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MATH 551 LECTURE NOTES FREDHOLM INTEGRAL EQUATIONS (A BRIEF INTRODUCTION)
MATH 551 讲座笔记弗雷德霍姆积分方程(简要介绍)

TOPICS COVERED 涵盖的主题

  • Fredholm integral operators
    弗雷德霍姆积分算子
  • Integral equations (Volterra vs. Fredholm)
    积分方程(Volterra vs. Fredholm)
  • Eigenfunctions for separable kernels
    可分离核的特征函数
  • Adjoint operator, symmetric kernels
    共轭算子,对称核
  • Solution procedure (separable)
    解决方案程序(可分离)
  • Solution via eigenfunctions (first and second kind)
    通过特征函数的解决方案(第一和第二种)
  • Shortcuts: undetermined coefficients
    快捷方式:未定系数
  • An example (separable kernel, )
    一个例子(可分离核,
  • Non-separable kernels (briefly)
    不可分离的核(简要)
  • Hilbert-Schmidt theory 希尔伯特-施密特理论

PREFACE 前言

Read the Fredholm alternative notes before proceeding. This is covered in the book (Section 9.4), but the material on integral equations is not. For references on integral equations (and other topics covered in the book too!), see:
在继续之前,请阅读弗雷德霍姆交替笔记。 这在书中有涵盖(第 9.4 节),但积分方程的材料没有。 有关积分方程(以及书中涵盖的其他主题!)的参考资料,请参见:
  • Riley and Hobson, Mathematical methods for physics and engineering (this is an extensive reference, also for other topics in the course)
    莱利和霍布森,《物理和工程的数学方法》(这是一个广泛的参考资料,也适用于课程中的其他主题)
  • Guenther and Lee, Partial differential equations of mathematical physics and integral equations (more technical; not the best first reference)
    Guenther 和 Lee,数学物理的偏微分方程和积分方程(更技术性;不是最佳的第一参考资料)
  • J.D. Logan, Applied mathematics (more generally about applied mathematics techniques, with a good section on integral equations)
    J.D. Logan,应用数学(更普遍地涉及应用数学技术,有一个很好的部分关于积分方程)

1. FREDHOLM INTEGRAL EQUATIONS: INTRODUCTION
1. 弗雷德霍姆积分方程:介绍

Differential equations are a subset of more general equations involving linear operators . Here, we give a brief treatment of a generalization to integral equations.
微分方程 是涉及线性算子 的更一般方程的子集。在这里,我们对积分方程的一般化进行简要处理。
To motivate this, every ODE IVP can be written as an 'integral equation' by integrating. For instance, consider the first order IVP
为了激励这一点,每个 ODE IVP 都可以通过积分写成一个“积分方程”。例如,考虑一阶 IVP
Integrate both sides from to to get the integral equation
积分两边得到积分方程
If solves (1.2) then it also solves (1.1); they are 'equivalent' in this sense. However, it is slightly more general as does not need to be differentiable.
如果 解决(1.2),那么它也解决(1.1);在这个意义上它们是“等价的”。然而,它稍微更一般,因为 不需要可微。
Definition: A Volterra integral equation for has the form
定义: 的 Volterra 积分方程的形式
The function is the kernel. Note the integral upper bound is (the ind. variable).
函数 是核心。请注意积分上限是 (自变量)。
Volterra integral equations are 'equivalent' to ODE initial value problems on for linear ODEs. They will not be studied here.
Volterra 积分方程在 上与线性 ODE 的初值问题“等价”。这里不会对它们进行研究。
In contrast, ODE boundary value problems generalize to Fredholm integral equations. Such an equation involves an integral over the whole domain (not up to ):
相比之下,ODE 边界值问题推广到 Fredholm 积分方程。这样的方程涉及整个域上的积分(不仅仅是 )。
Definition: A Fredholm integral equation (FIE) has two forms:
定义:Fredholm 积分方程(FIE)有两种形式:

- First kind: (FIE-1)
- 第一种:(FIE-1)

  • Second kind: (FIE-2) 第二种:(FIE-2)
The 'second kind' is the first kind plus a multiple of . Note that the operator
“第二类”是第一类加上 的倍数。请注意操作符
is linear; this is called a Fredholm integral operator.
是线性的;这被称为 Fredholm 积分算子。
The simplest kernels are separable ('degenerate'), which have the form
最简单的核是可分离的(“退化的”),其形式为
More complicated kernels are non-separable. Examples include:
更复杂的核是不可分离的。例如包括:
  • (Hilbert transform)
    (Hilbert 变换)
  • (Fourier transform)
    (傅里叶变换)
  • (Laplace transform)
    (拉普拉斯变换)
We will study the last two later. Writing a non-separable kernel in the form (1.5) would require an infinite series, which complicates the analysis. Instead, we will utilize an integral form and some complex analysis later to properly handle non-separable kernels.
我们稍后会研究最后两个。以(1.5)形式写一个不可分离的核需要一个无限级数,这会使分析变得复杂。相反,我们稍后将利用积分形式和一些复杂分析来正确处理不可分离的核。

2. SolVing SEParable FIEs
2. 解决可分离的有限元方程

Suppose is separable and is a Fredholm integral operator of the first kind:
假设 是可分离的, 是第一类 Fredholm 积分算子:
We wish to solve the eigenvalue problem
我们希望解决特征值问题
This can always be done for a separable kernel. The main result is the following:
这总是可以为可分离的核函数完成的。主要结果如下:
Eigenfunctions for FIE-1: For the FIE (2.1) with separable kernel,
FIE-1 的特征函数:对于具有可分离核的 FIE(2.1),
  1. there are non-zero eigenvalues with eigenfunctions . Each eigenfunction is a linear combination of the 's, i.e.
    个非零特征值 ,具有特征函数 。每个特征函数都是 的线性组合,即
  2. is an eigenvalue with infinite multiplicity: an infinite set of (orthogonal) eigenfunctions characterized by
    是具有无限重复性的特征值:由 特征化的无限集合(正交)特征函数
The eigenfunctions from (1) and (2) together are a basis for .
(1)和(2)中的特征函数一起构成 的基础。
Proof, part 1 (non-zero eigenvalues): Consider ; look for an eigenfunction
证明,第 1 部分(非零特征值):考虑 ;寻找一个特征函数
Derivation: Plug in this expression into the operator :
导出:将此表达式插入运算符 中:
where . Now set this equal to
处。现在将其设置为相等。
The coefficients on must match, leaving the linear system
系数必须匹配,使线性系统
so the eigenvalue problem for is equivalent to a matrix eigenvalue problem for an matrix. Assuming is invertible, the result follows.
因此, 的特征值问题等价于一个 矩阵的特征值问题。假设 是可逆的,结果就会得出。
Claim 2 (zero eigenvalue): We show that is always an eigenvalue with infinite multiplicity. Observe that
声明 2(零特征值):我们展示 始终是一个具有无限重复性的特征值。观察到
This must be true for all , so it follows that
这对所有 都必须是真实的,因此它遵循
That is, the set of eigenfunctions for is precisely the space of functions orthogonal to the span of the 's. But is infinite dimensional and the span of has dimension , so the orthogonal complement is infinite dimensional - this proves the claim. That is,
也就是说,对于 的特征函数集合恰好是与 的张成正交的函数空间。但 是无限维的,而 的张成维度为 ,因此正交补空间也是无限维的 - 这证明了这个断言。也就是说,
The fact that the basis for is countable (a sequence indexed by ) also follows from the fact that has this property. The eigenfunctions can be constructed using Gram-Schmidt (see example in subsection 2.1).
事实上, 的基础是可数的(由 索引的序列)也是因为 具有这个特性。 特征函数 可以使用 Gram-Schmidt 方法构建(请参见第 2.1 小节中的示例)。
2.1. Example (eigenfunctions). Define the (separable) kernel
2.1. 例子(特征函数)。定义(可分离)核
and consider the FIE of the first kind
考虑第一类的 FIE
The result says has non-zero eigenvalues. Look for an eigenfunction
结果显示 个非零特征值。寻找一个特征函数
then plug in and integrate to get
然后插入并集成以获得
which gives (equating coefficients of on the LHS/RHS as in (2.3))
这给出了(将 LHS/RHS 上的 的系数等同于(2.3)中的系数)
Plugging in the values from (2.4), the eigenvalue problem is
将(2.4)中的值代入,特征值问题是
Translating back to the integral equation with given by (2.5), the non-zero 's and 's are
将由(2.5)给出的积分方程翻译回来,非零
along with the zero eigenvalue and eigenfunctions .
随着零特征值和特征函数
Zero eigenvalue (details): For , use the characterization (2.2):
零特征值(详细信息):对于 ,使用特征描述(2.2):
First, we need to orthogonalize. Define and
首先,我们需要正交化。定义
It follows that if is any function then a zero eigenfunction is
根据这个结论,如果 是任何函数,那么零特征函数是
The whole set can be found using Gram-Schmidt, e.g. with . For instance,
整套可以使用 Gram-Schmidt 方法找到,例如,使用 。例如,
is an eigenfunction for (orthogonal to and ).
的特征函数(与 正交)。
2.2. Adjoint operator. The operator is not self-adjoint in general. To solve FIEs with an eigenfunction expansion, we need the adjoint and its eigenfunctions . To obtain it, let denote the inner product .
2.2. 伴随算子。一般情况下,算子 不是自伴的。为了用特征函数展开解决 FIEs 问题,我们需要伴随算子 及其特征函数 。为了获得它,让 表示 内积
We look for an integral operator such that
我们寻找一个积分算子 ,使得
To find the adjoint, carefully exchange integration order (pay attention to which of or is the 'integration variable' here!). Compute
为了找到伴随算子,仔细交换积分顺序(注意 哪个是“积分变量”!)。计算
Note the inner integration variable above is now and not . From this result, we see that
请注意上面的内部积分变量现在是 而不是 。从这个结果,我们可以看到
after swapping symbols for and . Comparing to , we have the following characterization for the adjoint:
在交换符号 后。与 相比,我们对伴随算子有以下描述:
FI operator adjoint: The FI operator of the first kind and its adjoint are
FI 运算符伴随:第一类 FI 运算符及其伴随是
i.e. the adjoint has kernel (the kernel of with the variables swapped). Moreover,
即伴随矩阵具有核 (即将变量交换的 的核)。此外,
That is, is self-adjoint if and only if the kernel is symmetric (e.g. ).
即,如果且仅当核对称时, 是自伴的(例如 )。

3. SolVing FIEs OF THE FIRST KIND (SEPARABLE)
3. 解决第一类(可分离)的一阶常微分方程

We are now equipped to solve
我们现在有能力解决
where has a separable kernel (1.5). Note that from (2.8), it follows that also has a separable kernel.
具有可分离核(1.5)时。请注意,根据(2.8),可以得出 也具有可分离核。
Thus the adjoint also has non-zero eigenvalues with eigenfunctions (same structure). Moreover, the 's and 's are bi-orthogonal. That is, for and the same for the 's and 's and between the two sets (e.g. for all .
因此,伴随矩阵 也具有 个非零特征值,其特征函数为 (结构相同)。此外, 是双正交的。也就是说, 对于 之间以及两组之间是相同的(例如 对于所有
Reminder: to get the coefficient of , take the inner product with , e.g.
提醒:要获得 的系数,取 的内积,例如。
Solving the FIE: Project by taking to get
解决 FIE:通过采取 来解决
We need to write and in terms of the eigenfunctions.
我们需要用特征函数来写
  • For the RHS (f): This is direct:
    对于 RHS (f):这是直接的
Let . Take the inner product with to get
。与 进行内积运算得到
The other coefficients will only be needed later.
其他系数只会在以后需要。
  • For the (Lu): First write
    对于 (卢):首先写
The second term is sent to zero by :
第二项被送到零
Taking the inner product with , we get
进行内积,我们得到
  • Combining: Equating the two parts, we find that
    结合:将这两部分等同起来,我们发现
Solvability: What about the 's? The adjoint has a zero eigenvalue, so we are in FAT case (B). A solvability condition decides between no solution or infinitely many solutions.
可解性: 的情况如何?伴随 有一个零特征值,所以我们处于 FAT 情况(B)。可解性条件决定了无解或无穷多解之间的选择。
To find this condition, project onto one a eigenfunction for , i.e. take the inner product of with one of the 's:
要找到这个条件,将一个特征函数投影到 上,即将 之一的内积取出:
Thus a solution exists only when has no component for any , i.e. if and only if
因此,只有当 对于任何 都没有 分量时,才存在解,即当且仅当
Summary of solution (separable FIE-1): If is of the form (3.4), the solution is
解决方案摘要(可分离 FIE-1):如果 的形式为(3.4),则解决方案是
and the 's are arbitrary. If is not of the form (3.4) then there is no solution.
的选择是任意的。如果 不是形式为(3.4)的话,那么就没有解。
3.1. The shortcut. There is a way to get around the full expansion. Recall that
3.1. 快捷方式。 有一种方法可以绕过完全展开。回想一下
i.e each eigenfunction (for non-zero ) is a linear combination of the 's. Then
即每个特征函数(对于非零 )都是 的线性组合。然后
It follows that we could anticipate the solution and guess
这意味着我们可以预料到解决方案并猜测
knowing that the result for will be in this form. We lose the bi-orthogonal structure (no eigenfunctions), but the 's are not needed to calculate the solution.
知道 的结果将以这种形式呈现。我们失去了双正交结构(没有特征函数),但不需要 来计算解决方案。
If is small, the shortcut is much easier (the linear system is small).
如果 很小,快捷方式会更容易(线性系统很小)。
3.2. Example: Return to the previous example (subsection 2.1),
3.2. 例子:回到前面的例子(第 2.1 小节),
with separable kernel 具有可分离核
and non-zero eigenvalues/functions
非零特征值/函数
along with the zero eigenvalue and eigenfunctions . Suppose the problem is
随着零特征值和特征函数 。假设问题是
Note that is always an eigenvalue, so we are in case (B) of the FAT. Here, the RHS is in the span of and (both linear combinations of and ), so there is a solution. It is unique up to an arbitrary sum of the form .
请注意, 总是一个特征值,所以我们处于 FAT 的情况(B)中。在这里,RHS 在 的张成空间中(都是 的线性组合),因此有解。它是唯一的,形式为 的任意和。
Direct method: Note that the kernel is symmetric here. Thus is self-adjoint and . Write the solution as
直接方法:注意这里的核是对称的。因此 是自伴的, 。将解写成
Take the inner product of the equation with :
将方程与 的内积
The coefficients can be computed from here; then
系数可以从这里计算;然后
for arbitrary 's (details not carried out here).
对于任意 的(这里未详细说明)。
Shortcut method: Instead look for the 'unique part' as a linear combination of 's:
快捷方法:而是寻找“独特部分”作为 的线性组合:
Plug into the equation and write as a linear system:
插入方程并写成线性系统:
so and . The solution is then (for arbitrary 's)
所以 。然后解决方案是(对于任意 的)。

4. FIEs OF THE SECOND KIND (STILL SEPARABLE)
第四种类型的外商独资企业(仍然可分离)

Now consider the FI operator of the second kind,
现在考虑第二类 FI 运算符
where is an FIE of the first kind with a separable kernel:
其中 是第一类具有可分离核的 FIE:
Note that the term added to only shifted the eigenvalues. The result:
请注意,添加到 项只是将特征值移动了。结果:
For the second kind: For the FIE of the second kind (4.1), the eigenfunctions are the same as and the eigenvalues are shifted by . That is, the eigenvalues of are
对于第二种情况:对于第二种情况的 FIE(4.1),特征函数与 相同,特征值偏移 。也就是说, 的特征值是
with the same eigenfunctions and .
具有相同的特征函数
It follows that has all non-zero eigenvalues unless is an eigenvalue of .
这意味着 具有所有非零特征值,除非 的特征值。
Now we solve the FIE
现在我们解决 FIE
under the assumption that
在假设下
If (4.3) holds then the FAT case (A) applies (since is non-zero) and there is a unique solution, unlike an FIE of the first kind.
如果(4.3)成立,则适用 FAT 情况(A)(因为 非零),并且存在唯一解,不同于第一类 FIE。
Direct method (not ideal): Expand and in terms of the eigenfunctions:
直接方法(不理想):根据特征函数展开
Now plug into the FIE (4.2) to get
现在插入 FIE(4.2)以获取
Equate this to (note that now ) to get the coefficients:
将此等同于 (注意现在 )以获得系数:
This can be continued, but there is a better shortcut, inspired by the FIE-1 case. The trick is that the 'infinite part' (with ) of the solution is really a multiple of , leaving only the 'finite part', which is a sum only over terms.
这可以继续,但有一个更好的捷径,灵感来自 FIE-1 案例。 技巧在于解决方案的“无限部分”(带有 )实际上是 的倍数,只留下“有限部分”,这只是 项的总和。
Practical note: The direct method leads to trivial equations (from orthogonality), but there are an infinite number of them. Moreover, the part is best avoided if we can get away with a solution containing only a finite sum!
实用笔记:直接方法导致微不足道的方程(来自正交性),但它们有无限多个。此外,如果我们可以用仅包含有限和的解决方案摆脱 部分,那将是最好的!

4.1. Shortcut (undetermined coefficients): Assume a solution of the form
4.1. 快捷方式(未定系数):假设解的形式

Since the kernel is separable, for any function is a linear combination of 's:
由于核是可分离的,对于任何函数 都是 的线性组合:
Now plug the guess (4.4) into and keep the part of separate from the rest. All the other terms, via rule (4.5), will give various linear combinations of 's. To be precise,
现在将猜测(4.4)插入 ,并将 部分与其余部分分开。根据规则(4.5),所有其他项将给出 的各种线性组合。准确地说,
Now plug in and collect all the terms and the leftover part:
现在插入并收集所有 项和剩下的 部分:
That is, the part must cancel, leaving just , so
也就是说, 部分必须取消,只留下
which is linear system for of the form . Now recall that under the assumptions made at the start, the FAT guarantees a unique solution, so we are done (the guess is a solution, so it is the unique solution).
这是形式为 的线性系统 。现在回想起在开始时所做的假设,FAT 保证了唯一解,所以我们完成了(猜测是一个解,因此它是唯一解)。
4.2. Example: again, return to the example. Now let
4.2. 例子:再次回到例子。现在让
The eigenvalues of are and , with the same eigenfunctions as computer earlier. Consider
的特征值为 ,与 计算机早期的特征函数相同。考虑
Look for a solution
寻找解决方案
After following the process (plug everything in), and
完成 (插入所有设备),
This is the unique solution! Note the deals neatly with the RHS; no infinite sum required. The downside is that the algebra for and is messy, but it is a small linear system, and a computer algebra package has no trouble with it.
这是独特的解决方案!请注意 巧妙地处理了右手边;不需要无限求和。不足之处在于 的代数运算很混乱,但这是一个小的线性系统,计算代数软件可以轻松处理。

5. WHAT IF THE KERNEL IS NON-SEPARABLE?
5. 如果核是不可分离的呢?

For a non-separable kernel such as
对于非可分离的核函数,例如
the theory is different. More conditions are required to ensure that the eigenvalue problem behaves well. If the kernel is 'nice', there is an infinite set of eigenvalues with structure similar to Sturm-Liouville theory. As for Sturm-Liouville operators the general idea is that
理论不同。需要更多条件来确保特征值问题表现良好。如果核是“好的”,则存在一个无限集的特征值,其结构类似于斯图姆-利乌维尔理论。至于斯图姆-利乌维尔算子的一般想法
self-adjoint is 'nice' good properties for eigenfunctions/values.
自伴 是对特征函数/值有良好性质的“好”
For integral equations, Hilbert-Schmidt theory provides the answer for what is required to be 'nice' and what 'good properties' result. The Hilbert-Schmidt condition is
对于积分方程,希尔伯特-施密特理论提供了所需的“良好”条件和“良好性质”结果的答案。希尔伯特-施密特条件是
which guarantees that the operator is 'nice' (precisely, a compact operator on . Hilbert-Schmidt theory then says that if
确保运算符 是“好的”(准确地说,是 上的紧算子。希尔伯特-施密特理论随后指出,如果
satisfies the conditions
满足条件
  1. is self-adjoint (in )
    是自伴的(在
  2. is not separable (although the separable case is similar)
    不可分(尽管可分的情况类似)
  3. The Hilbert-Schmidt condition (5.2) holds ( is 'compact') then the eigenvalue problem has nice properties:
    希尔伯特-施密特条件(5.2)成立( 是“紧致的”)则特征值问题具有良好的性质:
  • The eigenvalues are real
    特征值 是实数
  • The eigenvalues are a discrete sequence, each with finite multiplicity:
    特征值是一个离散序列,每个特征值都具有有限重数:
  • The eigenfunctions are an orthogonal basis for if
    特征函数 的正交基,如果
  • The Fredholm Alternative and eigenfunction expansions for apply (in the same way that we used them for BVPs with Sturm-Liouville theory)
    Fredholm 替代和特征函数展开适用于 (就像我们在 Sturm-Liouville 理论中用于 BVPs 一样)
For further reading, see the references at the start of the notes. We will study non-separable kernels in a different way when addressing the Fourier and Laplace transforms.
进一步阅读,请参阅注释开头的参考资料。在讨论傅里叶和拉普拉斯变换时,我们将以不可分离的核心进行研究。

  1. In functional analysis terms, it is a 'separable Hilbert space'.
    在功能分析术语中,它是一个“可分的希尔伯特空间”。
  2. The computations are messy and not included here.
    计算复杂且未包含在此处。
    Both the theory for integral operators and Sturm-Liouville theory are part of a more general theory; the structure comes from the theory of compact operators on a Hilbert space (the 'spectral theorem for compact operators').
    积分算子理论和斯图姆-利乌维尔理论都是更一般理论的一部分;结构来自于希尔伯特空间上紧致算子的理论(“紧致算子的谱定理”)。