Showing $|exp(tA)| leq K$ if all eigenvalues have real part negative or zero (and if zero real part, simple...
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I wish to show that if all eigenvalues have real part negative or zero and if those eigenvalues with zero real part are simple, there exists a constant $K>0$ such that $|exp(tA)| leq K$, $(0<t<infty)$, and hence every solution of $y' = Ay$ is bounded on $(0 leq t < infty)$.
We can write our matrix $A$ as $A = PBP^{-1}$ and since all eigenvalues are simple, $B$ is diagonal so $A^n = PB^nP^{-1}$. If $B$ is nilpotent then our sum has finite number of terms and stops at the $n-1$ term.
EDIT:
ordinary-differential-equations
$endgroup$
|
show 3 more comments
$begingroup$
I wish to show that if all eigenvalues have real part negative or zero and if those eigenvalues with zero real part are simple, there exists a constant $K>0$ such that $|exp(tA)| leq K$, $(0<t<infty)$, and hence every solution of $y' = Ay$ is bounded on $(0 leq t < infty)$.
We can write our matrix $A$ as $A = PBP^{-1}$ and since all eigenvalues are simple, $B$ is diagonal so $A^n = PB^nP^{-1}$. If $B$ is nilpotent then our sum has finite number of terms and stops at the $n-1$ term.
EDIT:
ordinary-differential-equations
$endgroup$
$begingroup$
You mean the norm of the matrix? It is a usual convention that $|A|$ denotes the determinant of the matrix $A$.
$endgroup$
– LutzL
Dec 13 '18 at 22:13
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Hi @LutzL ..of course ah sorry. I've made an edit. Could you please see it?
$endgroup$
– Nalt
Dec 13 '18 at 22:22
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This seems now wrong. You get from the differential equation and the Wronski relation that $det(exp(tA))=exp(t,{rm trace}(A))$, so that this interpretation is trivial. I think your task is really for the norm $|exp(tA)|$, probably the spectral norm.
$endgroup$
– LutzL
Dec 13 '18 at 22:28
$begingroup$
@LutzL Here is a photo of the exericse: i.imgur.com/dUby5kn.png By spectral norm, we have to talk about the maximum norm $sqrt{A^H A}$ mathworld.wolfram.com/SpectralNorm.html But here we don't know which eigenvalue will the be maximum. I don't think we have enough information for that
$endgroup$
– Nalt
Dec 13 '18 at 23:06
$begingroup$
The spectral norm is $sqrt{lambda_{max}(A^HA)}$, the Frobenius norm is $sqrt{trace(A^HA)}$, you probably have to use the first one.
$endgroup$
– LutzL
Dec 13 '18 at 23:33
|
show 3 more comments
$begingroup$
I wish to show that if all eigenvalues have real part negative or zero and if those eigenvalues with zero real part are simple, there exists a constant $K>0$ such that $|exp(tA)| leq K$, $(0<t<infty)$, and hence every solution of $y' = Ay$ is bounded on $(0 leq t < infty)$.
We can write our matrix $A$ as $A = PBP^{-1}$ and since all eigenvalues are simple, $B$ is diagonal so $A^n = PB^nP^{-1}$. If $B$ is nilpotent then our sum has finite number of terms and stops at the $n-1$ term.
EDIT:
ordinary-differential-equations
$endgroup$
I wish to show that if all eigenvalues have real part negative or zero and if those eigenvalues with zero real part are simple, there exists a constant $K>0$ such that $|exp(tA)| leq K$, $(0<t<infty)$, and hence every solution of $y' = Ay$ is bounded on $(0 leq t < infty)$.
We can write our matrix $A$ as $A = PBP^{-1}$ and since all eigenvalues are simple, $B$ is diagonal so $A^n = PB^nP^{-1}$. If $B$ is nilpotent then our sum has finite number of terms and stops at the $n-1$ term.
EDIT:
ordinary-differential-equations
ordinary-differential-equations
edited Dec 14 '18 at 0:20
Nalt
asked Dec 13 '18 at 21:52
NaltNalt
756
756
$begingroup$
You mean the norm of the matrix? It is a usual convention that $|A|$ denotes the determinant of the matrix $A$.
$endgroup$
– LutzL
Dec 13 '18 at 22:13
$begingroup$
Hi @LutzL ..of course ah sorry. I've made an edit. Could you please see it?
$endgroup$
– Nalt
Dec 13 '18 at 22:22
$begingroup$
This seems now wrong. You get from the differential equation and the Wronski relation that $det(exp(tA))=exp(t,{rm trace}(A))$, so that this interpretation is trivial. I think your task is really for the norm $|exp(tA)|$, probably the spectral norm.
$endgroup$
– LutzL
Dec 13 '18 at 22:28
$begingroup$
@LutzL Here is a photo of the exericse: i.imgur.com/dUby5kn.png By spectral norm, we have to talk about the maximum norm $sqrt{A^H A}$ mathworld.wolfram.com/SpectralNorm.html But here we don't know which eigenvalue will the be maximum. I don't think we have enough information for that
$endgroup$
– Nalt
Dec 13 '18 at 23:06
$begingroup$
The spectral norm is $sqrt{lambda_{max}(A^HA)}$, the Frobenius norm is $sqrt{trace(A^HA)}$, you probably have to use the first one.
$endgroup$
– LutzL
Dec 13 '18 at 23:33
|
show 3 more comments
$begingroup$
You mean the norm of the matrix? It is a usual convention that $|A|$ denotes the determinant of the matrix $A$.
$endgroup$
– LutzL
Dec 13 '18 at 22:13
$begingroup$
Hi @LutzL ..of course ah sorry. I've made an edit. Could you please see it?
$endgroup$
– Nalt
Dec 13 '18 at 22:22
$begingroup$
This seems now wrong. You get from the differential equation and the Wronski relation that $det(exp(tA))=exp(t,{rm trace}(A))$, so that this interpretation is trivial. I think your task is really for the norm $|exp(tA)|$, probably the spectral norm.
$endgroup$
– LutzL
Dec 13 '18 at 22:28
$begingroup$
@LutzL Here is a photo of the exericse: i.imgur.com/dUby5kn.png By spectral norm, we have to talk about the maximum norm $sqrt{A^H A}$ mathworld.wolfram.com/SpectralNorm.html But here we don't know which eigenvalue will the be maximum. I don't think we have enough information for that
$endgroup$
– Nalt
Dec 13 '18 at 23:06
$begingroup$
The spectral norm is $sqrt{lambda_{max}(A^HA)}$, the Frobenius norm is $sqrt{trace(A^HA)}$, you probably have to use the first one.
$endgroup$
– LutzL
Dec 13 '18 at 23:33
$begingroup$
You mean the norm of the matrix? It is a usual convention that $|A|$ denotes the determinant of the matrix $A$.
$endgroup$
– LutzL
Dec 13 '18 at 22:13
$begingroup$
You mean the norm of the matrix? It is a usual convention that $|A|$ denotes the determinant of the matrix $A$.
$endgroup$
– LutzL
Dec 13 '18 at 22:13
$begingroup$
Hi @LutzL ..of course ah sorry. I've made an edit. Could you please see it?
$endgroup$
– Nalt
Dec 13 '18 at 22:22
$begingroup$
Hi @LutzL ..of course ah sorry. I've made an edit. Could you please see it?
$endgroup$
– Nalt
Dec 13 '18 at 22:22
$begingroup$
This seems now wrong. You get from the differential equation and the Wronski relation that $det(exp(tA))=exp(t,{rm trace}(A))$, so that this interpretation is trivial. I think your task is really for the norm $|exp(tA)|$, probably the spectral norm.
$endgroup$
– LutzL
Dec 13 '18 at 22:28
$begingroup$
This seems now wrong. You get from the differential equation and the Wronski relation that $det(exp(tA))=exp(t,{rm trace}(A))$, so that this interpretation is trivial. I think your task is really for the norm $|exp(tA)|$, probably the spectral norm.
$endgroup$
– LutzL
Dec 13 '18 at 22:28
$begingroup$
@LutzL Here is a photo of the exericse: i.imgur.com/dUby5kn.png By spectral norm, we have to talk about the maximum norm $sqrt{A^H A}$ mathworld.wolfram.com/SpectralNorm.html But here we don't know which eigenvalue will the be maximum. I don't think we have enough information for that
$endgroup$
– Nalt
Dec 13 '18 at 23:06
$begingroup$
@LutzL Here is a photo of the exericse: i.imgur.com/dUby5kn.png By spectral norm, we have to talk about the maximum norm $sqrt{A^H A}$ mathworld.wolfram.com/SpectralNorm.html But here we don't know which eigenvalue will the be maximum. I don't think we have enough information for that
$endgroup$
– Nalt
Dec 13 '18 at 23:06
$begingroup$
The spectral norm is $sqrt{lambda_{max}(A^HA)}$, the Frobenius norm is $sqrt{trace(A^HA)}$, you probably have to use the first one.
$endgroup$
– LutzL
Dec 13 '18 at 23:33
$begingroup$
The spectral norm is $sqrt{lambda_{max}(A^HA)}$, the Frobenius norm is $sqrt{trace(A^HA)}$, you probably have to use the first one.
$endgroup$
– LutzL
Dec 13 '18 at 23:33
|
show 3 more comments
1 Answer
1
active
oldest
votes
$begingroup$
In this answer, I will focus on showing that $Vert e^{At} Vert$ is bounded where $Vert cdot Vert$ is the standard operator norm,
$Vert A Vert = sup {Vert Ax Vert, ; Vert x Vert = 1 } = inf {C mid Vert Ax Vert le C Vert x Vert, ; forall x }, tag 0$
where $Vert x Vert$ is the standard Hermitian norm for vectors $x in Bbb C^n$, that is, $Vert x Vert$ is derived from the Hermitian inner product
$langle y, z rangle = displaystyle sum_1^n bar y_i z_i, y = (y_1, y_2, ldots, y_n)^T in Bbb C^n, ; text{etc,} tag{0.1}$
by
$Vert x Vert^2 = langle x, x rangle = displaystyle sum_1^n bar x_i x_i. tag{0.2}$
We resort to extending the normal real Euclidean inner product on $Bbb R^n$ to the Heritian product (0.1) to facilitate addressing and handling situations in which some of the eigenvalues of $A$ are non-real complex numbers.
We want to show that
$forall t in Bbb R, ; 0 le t < infty, Vert e^{At} Vert < K tag 1$
for some $0 < K in Bbb R$.
We know that $A$ may be cast into Jordan canonical form by a similarity transformation
$A to PAP^{-1} tag 2$
for some non-singular matrix $P$; we thus first deal with the case of $A$ a Jordan matrix; indeed, we will first address the situation when $A$ is a single Jordan block, that is, a matrix of the form
$A = lambda I_m + N, tag 3$
here $I_m$ is the $m times m$ identity matrix, $lambda$ is an eigenvalue of $A$ and $N$ is the $m times m$ nilpotent matrix consisting of $m - 1$ $1$s on the superdiagonal and zeroes everywhere else. Since $I_m$ commutes with $N_m$, that is,
$I_m N_m = N_m = N_m I_m, tag 4$
it follows that
$e^{At} = e^{(lambda I_m + N_m)t} = e^{lambda I_m t + N_m t} = e^{lambda I_m t} e^{N_m t}; tag 5$
now it is both well-known and easy to see from the matrix power series of $exp$ that
$e^{lambda I_m t} = displaystyle sum_0^infty dfrac{(lambda I_m t)^k}{k!} = sum_0^infty dfrac{lambda^k t^k I_m }{k!} = sum_0^infty dfrac{lambda^k t^k}{k!} I_m = e^{lambda t} I_m; tag 6$
also, since the nilpotent matrix $N$ satisfies
$N^m = 0, tag 7$
we have
$e^{N_m t} = displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 8$
which is an $m times m$ matrix whose entries are polynomials in $t$ of degree at most $m - 1$; it follows from (5), (6) and (8) that $e^{At}$ takes the form
$e^{At} = e^{lambda t} I_m displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} = e^{lambda t} sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 9$
and if
$lambda = sigma + i omega, ; sigma < 0, tag{10}$
we may further decompose $e^{At}$ as
$e^{At} = e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag{11}$
whence
$Vert e^{At} Vert = left Vert e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = vert e^{iomega t} vert left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{12}$
Now it is well-known that for $sigma < 0$ the expression on the right of (12), being dominated by the exponential $e^{sigma t}$, eventually decreases to $0$ as $t to infty$:
$displaystyle lim_{t to infty} Vert e^{At} Vert = lim_{t to infty} left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = 0; tag{13}$
since
$displaystyle Vert e^{At} Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{14}$
is continuous as a function of $t$, it is bounded on any compact interval $[0, tau]$; by choosing $tau$ sufficiently large we may, in the light of the limit (13), assume $Vert e^{At} Vert < epsilon$, $0 < epsilon in Bbb R$, for $t ge tau$; therefore (14) is bounded by some $0 < K in Bbb R$ for all $t in [0, infty)$. We note that in the case $sigma = 0$, we have $m = 1$ by our hypotheses on the matrix $A$, and the Jordan block reduces to $e^{iomega t}$, which is manifestly bounded; indeed, as long as the block size is $1$, the block reduces to $e^{(sigma + i omega)t}$ with $sigma le 0$ and is thus easily seen to be bounded in norm.
The preceding discussion shows that $e^{At}$ is bounded for any Jordan block (3) of $A$ as long as $sigma = Re(lambda) le 0$; if $A$ is comprised of multiple Jordan blocks, then there is a bound for each and hence, since the number of Jordan blocks is finite, a bound over all the Jordan blocks of $A$ is obtained by taking the greatest such bound.
The preceding discussion covers the situation when $A$ is in Jordan form; it result may be extended to any $A$ by inverting the similarity transformation (2), an operation which preserves the boundedness of $Vert e^{At} Vert$ (though it may alter a particular bound) since $P$ does not depend upon $t$. We conclude that, in all specified/required cases, there is some $K > 0$ with
$Vert e^{At} Vert < K, ; t in [0, infty). tag{15}$
And we are done.
$endgroup$
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
add a comment |
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1 Answer
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1 Answer
1
active
oldest
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active
oldest
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active
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$begingroup$
In this answer, I will focus on showing that $Vert e^{At} Vert$ is bounded where $Vert cdot Vert$ is the standard operator norm,
$Vert A Vert = sup {Vert Ax Vert, ; Vert x Vert = 1 } = inf {C mid Vert Ax Vert le C Vert x Vert, ; forall x }, tag 0$
where $Vert x Vert$ is the standard Hermitian norm for vectors $x in Bbb C^n$, that is, $Vert x Vert$ is derived from the Hermitian inner product
$langle y, z rangle = displaystyle sum_1^n bar y_i z_i, y = (y_1, y_2, ldots, y_n)^T in Bbb C^n, ; text{etc,} tag{0.1}$
by
$Vert x Vert^2 = langle x, x rangle = displaystyle sum_1^n bar x_i x_i. tag{0.2}$
We resort to extending the normal real Euclidean inner product on $Bbb R^n$ to the Heritian product (0.1) to facilitate addressing and handling situations in which some of the eigenvalues of $A$ are non-real complex numbers.
We want to show that
$forall t in Bbb R, ; 0 le t < infty, Vert e^{At} Vert < K tag 1$
for some $0 < K in Bbb R$.
We know that $A$ may be cast into Jordan canonical form by a similarity transformation
$A to PAP^{-1} tag 2$
for some non-singular matrix $P$; we thus first deal with the case of $A$ a Jordan matrix; indeed, we will first address the situation when $A$ is a single Jordan block, that is, a matrix of the form
$A = lambda I_m + N, tag 3$
here $I_m$ is the $m times m$ identity matrix, $lambda$ is an eigenvalue of $A$ and $N$ is the $m times m$ nilpotent matrix consisting of $m - 1$ $1$s on the superdiagonal and zeroes everywhere else. Since $I_m$ commutes with $N_m$, that is,
$I_m N_m = N_m = N_m I_m, tag 4$
it follows that
$e^{At} = e^{(lambda I_m + N_m)t} = e^{lambda I_m t + N_m t} = e^{lambda I_m t} e^{N_m t}; tag 5$
now it is both well-known and easy to see from the matrix power series of $exp$ that
$e^{lambda I_m t} = displaystyle sum_0^infty dfrac{(lambda I_m t)^k}{k!} = sum_0^infty dfrac{lambda^k t^k I_m }{k!} = sum_0^infty dfrac{lambda^k t^k}{k!} I_m = e^{lambda t} I_m; tag 6$
also, since the nilpotent matrix $N$ satisfies
$N^m = 0, tag 7$
we have
$e^{N_m t} = displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 8$
which is an $m times m$ matrix whose entries are polynomials in $t$ of degree at most $m - 1$; it follows from (5), (6) and (8) that $e^{At}$ takes the form
$e^{At} = e^{lambda t} I_m displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} = e^{lambda t} sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 9$
and if
$lambda = sigma + i omega, ; sigma < 0, tag{10}$
we may further decompose $e^{At}$ as
$e^{At} = e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag{11}$
whence
$Vert e^{At} Vert = left Vert e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = vert e^{iomega t} vert left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{12}$
Now it is well-known that for $sigma < 0$ the expression on the right of (12), being dominated by the exponential $e^{sigma t}$, eventually decreases to $0$ as $t to infty$:
$displaystyle lim_{t to infty} Vert e^{At} Vert = lim_{t to infty} left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = 0; tag{13}$
since
$displaystyle Vert e^{At} Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{14}$
is continuous as a function of $t$, it is bounded on any compact interval $[0, tau]$; by choosing $tau$ sufficiently large we may, in the light of the limit (13), assume $Vert e^{At} Vert < epsilon$, $0 < epsilon in Bbb R$, for $t ge tau$; therefore (14) is bounded by some $0 < K in Bbb R$ for all $t in [0, infty)$. We note that in the case $sigma = 0$, we have $m = 1$ by our hypotheses on the matrix $A$, and the Jordan block reduces to $e^{iomega t}$, which is manifestly bounded; indeed, as long as the block size is $1$, the block reduces to $e^{(sigma + i omega)t}$ with $sigma le 0$ and is thus easily seen to be bounded in norm.
The preceding discussion shows that $e^{At}$ is bounded for any Jordan block (3) of $A$ as long as $sigma = Re(lambda) le 0$; if $A$ is comprised of multiple Jordan blocks, then there is a bound for each and hence, since the number of Jordan blocks is finite, a bound over all the Jordan blocks of $A$ is obtained by taking the greatest such bound.
The preceding discussion covers the situation when $A$ is in Jordan form; it result may be extended to any $A$ by inverting the similarity transformation (2), an operation which preserves the boundedness of $Vert e^{At} Vert$ (though it may alter a particular bound) since $P$ does not depend upon $t$. We conclude that, in all specified/required cases, there is some $K > 0$ with
$Vert e^{At} Vert < K, ; t in [0, infty). tag{15}$
And we are done.
$endgroup$
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
add a comment |
$begingroup$
In this answer, I will focus on showing that $Vert e^{At} Vert$ is bounded where $Vert cdot Vert$ is the standard operator norm,
$Vert A Vert = sup {Vert Ax Vert, ; Vert x Vert = 1 } = inf {C mid Vert Ax Vert le C Vert x Vert, ; forall x }, tag 0$
where $Vert x Vert$ is the standard Hermitian norm for vectors $x in Bbb C^n$, that is, $Vert x Vert$ is derived from the Hermitian inner product
$langle y, z rangle = displaystyle sum_1^n bar y_i z_i, y = (y_1, y_2, ldots, y_n)^T in Bbb C^n, ; text{etc,} tag{0.1}$
by
$Vert x Vert^2 = langle x, x rangle = displaystyle sum_1^n bar x_i x_i. tag{0.2}$
We resort to extending the normal real Euclidean inner product on $Bbb R^n$ to the Heritian product (0.1) to facilitate addressing and handling situations in which some of the eigenvalues of $A$ are non-real complex numbers.
We want to show that
$forall t in Bbb R, ; 0 le t < infty, Vert e^{At} Vert < K tag 1$
for some $0 < K in Bbb R$.
We know that $A$ may be cast into Jordan canonical form by a similarity transformation
$A to PAP^{-1} tag 2$
for some non-singular matrix $P$; we thus first deal with the case of $A$ a Jordan matrix; indeed, we will first address the situation when $A$ is a single Jordan block, that is, a matrix of the form
$A = lambda I_m + N, tag 3$
here $I_m$ is the $m times m$ identity matrix, $lambda$ is an eigenvalue of $A$ and $N$ is the $m times m$ nilpotent matrix consisting of $m - 1$ $1$s on the superdiagonal and zeroes everywhere else. Since $I_m$ commutes with $N_m$, that is,
$I_m N_m = N_m = N_m I_m, tag 4$
it follows that
$e^{At} = e^{(lambda I_m + N_m)t} = e^{lambda I_m t + N_m t} = e^{lambda I_m t} e^{N_m t}; tag 5$
now it is both well-known and easy to see from the matrix power series of $exp$ that
$e^{lambda I_m t} = displaystyle sum_0^infty dfrac{(lambda I_m t)^k}{k!} = sum_0^infty dfrac{lambda^k t^k I_m }{k!} = sum_0^infty dfrac{lambda^k t^k}{k!} I_m = e^{lambda t} I_m; tag 6$
also, since the nilpotent matrix $N$ satisfies
$N^m = 0, tag 7$
we have
$e^{N_m t} = displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 8$
which is an $m times m$ matrix whose entries are polynomials in $t$ of degree at most $m - 1$; it follows from (5), (6) and (8) that $e^{At}$ takes the form
$e^{At} = e^{lambda t} I_m displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} = e^{lambda t} sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 9$
and if
$lambda = sigma + i omega, ; sigma < 0, tag{10}$
we may further decompose $e^{At}$ as
$e^{At} = e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag{11}$
whence
$Vert e^{At} Vert = left Vert e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = vert e^{iomega t} vert left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{12}$
Now it is well-known that for $sigma < 0$ the expression on the right of (12), being dominated by the exponential $e^{sigma t}$, eventually decreases to $0$ as $t to infty$:
$displaystyle lim_{t to infty} Vert e^{At} Vert = lim_{t to infty} left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = 0; tag{13}$
since
$displaystyle Vert e^{At} Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{14}$
is continuous as a function of $t$, it is bounded on any compact interval $[0, tau]$; by choosing $tau$ sufficiently large we may, in the light of the limit (13), assume $Vert e^{At} Vert < epsilon$, $0 < epsilon in Bbb R$, for $t ge tau$; therefore (14) is bounded by some $0 < K in Bbb R$ for all $t in [0, infty)$. We note that in the case $sigma = 0$, we have $m = 1$ by our hypotheses on the matrix $A$, and the Jordan block reduces to $e^{iomega t}$, which is manifestly bounded; indeed, as long as the block size is $1$, the block reduces to $e^{(sigma + i omega)t}$ with $sigma le 0$ and is thus easily seen to be bounded in norm.
The preceding discussion shows that $e^{At}$ is bounded for any Jordan block (3) of $A$ as long as $sigma = Re(lambda) le 0$; if $A$ is comprised of multiple Jordan blocks, then there is a bound for each and hence, since the number of Jordan blocks is finite, a bound over all the Jordan blocks of $A$ is obtained by taking the greatest such bound.
The preceding discussion covers the situation when $A$ is in Jordan form; it result may be extended to any $A$ by inverting the similarity transformation (2), an operation which preserves the boundedness of $Vert e^{At} Vert$ (though it may alter a particular bound) since $P$ does not depend upon $t$. We conclude that, in all specified/required cases, there is some $K > 0$ with
$Vert e^{At} Vert < K, ; t in [0, infty). tag{15}$
And we are done.
$endgroup$
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
add a comment |
$begingroup$
In this answer, I will focus on showing that $Vert e^{At} Vert$ is bounded where $Vert cdot Vert$ is the standard operator norm,
$Vert A Vert = sup {Vert Ax Vert, ; Vert x Vert = 1 } = inf {C mid Vert Ax Vert le C Vert x Vert, ; forall x }, tag 0$
where $Vert x Vert$ is the standard Hermitian norm for vectors $x in Bbb C^n$, that is, $Vert x Vert$ is derived from the Hermitian inner product
$langle y, z rangle = displaystyle sum_1^n bar y_i z_i, y = (y_1, y_2, ldots, y_n)^T in Bbb C^n, ; text{etc,} tag{0.1}$
by
$Vert x Vert^2 = langle x, x rangle = displaystyle sum_1^n bar x_i x_i. tag{0.2}$
We resort to extending the normal real Euclidean inner product on $Bbb R^n$ to the Heritian product (0.1) to facilitate addressing and handling situations in which some of the eigenvalues of $A$ are non-real complex numbers.
We want to show that
$forall t in Bbb R, ; 0 le t < infty, Vert e^{At} Vert < K tag 1$
for some $0 < K in Bbb R$.
We know that $A$ may be cast into Jordan canonical form by a similarity transformation
$A to PAP^{-1} tag 2$
for some non-singular matrix $P$; we thus first deal with the case of $A$ a Jordan matrix; indeed, we will first address the situation when $A$ is a single Jordan block, that is, a matrix of the form
$A = lambda I_m + N, tag 3$
here $I_m$ is the $m times m$ identity matrix, $lambda$ is an eigenvalue of $A$ and $N$ is the $m times m$ nilpotent matrix consisting of $m - 1$ $1$s on the superdiagonal and zeroes everywhere else. Since $I_m$ commutes with $N_m$, that is,
$I_m N_m = N_m = N_m I_m, tag 4$
it follows that
$e^{At} = e^{(lambda I_m + N_m)t} = e^{lambda I_m t + N_m t} = e^{lambda I_m t} e^{N_m t}; tag 5$
now it is both well-known and easy to see from the matrix power series of $exp$ that
$e^{lambda I_m t} = displaystyle sum_0^infty dfrac{(lambda I_m t)^k}{k!} = sum_0^infty dfrac{lambda^k t^k I_m }{k!} = sum_0^infty dfrac{lambda^k t^k}{k!} I_m = e^{lambda t} I_m; tag 6$
also, since the nilpotent matrix $N$ satisfies
$N^m = 0, tag 7$
we have
$e^{N_m t} = displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 8$
which is an $m times m$ matrix whose entries are polynomials in $t$ of degree at most $m - 1$; it follows from (5), (6) and (8) that $e^{At}$ takes the form
$e^{At} = e^{lambda t} I_m displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} = e^{lambda t} sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 9$
and if
$lambda = sigma + i omega, ; sigma < 0, tag{10}$
we may further decompose $e^{At}$ as
$e^{At} = e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag{11}$
whence
$Vert e^{At} Vert = left Vert e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = vert e^{iomega t} vert left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{12}$
Now it is well-known that for $sigma < 0$ the expression on the right of (12), being dominated by the exponential $e^{sigma t}$, eventually decreases to $0$ as $t to infty$:
$displaystyle lim_{t to infty} Vert e^{At} Vert = lim_{t to infty} left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = 0; tag{13}$
since
$displaystyle Vert e^{At} Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{14}$
is continuous as a function of $t$, it is bounded on any compact interval $[0, tau]$; by choosing $tau$ sufficiently large we may, in the light of the limit (13), assume $Vert e^{At} Vert < epsilon$, $0 < epsilon in Bbb R$, for $t ge tau$; therefore (14) is bounded by some $0 < K in Bbb R$ for all $t in [0, infty)$. We note that in the case $sigma = 0$, we have $m = 1$ by our hypotheses on the matrix $A$, and the Jordan block reduces to $e^{iomega t}$, which is manifestly bounded; indeed, as long as the block size is $1$, the block reduces to $e^{(sigma + i omega)t}$ with $sigma le 0$ and is thus easily seen to be bounded in norm.
The preceding discussion shows that $e^{At}$ is bounded for any Jordan block (3) of $A$ as long as $sigma = Re(lambda) le 0$; if $A$ is comprised of multiple Jordan blocks, then there is a bound for each and hence, since the number of Jordan blocks is finite, a bound over all the Jordan blocks of $A$ is obtained by taking the greatest such bound.
The preceding discussion covers the situation when $A$ is in Jordan form; it result may be extended to any $A$ by inverting the similarity transformation (2), an operation which preserves the boundedness of $Vert e^{At} Vert$ (though it may alter a particular bound) since $P$ does not depend upon $t$. We conclude that, in all specified/required cases, there is some $K > 0$ with
$Vert e^{At} Vert < K, ; t in [0, infty). tag{15}$
And we are done.
$endgroup$
In this answer, I will focus on showing that $Vert e^{At} Vert$ is bounded where $Vert cdot Vert$ is the standard operator norm,
$Vert A Vert = sup {Vert Ax Vert, ; Vert x Vert = 1 } = inf {C mid Vert Ax Vert le C Vert x Vert, ; forall x }, tag 0$
where $Vert x Vert$ is the standard Hermitian norm for vectors $x in Bbb C^n$, that is, $Vert x Vert$ is derived from the Hermitian inner product
$langle y, z rangle = displaystyle sum_1^n bar y_i z_i, y = (y_1, y_2, ldots, y_n)^T in Bbb C^n, ; text{etc,} tag{0.1}$
by
$Vert x Vert^2 = langle x, x rangle = displaystyle sum_1^n bar x_i x_i. tag{0.2}$
We resort to extending the normal real Euclidean inner product on $Bbb R^n$ to the Heritian product (0.1) to facilitate addressing and handling situations in which some of the eigenvalues of $A$ are non-real complex numbers.
We want to show that
$forall t in Bbb R, ; 0 le t < infty, Vert e^{At} Vert < K tag 1$
for some $0 < K in Bbb R$.
We know that $A$ may be cast into Jordan canonical form by a similarity transformation
$A to PAP^{-1} tag 2$
for some non-singular matrix $P$; we thus first deal with the case of $A$ a Jordan matrix; indeed, we will first address the situation when $A$ is a single Jordan block, that is, a matrix of the form
$A = lambda I_m + N, tag 3$
here $I_m$ is the $m times m$ identity matrix, $lambda$ is an eigenvalue of $A$ and $N$ is the $m times m$ nilpotent matrix consisting of $m - 1$ $1$s on the superdiagonal and zeroes everywhere else. Since $I_m$ commutes with $N_m$, that is,
$I_m N_m = N_m = N_m I_m, tag 4$
it follows that
$e^{At} = e^{(lambda I_m + N_m)t} = e^{lambda I_m t + N_m t} = e^{lambda I_m t} e^{N_m t}; tag 5$
now it is both well-known and easy to see from the matrix power series of $exp$ that
$e^{lambda I_m t} = displaystyle sum_0^infty dfrac{(lambda I_m t)^k}{k!} = sum_0^infty dfrac{lambda^k t^k I_m }{k!} = sum_0^infty dfrac{lambda^k t^k}{k!} I_m = e^{lambda t} I_m; tag 6$
also, since the nilpotent matrix $N$ satisfies
$N^m = 0, tag 7$
we have
$e^{N_m t} = displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 8$
which is an $m times m$ matrix whose entries are polynomials in $t$ of degree at most $m - 1$; it follows from (5), (6) and (8) that $e^{At}$ takes the form
$e^{At} = e^{lambda t} I_m displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} = e^{lambda t} sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag 9$
and if
$lambda = sigma + i omega, ; sigma < 0, tag{10}$
we may further decompose $e^{At}$ as
$e^{At} = e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!}, tag{11}$
whence
$Vert e^{At} Vert = left Vert e^{iomega t} e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = vert e^{iomega t} vert left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{12}$
Now it is well-known that for $sigma < 0$ the expression on the right of (12), being dominated by the exponential $e^{sigma t}$, eventually decreases to $0$ as $t to infty$:
$displaystyle lim_{t to infty} Vert e^{At} Vert = lim_{t to infty} left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert = 0; tag{13}$
since
$displaystyle Vert e^{At} Vert = left Vert e^{sigma t} displaystyle sum_0^{m - 1} dfrac{N_m^k t^k}{k!} right Vert. tag{14}$
is continuous as a function of $t$, it is bounded on any compact interval $[0, tau]$; by choosing $tau$ sufficiently large we may, in the light of the limit (13), assume $Vert e^{At} Vert < epsilon$, $0 < epsilon in Bbb R$, for $t ge tau$; therefore (14) is bounded by some $0 < K in Bbb R$ for all $t in [0, infty)$. We note that in the case $sigma = 0$, we have $m = 1$ by our hypotheses on the matrix $A$, and the Jordan block reduces to $e^{iomega t}$, which is manifestly bounded; indeed, as long as the block size is $1$, the block reduces to $e^{(sigma + i omega)t}$ with $sigma le 0$ and is thus easily seen to be bounded in norm.
The preceding discussion shows that $e^{At}$ is bounded for any Jordan block (3) of $A$ as long as $sigma = Re(lambda) le 0$; if $A$ is comprised of multiple Jordan blocks, then there is a bound for each and hence, since the number of Jordan blocks is finite, a bound over all the Jordan blocks of $A$ is obtained by taking the greatest such bound.
The preceding discussion covers the situation when $A$ is in Jordan form; it result may be extended to any $A$ by inverting the similarity transformation (2), an operation which preserves the boundedness of $Vert e^{At} Vert$ (though it may alter a particular bound) since $P$ does not depend upon $t$. We conclude that, in all specified/required cases, there is some $K > 0$ with
$Vert e^{At} Vert < K, ; t in [0, infty). tag{15}$
And we are done.
edited Dec 14 '18 at 20:47
answered Dec 14 '18 at 18:49
Robert LewisRobert Lewis
46.6k23067
46.6k23067
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
add a comment |
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
This is very detailed thank you so much. I believe I understand it, but i'll come back with comments when I find things I am confused about.
$endgroup$
– Nalt
Dec 15 '18 at 5:32
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
$begingroup$
@Nalt: thank you. Looking forward to hearing from you. Cheers!
$endgroup$
– Robert Lewis
Dec 15 '18 at 5:45
add a comment |
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$begingroup$
You mean the norm of the matrix? It is a usual convention that $|A|$ denotes the determinant of the matrix $A$.
$endgroup$
– LutzL
Dec 13 '18 at 22:13
$begingroup$
Hi @LutzL ..of course ah sorry. I've made an edit. Could you please see it?
$endgroup$
– Nalt
Dec 13 '18 at 22:22
$begingroup$
This seems now wrong. You get from the differential equation and the Wronski relation that $det(exp(tA))=exp(t,{rm trace}(A))$, so that this interpretation is trivial. I think your task is really for the norm $|exp(tA)|$, probably the spectral norm.
$endgroup$
– LutzL
Dec 13 '18 at 22:28
$begingroup$
@LutzL Here is a photo of the exericse: i.imgur.com/dUby5kn.png By spectral norm, we have to talk about the maximum norm $sqrt{A^H A}$ mathworld.wolfram.com/SpectralNorm.html But here we don't know which eigenvalue will the be maximum. I don't think we have enough information for that
$endgroup$
– Nalt
Dec 13 '18 at 23:06
$begingroup$
The spectral norm is $sqrt{lambda_{max}(A^HA)}$, the Frobenius norm is $sqrt{trace(A^HA)}$, you probably have to use the first one.
$endgroup$
– LutzL
Dec 13 '18 at 23:33