <math>y(x) = e^{-bx} \left( e^{bx}/b+ C \right) = 1/b + C e^{-bx} .</math> ..
..
(==) See also (==) ..
* CONTINUOUS-REPAYMENT_MORTGAGE#ORDINARY_TIME_DIFFERENTIAL_EQUATION .3. CONTINUOUS-REPAYMENT MORTGAGE .3. Continuous-repayment mortgage]] ..
* FOURIER TRANSFORM ..
* LAPLACE TRANSFORM ..
..
(==) Notes (==) ..
{{ reflist .3. 2}} ..
..
(==) References (==) ..
* {{ Citation ..
.3. author = Birkhoff , Garret and Rota , Gian-Carlo ..
.3. year = 1978 ..
.3. title = Ordinary Differential Equations ..
.3. isbn = 0-471-07411-X ..
.3. publisher = John Wiley and Sons , Inc. ..
.3. location = New York ..
.3. oclc = ..
}} ..
* {{ Citation ..
.3. author = Gershenfeld , Neil ..
.3. year = 1999 ..
.3. title =The Nature of Mathematical Modeling ..
.3. isbn = 978-0521-570954 ..
.3. publisher = Cambridge University Press ..
.3. location = Cambridge , Uk. ..
.3. oclc = ..
}} ..
* {{ Citation ..
.3. author = Robinson , James C. ..
.3. year = 2004 ..
.3. title = An Introduction to Ordinary Differential Equations ..
.3. isbn = 0-521-826500 ..
.3. publisher = Cambridge University Press ..
.3. location = Cambridge , Uk. ..
.3. oclc = ..
}} ..
..
[[Category:Differential equations]] ..
..
[[ar:معادلة تفاضلية خطية]] ..
[[cs:Lineární diferenciální rovnice]] ..
[[de:Lineare gewöhnliche Differentialgleichung]] ..
[[es:Ecuación diferencial lineal]] ..
[[fr:Équation différentielle linéaire]] ..
[[it:Equazione differenziale lineare]] ..
[[he:משוואה דיפרנציאלית לינארית]] ..
[[ja:線型微分方程式]] ..
[[pt:Equação diferencial linear]] ..
[[ru:Линейное дифференциальное уравнение]] ..
[[sv:Linjär differentialekvation]] ..
[[zh:线性微分方程]] ..
paraulesenllacos ..
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MATHEMATICS ..
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DIFFERENTIAL EQUATION ..
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DIFFERENTIAL OPERATOR ..
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LINEAR OPERATOR ..
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RIGHT HAND SIDE ..
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DERIVATIVE ..
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SHROUD OF TURIN ..
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ORDINARY DIFFERENTIAL EQUATION ..
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CONTRACTED ..
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TENSORS ..
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PARTIAL DIFFERENTIAL EQUATION ..
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CONSTANT COEFFICIENTS ..
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EULER ..
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MONGE ..
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CAUCHY ..
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ROOT-FINDING ALGORITHM#FINDING ROOTS OF POLYNOMIALS .3. SOLVING ..
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SUPERPOSITION PRINCIPLE ..
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LINEAR COMBINATION ..
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DISTINCT ..
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LINEARLY INDEPENDENT ..
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VANDERMONDE DETERMINANT ..
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BASIS ..
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MULTIPLICITY#MULTIPLICITY OF A ROOT OF A POLYNOMIAL .3. MULTIPLICITY ..
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ZERO ..
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CONJUGATE ..
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LINEAR COMBINATIONS ..
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RE(((( Y )))) ..
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IM(((( Y )))) ..
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EULER'S FORMULA ..
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IF AND ONLY IF ..
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HARMONIC OSCILLATOR ..
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SOLUTION SPACE ..
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HARMONIC OSCILLATOR ..
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QUADRATIC FORMULA ..
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OSCILLATE ..
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METHOD OF UNDETERMINED COEFFICIENTS ..
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METHOD OF VARIATION OF PARAMETERS ..
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CRAMER'S RULE ..
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WRONSKIAN ..
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LIST OF INTEGRALS OF EXPONENTIAL FUNCTIONS ..
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HARMONIC OSCILLATOR ..
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CAUCHY–EULER EQUATION ..
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INTEGRATING FACTOR ..
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PRODUCT RULE ..
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CONSTANT COEFFICIENTS ..
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RC CIRCUITS ..
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MASS-DAMPER ..
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CONTINUOUS-REPAYMENT_MORTGAGE#ORDINARY_TIME_DIFFERENTIAL_EQUATION .3. CONTINUOUS-REPAYMENT MORTGAGE ..
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FOURIER TRANSFORM ..
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LAPLACE TRANSFORM ..
170.156

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