University Calculus · Calculus IV大学微积分 · 微积分 IV

Unit D6: The Laplace Transform

An integral transform that turns constant-coefficient differential equations into algebra, then turns the answer back into a function of time.一种积分变换,将常系数微分方程转化为代数方程,再将代数解还原为时域函数。

Calculus IV ODEs Differential Equations MIT 18.03 / GT 2552
Read me first. This unit assumes you can already solve linear constant-coefficient ODEs by hand and are comfortable with partial fractions. We build the transform table from the definition, then use it to solve initial value problems, handle piecewise and impulsive forcing through step functions and the Dirac delta, and close with convolution. Keep the transform table beside you; almost every problem reduces to matching an entry.
阅读须知。 本单元假设你已能手算线性常系数常微分方程,并熟悉部分分式(partial fractions)分解。我们从定义出发建立变换表,再用拉普拉斯变换(Laplace transform)求解初值问题(IVP),通过阶跃函数和狄拉克 δ 函数(Dirac delta)处理分段与冲激激励,最后介绍卷积(convolution)。建议随时备好变换表,几乎每道题都归结为对表查找。

Definition and Existence定义与存在性

Key idea. The Laplace transform converts a function of time $t$ into a function of a complex frequency variable $s$ by integrating against a decaying exponential. It turns differentiation into multiplication, so a linear constant-coefficient ODE becomes an algebraic equation in $s$.
核心思路。 拉普拉斯变换(Laplace transform)将时域函数 $t$ 通过与衰减指数的积分,转换为复频率变量 $s$ 的函数。它将微分运算变为乘法,从而将线性常系数常微分方程(ODE)化为关于 $s$ 的代数方程。
Definition of the Laplace transform拉普拉斯变换的定义
$$ \mathcal{L}\{f(t)\}(s) = F(s) = \int_{0}^{\infty} e^{-st} f(t)\, dt, $$

The integral is improper, so $F(s)$ is defined only for those $s$ where the integral converges. We say $f$ is of exponential order if there are constants $M > 0$ and $a$ with $|f(t)| \le M e^{at}$ for all large $t$. Together with piecewise continuity on every finite interval, this guarantees existence.

该积分是反常积分,$F(s)$ 仅在积分收敛的 $s$ 值处有定义。若存在常数 $M>0$ 和 $a$,使得对所有足够大的 $t$ 有 $|f(t)|\le Me^{at}$,则称 $f$ 为指数阶(of exponential order)函数。结合在每个有限区间上的分段连续(piecewise continuous)条件,即可保证变换的存在性。

Existence theorem存在性定理
$$ f \text{ piecewise continuous on } [0,\infty),\quad |f(t)| \le M e^{at} \;\Longrightarrow\; F(s) \text{ converges for } s > a. $$

Two structural facts make the transform useful: it is linear, and bounded transforms vanish at infinity. Linearity follows immediately from linearity of the integral.

变换有两个关键性质:线性性和有界变换在无穷处趋于零。线性性直接由积分的线性性得出。

Linearity线性性
$$ \mathcal{L}\{\alpha f(t) + \beta g(t)\} = \alpha F(s) + \beta G(s). $$
Worked Example 1.1: transform of a constant and of $e^{at}$例题 1.1:常数和 $e^{at}$ 的变换

For $f(t) = 1$ we integrate directly, valid for $s > 0$:

$$ \mathcal{L}\{1\} = \int_{0}^{\infty} e^{-st}\, dt = \left[ -\tfrac{1}{s} e^{-st} \right]_{0}^{\infty} = \frac{1}{s}. $$

For $f(t) = e^{at}$ the exponentials combine, and convergence requires $s > a$:

$$ \mathcal{L}\{e^{at}\} = \int_{0}^{\infty} e^{-(s-a)t}\, dt = \frac{1}{s-a}, \qquad s > a. $$

对 $f(t)=1$,直接积分($s>0$):

$$ \mathcal{L}\{1\} = \int_{0}^{\infty} e^{-st}\, dt = \left[ -\tfrac{1}{s} e^{-st} \right]_{0}^{\infty} = \frac{1}{s}. $$

对 $f(t)=e^{at}$,指数合并,收敛条件 $s>a$:

$$ \mathcal{L}\{e^{at}\} = \int_{0}^{\infty} e^{-(s-a)t}\, dt = \frac{1}{s-a}, \quad s>a. $$
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Worked Example 1.2: transform of $t$ from first principles例题 1.2:从第一性原理求 $t$ 的变换

We compute $\mathcal{L}\{t\}$ directly from the definition rather than quoting the table, valid for $s > 0$. Integrate by parts with $u = t$ and $dv = e^{-st}\,dt$, so $du = dt$ and $v = -\tfrac{1}{s}e^{-st}$:

$$ \mathcal{L}\{t\} = \int_{0}^{\infty} t\, e^{-st}\, dt = \left[ -\frac{t}{s} e^{-st} \right]_{0}^{\infty} + \frac{1}{s}\int_{0}^{\infty} e^{-st}\, dt. $$

For $s > 0$ the boundary term vanishes at both ends: at $t = 0$ the factor $t$ is zero, and as $t \to \infty$ the exponential $e^{-st}$ dominates the linear growth, so $t\,e^{-st} \to 0$. The remaining integral is $\mathcal{L}\{1\} = 1/s$, giving

$$ \mathcal{L}\{t\} = \frac{1}{s}\cdot\frac{1}{s} = \frac{1}{s^{2}}. $$

This matches $n!/s^{n+1}$ with $n = 1$, and the same integration-by-parts step repeated $n$ times produces the full power rule $\mathcal{L}\{t^{n}\} = n!/s^{n+1}$.

不查表,直接由定义计算。令 $u=t$,$dv=e^{-st}dt$ 分部积分($s>0$):

$$ \mathcal{L}\{t\} = \int_{0}^{\infty} t\, e^{-st}\, dt = \left[ -\frac{t}{s} e^{-st} \right]_{0}^{\infty} + \frac{1}{s}\int_{0}^{\infty} e^{-st}\, dt = \frac{1}{s^{2}}. $$

与 $n!/s^{n+1}$($n=1$)吻合;重复分部积分即得 $\mathcal{L}\{t^{n}\}=n!/s^{n+1}$。

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Worked Example 1.3: a function that is not of exponential order例题 1.3:非指数阶函数的例子

The existence theorem gives a sufficient condition, not a necessary one, so it is worth seeing where it fails. Consider $f(t) = e^{t^{2}}$. For any fixed constant $a$, the ratio

$$ \frac{e^{t^{2}}}{e^{at}} = e^{t^{2} - at} \to \infty \quad\text{as } t \to \infty, $$

since $t^{2} - at \to \infty$. No choice of $M$ and $a$ can satisfy $|f(t)| \le M e^{at}$ for all large $t$, so $f$ is not of exponential order. Indeed the integral $\int_{0}^{\infty} e^{-st} e^{t^{2}}\, dt$ diverges for every $s$ because the integrand $e^{t^{2}-st} \to \infty$. By contrast $f(t) = t^{100}$ is of exponential order, because any polynomial is eventually dominated by $e^{t}$, so its transform exists for $s > 0$.

存在性定理给出充分条件。考察 $f(t)=e^{t^{2}}$:对任意 $a$,$e^{t^{2}-at}\to\infty$,故 $f$ 非指数阶,变换不存在。反之,$t^{100}$ 是指数阶,其变换在 $s>0$ 存在。

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Going deeper: why bounded transforms satisfy $F(s) \to 0$ as $s \to \infty$深入探讨:为何有界变换满足 $F(s)\to 0$($s\to\infty$)

Suppose $|f(t)| \le M e^{at}$. For $s > a$ we bound the transform by pulling the absolute value inside the integral:

$$ |F(s)| \le \int_{0}^{\infty} e^{-st} |f(t)|\, dt \le M \int_{0}^{\infty} e^{-(s-a)t}\, dt = \frac{M}{s-a}. $$

As $s \to \infty$ the right side tends to $0$, so every transform of an exponential-order function decays to $0$. A consequence: a rational function with numerator degree at least the denominator degree (for instance a constant or a polynomial in $s$) cannot be the Laplace transform of such a function.

由 $\mathcal{L}\{\sin 5t\}=\dfrac{5}{s^{2}+25}$,第一平移定理($a=2$)将 $s$ 换为 $s-2$:

$$ \mathcal{L}\{e^{2t}\sin 5t\} = \frac{5}{(s-2)^{2}+25}. $$
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One more structural remark sets up everything that follows. The transform is an integral against a parameter $s$, so it inherits the good behaviour of integrals: it is linear, it respects limits under the mild hypothesis of exponential order, and it is injective on continuous functions. Injectivity is what lets us speak of the inverse transform later, and exponential order is the recurring admission ticket. Almost every theorem in this unit carries the silent assumption that the functions involved are piecewise continuous and of exponential order, which is exactly the class of inputs that arise from constant-coefficient ODEs with reasonable forcing.

Common error. Students often write $\mathcal{L}\{e^{at}\} = 1/(s-a)$ with no restriction on $s$, or worse plug in $s = a$ to "evaluate" it. The formula is only valid on the half line $s > a$, exactly the region where the defining integral converges. At $s = a$ the integrand is $e^{0} = 1$ and the integral $\int_0^\infty 1\,dt$ diverges. Always carry the region of convergence, because it tells you, for instance, that two different functions can never share a transform on overlapping half lines (uniqueness), and it flags when an answer cannot possibly be a Laplace transform.
For which values of $s$ does $\mathcal{L}\{e^{3t}\} = \dfrac{1}{s-3}$ hold?
1.1
All real $s$
$s > 3$
$s < 3$
$s > 0$
Correct. The defining integral $\int_0^\infty e^{-(s-3)t}\,dt$ converges precisely when $s - 3 > 0$, that is $s > 3$.
The integral $\int_0^\infty e^{-(s-3)t}\,dt$ converges only when the exponent is negative for large $t$, requiring $s - 3 > 0$.
A function $f$ satisfies $|f(t)| \le M e^{at}$ and is piecewise continuous on $[0,\infty)$. What does the existence theorem conclude?
1.2
$F(s)$ exists for all $s$
$F(s)$ never exists
$F(s)$ converges for $s > a$
$F(s)$ converges for $s < a$
Correct. Exponential order with growth rate $a$ plus piecewise continuity guarantees convergence of the transform for $s > a$.
Exponential order of rate $a$ guarantees convergence on the half line $s > a$, not for all $s$.

Transforms of Common Functions常用函数的变换

Key idea. A short table of transforms, combined with linearity and a few shift rules, covers nearly every function that arises in constant-coefficient ODEs. The table is built once by direct integration and then reused.
Core table (each valid on its half line of $s$)
$$ \mathcal{L}\{t^{n}\} = \frac{n!}{s^{n+1}}, \quad \mathcal{L}\{e^{at}\} = \frac{1}{s-a}, \quad \mathcal{L}\{\cos bt\} = \frac{s}{s^{2}+b^{2}}, \quad \mathcal{L}\{\sin bt\} = \frac{b}{s^{2}+b^{2}}. $$

The first frequency shift rule explains the whole table at once: multiplying $f$ by $e^{at}$ shifts its transform.

First shift theorem (s-shift)
$$ \mathcal{L}\{e^{at} f(t)\} = F(s-a). $$

So $\mathcal{L}\{e^{at}\cos bt\}$ is just the cosine transform with $s$ replaced by $s-a$. A second tool, multiplication by $t$, corresponds to differentiating in $s$.

Multiplication by $t^n$
$$ \mathcal{L}\{t^{n} f(t)\} = (-1)^{n} \frac{d^{n}}{ds^{n}} F(s). $$
Worked Example 2.1: transform of $e^{2t}\sin 5t$例题 2.1:$e^{2t}\sin 5t$ 的变换

Start from $\mathcal{L}\{\sin 5t\} = \dfrac{5}{s^{2}+25}$. Apply the first shift theorem with $a = 2$, replacing $s$ by $s-2$:

$$ \mathcal{L}\{e^{2t}\sin 5t\} = \frac{5}{(s-2)^{2}+25}. $$

由 $\mathcal{L}\{\sin 5t\}=\dfrac{5}{s^{2}+25}$,第一平移定理($a=2$)将 $s$ 换为 $s-2$:

$$ \mathcal{L}\{e^{2t}\sin 5t\} = \frac{5}{(s-2)^{2}+25}. $$
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Worked Example 2.2: transform of $t\cos 3t$例题 2.2:$t\cos 3t$ 的变换

Use multiplication by $t$ with $F(s) = \dfrac{s}{s^{2}+9}$ and $n = 1$:

$$ \mathcal{L}\{t\cos 3t\} = -\frac{d}{ds}\left( \frac{s}{s^{2}+9} \right). $$

Differentiating the quotient gives

$$ \frac{d}{ds}\left( \frac{s}{s^{2}+9} \right) = \frac{(s^{2}+9) - s(2s)}{(s^{2}+9)^{2}} = \frac{9 - s^{2}}{(s^{2}+9)^{2}}, $$ $$ \mathcal{L}\{t\cos 3t\} = \frac{s^{2}-9}{(s^{2}+9)^{2}}. $$

$t$ 乘法法则:$\mathcal{L}\{t\cos 3t\}=-\dfrac{d}{ds}\dfrac{s}{s^{2}+9}$。对商式求导:

$$ \mathcal{L}\{t\cos 3t\} = \frac{s^{2}-9}{(s^{2}+9)^{2}}. $$
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Worked Example 2.3: transform of $e^{-t}(t^{2} + \cos 2t)$例题 2.3:$e^{-t}(t^{2}+\cos 2t)$ 的变换

Linearity lets us split the bracket, then the first shift theorem with $a = -1$ acts on each piece by sending $s \mapsto s + 1$. Start from the unshifted transforms $\mathcal{L}\{t^{2}\} = 2/s^{3}$ and $\mathcal{L}\{\cos 2t\} = s/(s^{2}+4)$. Replacing $s$ by $s+1$ in each:

$$ \mathcal{L}\{e^{-t} t^{2}\} = \frac{2}{(s+1)^{3}}, \qquad \mathcal{L}\{e^{-t}\cos 2t\} = \frac{s+1}{(s+1)^{2}+4}. $$

Adding the two results gives the full transform:

$$ \mathcal{L}\{e^{-t}(t^{2} + \cos 2t)\} = \frac{2}{(s+1)^{3}} + \frac{s+1}{(s+1)^{2}+4}. $$

Notice the order of operations: apply linearity first to break the sum apart, then apply the shift to each transform separately. The shift acts on the whole transform of each summand, including the numerator, which is why the cosine numerator becomes $s+1$ rather than staying $s$.

线性性拆括号,再用第一平移定理($a=-1$,$s\to s+1$):

$$ \mathcal{L}\{e^{-t}(t^{2}+\cos 2t)\} = \frac{2}{(s+1)^{3}} + \frac{s+1}{(s+1)^{2}+4}. $$
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Going deeper: deriving the sine and cosine transforms together深入探讨:同时推导正弦和余弦变换

Rather than two separate integration-by-parts marathons, compute both at once through the complex exponential. For $s > 0$,

$$ \mathcal{L}\{e^{ibt}\} = \int_{0}^{\infty} e^{-st} e^{ibt}\, dt = \int_{0}^{\infty} e^{-(s-ib)t}\, dt = \frac{1}{s-ib}, $$

valid because $|e^{-(s-ib)t}| = e^{-st} \to 0$. Rationalize by multiplying top and bottom by the conjugate $s + ib$:

$$ \frac{1}{s-ib} = \frac{s+ib}{s^{2}+b^{2}} = \frac{s}{s^{2}+b^{2}} + i\,\frac{b}{s^{2}+b^{2}}. $$

Since $e^{ibt} = \cos bt + i\sin bt$ and the transform is linear, the real part is $\mathcal{L}\{\cos bt\}$ and the imaginary part is $\mathcal{L}\{\sin bt\}$. Reading off the two parts gives both table entries simultaneously:

$$ \mathcal{L}\{\cos bt\} = \frac{s}{s^{2}+b^{2}}, \qquad \mathcal{L}\{\sin bt\} = \frac{b}{s^{2}+b^{2}}. $$

拆分为余弦和正弦两项($b=2$):

$$ \frac{3s+2}{s^{2}+4} = 3\cdot\frac{s}{s^{2}+4} + 1\cdot\frac{2}{s^{2}+4}. $$ $$ \mathcal{L}^{-1}\left\{\frac{3s+2}{s^{2}+4}\right\} = 3\cos 2t + \sin 2t. $$
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Common error. When applying the first shift theorem to $e^{at}\cos bt$, a frequent slip is to shift only the denominator and leave the numerator as $s$, writing $\dfrac{s}{(s-a)^{2}+b^{2}}$. The rule $\mathcal{L}\{e^{at}f(t)\} = F(s-a)$ replaces every $s$ in $F(s)$, including the numerator, so the correct transform is $\dfrac{s-a}{(s-a)^{2}+b^{2}}$. A clean way to avoid the mistake is to write $F(s)$ as a single expression, then substitute the symbol $s-a$ for $s$ literally before simplifying.
What is $\mathcal{L}\{t^{3}\}$?
2.1
$\dfrac{6}{s^{4}}$
$\dfrac{3}{s^{4}}$
$\dfrac{6}{s^{3}}$
$\dfrac{1}{s^{4}}$
Correct. With $n = 3$, $\mathcal{L}\{t^{n}\} = n!/s^{n+1} = 3!/s^{4} = 6/s^{4}$.
Use $\mathcal{L}\{t^{n}\} = n!/s^{n+1}$. For $n = 3$ this is $3!/s^{4} = 6/s^{4}$.
Using the first shift theorem, $\mathcal{L}\{e^{-t}\cos 4t\}$ equals which expression?
2.2
$\dfrac{s}{s^{2}+16}$
$\dfrac{s-1}{(s-1)^{2}+16}$
$\dfrac{4}{(s+1)^{2}+16}$
$\dfrac{s+1}{(s+1)^{2}+16}$
Correct. Replace $s$ by $s - a = s - (-1) = s+1$ in $\mathcal{L}\{\cos 4t\} = s/(s^{2}+16)$.
The shift is $s \mapsto s - a$ with $a = -1$, so $s \mapsto s+1$ throughout the cosine transform $s/(s^{2}+16)$.

The Inverse Transform逆变换

Key idea. To recover $f(t)$ from $F(s)$ we read the transform table backward. The main working tool is partial fractions, which splits a rational $F(s)$ into pieces each of which matches a table entry.
Inverse is linear
$$ \mathcal{L}^{-1}\{\alpha F(s) + \beta G(s)\} = \alpha f(t) + \beta g(t). $$

Uniqueness justifies the phrase "the" inverse: if $f$ and $g$ are continuous on $[0,\infty)$ and have the same transform, then $f = g$ (Lerch's theorem). Repeated and complex linear factors call for two standard patterns.

Strategy for any rational $F(s) = P(s)/Q(s)$ runs in a fixed order. First confirm the degree of $P$ is strictly less than the degree of $Q$; if not, do polynomial division first, since a proper rational part is what the table can match. Next factor $Q$ completely over the reals into linear and irreducible-quadratic factors. Then allocate partial-fraction terms: one term per power of each repeated linear factor, and a linear numerator $\frac{As+B}{\cdots}$ over each irreducible quadratic. Finally match each piece to a table entry, completing the square whenever a quadratic is shifted. The cover-up method, evaluating both sides at the root of a factor, is the fastest way to pin down the constants over distinct linear factors.

Two patterns worth memorizing
$$ \mathcal{L}^{-1}\left\{ \frac{1}{(s-a)^{2}} \right\} = t\, e^{at}, \qquad \mathcal{L}^{-1}\left\{ \frac{1}{(s-a)^{2}+b^{2}} \right\} = \frac{1}{b}\, e^{at}\sin bt. $$
Worked Example 3.1: inverse of $\dfrac{3s+2}{s^{2}+4}$例题 3.1:$\dfrac{3s+2}{s^{2}+4}$ 的逆变换

Split into a cosine piece and a sine piece:

$$ \frac{3s+2}{s^{2}+4} = 3\cdot\frac{s}{s^{2}+4} + 1\cdot\frac{2}{s^{2}+4}. $$

Each term is a table entry with $b = 2$:

$$ \mathcal{L}^{-1}\left\{ \frac{3s+2}{s^{2}+4} \right\} = 3\cos 2t + \sin 2t. $$

拆分为余弦和正弦两项($b=2$):

$$ \frac{3s+2}{s^{2}+4} = 3\cdot\frac{s}{s^{2}+4} + 1\cdot\frac{2}{s^{2}+4}. $$ $$ \mathcal{L}^{-1}\left\{\frac{3s+2}{s^{2}+4}\right\} = 3\cos 2t + \sin 2t. $$
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Worked Example 3.2: partial fractions for $\dfrac{s+7}{(s-1)(s+2)}$例题 3.2:$\dfrac{s+7}{(s-1)(s+2)}$ 的部分分式

Write $\dfrac{s+7}{(s-1)(s+2)} = \dfrac{A}{s-1} + \dfrac{B}{s+2}$. Clearing denominators gives $s+7 = A(s+2) + B(s-1)$. Set $s = 1$: $8 = 3A$, so $A = \tfrac{8}{3}$. Set $s = -2$: $5 = -3B$, so $B = -\tfrac{5}{3}$. Therefore

$$ \mathcal{L}^{-1}\left\{ \frac{s+7}{(s-1)(s+2)} \right\} = \frac{8}{3} e^{t} - \frac{5}{3} e^{-2t}. $$

令 $A(s+2)+B(s-1)=s+7$。$s=1$:$A=8/3$;$s=-2$:$B=-5/3$。故

$$ f(t) = \tfrac{8}{3}e^{t} - \tfrac{5}{3}e^{-2t}. $$
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Worked Example 3.3: a repeated linear factor, $\dfrac{s}{(s+1)^{2}(s-2)}$例题 3.3:重线性因子,$\dfrac{s}{(s+1)^{2}(s-2)}$

A repeated factor $(s+1)^{2}$ needs two terms in the decomposition, one for each power up to the multiplicity:

$$ \frac{s}{(s+1)^{2}(s-2)} = \frac{A}{s+1} + \frac{B}{(s+1)^{2}} + \frac{C}{s-2}. $$

Clear denominators: $s = A(s+1)(s-2) + B(s-2) + C(s+1)^{2}$. Set $s = -1$: $-1 = B(-3)$, so $B = \tfrac{1}{3}$. Set $s = 2$: $2 = C(9)$, so $C = \tfrac{2}{9}$. To find $A$, compare $s^{2}$ coefficients: $0 = A + C$, so $A = -\tfrac{2}{9}$. Now invert term by term, using $\mathcal{L}^{-1}\{1/(s-a)\} = e^{at}$ and $\mathcal{L}^{-1}\{1/(s-a)^{2}\} = t e^{at}$:

$$ \mathcal{L}^{-1}\left\{ \frac{s}{(s+1)^{2}(s-2)} \right\} = -\frac{2}{9} e^{-t} + \frac{1}{3} t e^{-t} + \frac{2}{9} e^{2t}. $$

重因子 $(s+1)^{2}$ 需两项:$A/(s+1)+B/(s+1)^{2}+C/(s-2)$。求解得 $B=-1/3$,$C=2/9$,$A=-2/9$,故

$$ f(t) = -\tfrac{2}{9}e^{-t} - \tfrac{1}{3}te^{-t} + \tfrac{2}{9}e^{2t}. $$
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Going deeper: completing the square to invert an irreducible quadratic深入探讨:配方法对不可约二次分母求逆变换

When a denominator is an irreducible quadratic such as $s^{2} + 2s + 5$, do not force real partial fractions. Complete the square to expose a shifted sine or cosine. Take

$$ \frac{s+3}{s^{2}+2s+5} = \frac{s+3}{(s+1)^{2}+4}. $$

Match the shift $a = -1$ and frequency $b = 2$. Rewrite the numerator in terms of $(s+1)$ so the cosine and sine patterns appear cleanly:

$$ \frac{s+3}{(s+1)^{2}+4} = \frac{(s+1)}{(s+1)^{2}+4} + \frac{2}{(s+1)^{2}+4}. $$

The first piece inverts to $e^{-t}\cos 2t$ and the second, with the constant $2 = b$, to $e^{-t}\sin 2t$. Hence

$$ \mathcal{L}^{-1}\left\{ \frac{s+3}{s^{2}+2s+5} \right\} = e^{-t}\cos 2t + e^{-t}\sin 2t. $$

The general moral: an irreducible quadratic always pairs with the shifted sine and cosine family, and completing the square is the bridge from the algebra to the table.

代入 $y(0)=1$,$y'(0)=0$ 取变换,整理得代数方程,部分分式后取逆变换得 $y(t)$。

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Common error. A repeated factor $(s-a)^{2}$ is frequently given just a single term $\dfrac{A}{(s-a)^{2}}$. That decomposition is incomplete and the algebra will be inconsistent: a factor of multiplicity $m$ requires a separate term for every power $\dfrac{A_1}{s-a} + \dfrac{A_2}{(s-a)^{2}} + \cdots + \dfrac{A_m}{(s-a)^{m}}$. Omitting the lower-power terms is the single most common cause of a partial-fraction setup that has no solution. Count the multiplicity, then allow that many constants.
What is $\mathcal{L}^{-1}\left\{ \dfrac{1}{(s-4)^{2}} \right\}$?
3.1
$e^{4t}$
$t\, e^{-4t}$
$t\, e^{4t}$
$\tfrac{1}{2} t^{2} e^{4t}$
Correct. The pattern $1/(s-a)^{2}$ inverts to $t e^{at}$, here with $a = 4$.
A repeated linear factor $1/(s-a)^{2}$ inverts to $t e^{at}$; with $a = 4$ this is $t e^{4t}$.
To invert $\dfrac{2}{(s+1)^{2}+9}$, which table entry applies?
3.2
$\cos$ with a shift, giving $e^{-t}\cos 3t$
$\sin$ with a shift, giving $\tfrac{2}{3} e^{-t}\sin 3t$
a repeated factor, giving $t e^{-t}$
a constant, giving $2 e^{-t}$
Correct. With $a = -1$, $b = 3$, $\mathcal{L}^{-1}\{1/((s-a)^{2}+b^{2})\} = \tfrac{1}{b} e^{at}\sin bt$, and the factor $2$ gives $\tfrac{2}{3} e^{-t}\sin 3t$.
A numerator with no $s$ matches the sine pattern $1/((s-a)^{2}+b^{2}) \mapsto \tfrac{1}{b} e^{at}\sin bt$, here $\tfrac{2}{3} e^{-t}\sin 3t$.

Solving Initial Value Problems求解初值问题

Key idea. The transform of a derivative folds the initial data directly into an algebraic equation. Transform the whole ODE, solve for $F(s)$, then invert. Initial conditions enter at the start rather than as constants fixed at the end.
Transforms of derivatives
$$ \mathcal{L}\{y'\} = sY(s) - y(0), \qquad \mathcal{L}\{y''\} = s^{2}Y(s) - s\,y(0) - y'(0). $$

The three step recipe is: (1) apply $\mathcal{L}$ to each term, inserting the initial values; (2) solve the resulting algebraic equation for $Y(s)$; (3) take $\mathcal{L}^{-1}$, using partial fractions as needed.

Worked Example 4.1: solve $y'' + 4y = 0$, $y(0) = 2$, $y'(0) = 0$例题 4.1:求解 $y''+4y=0$,$y(0)=2$,$y'(0)=0$

Transform every term, substituting the initial data:

$$ s^{2}Y - s(2) - 0 + 4Y = 0 \;\Longrightarrow\; (s^{2}+4)Y = 2s. $$

Solve for $Y$ and invert:

$$ Y(s) = \frac{2s}{s^{2}+4}, \qquad y(t) = 2\cos 2t. $$

代入初始条件取变换:$(s^{2}+4)Y=2s$,故

$$ y(t) = 2\cos 2t. $$
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Worked Example 4.2: a nonhomogeneous IVP, $y'' - 3y' + 2y = e^{3t}$, $y(0)=1$, $y'(0)=0$例题 4.2:非齐次初值问题,$y''-3y'+2y=e^{3t}$,$y(0)=1$,$y'(0)=0$

Transform every term. Use $\mathcal{L}\{y''\} = s^{2}Y - s y(0) - y'(0)$, $\mathcal{L}\{y'\} = sY - y(0)$, and $\mathcal{L}\{e^{3t}\} = 1/(s-3)$:

$$ \big(s^{2}Y - s - 0\big) - 3\big(sY - 1\big) + 2Y = \frac{1}{s-3}. $$

Collect the $Y$ terms and the constants. The characteristic polynomial factors as $s^{2}-3s+2 = (s-1)(s-2)$:

$$ (s-1)(s-2)\,Y = s - 3 + \frac{1}{s-3} = \frac{(s-3)^{2}+1}{s-3} = \frac{s^{2}-6s+10}{s-3}. $$

Hence $Y(s) = \dfrac{s^{2}-6s+10}{(s-1)(s-2)(s-3)}$. Decompose: $\dfrac{A}{s-1}+\dfrac{B}{s-2}+\dfrac{C}{s-3}$. Cover-up at $s=1$: $\dfrac{1-6+10}{(-1)(-2)} = \dfrac{5}{2}=A$. At $s=2$: $\dfrac{4-12+10}{(1)(-1)} = \dfrac{2}{-1}=-2=B$. At $s=3$: $\dfrac{9-18+10}{(2)(1)} = \dfrac{1}{2}=C$. Inverting,

$$ y(t) = \frac{5}{2} e^{t} - 2 e^{2t} + \frac{1}{2} e^{3t}. $$

The terms $e^{t}$ and $e^{2t}$ are the homogeneous part fixed by the initial data, and $\tfrac{1}{2}e^{3t}$ is the particular response to the forcing, all produced in one pass.

代入 $y(0)=1$,$y'(0)=0$ 取变换,整理得代数方程,部分分式后取逆变换得 $y(t)$。

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Worked Example 4.3: a first-order IVP, $y' + 2y = 6$, $y(0) = 1$例题 4.3:一阶初值问题,$y'+2y=6$,$y(0)=1$

Transform: $sY - y(0) + 2Y = 6/s$, that is $(s+2)Y = 1 + 6/s = (s+6)/s$. So

$$ Y(s) = \frac{s+6}{s(s+2)} = \frac{A}{s} + \frac{B}{s+2}. $$

Cover-up at $s = 0$: $A = 6/2 = 3$. At $s = -2$: $B = 4/(-2) = -2$. Therefore

$$ y(t) = 3 - 2 e^{-2t}. $$

As a check, $y(0) = 3 - 2 = 1$ and as $t \to \infty$ the solution settles to the steady state $y = 3$, the value where $y' = 0$ forces $2y = 6$.

代入 $y(0)=1$:$(s+2)Y=(s+6)/s$。部分分式:$A=3$,$B=-2$,故 $y(t)=3-2e^{-2t}$。

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Going deeper: derivation of $\mathcal{L}\{y'\} = sY(s) - y(0)$深入探讨:$\mathcal{L}\{y'\}=sY(s)-y(0)$ 的推导

Apply the definition and integrate by parts with $u = e^{-st}$, $dv = y'(t)\,dt$:

$$ \mathcal{L}\{y'\} = \int_{0}^{\infty} e^{-st} y'(t)\, dt = \Big[ e^{-st} y(t) \Big]_{0}^{\infty} + s\int_{0}^{\infty} e^{-st} y(t)\, dt. $$

If $y$ is of exponential order then $e^{-st}y(t) \to 0$ as $t \to \infty$ for large $s$, so the boundary term is $0 - y(0) = -y(0)$. The remaining integral is $sY(s)$, giving $\mathcal{L}\{y'\} = sY(s) - y(0)$. Iterating the rule on $y''=(y')'$ and substituting the first-derivative formula produces $\mathcal{L}\{y''\} = s^{2}Y - s\,y(0) - y'(0)$, and induction gives $\mathcal{L}\{y^{(n)}\} = s^{n}Y - s^{n-1}y(0) - \cdots - y^{(n-1)}(0)$.

$f(t)=t^{2}$,$\mathcal{L}\{t^{2}\}=2/s^{3}$。第二平移定理($c=2$):

$$ \mathcal{L}\{u_{2}(t)(t-2)^{2}\} = \frac{2e^{-2s}}{s^{3}}. $$
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Common error. When transforming $y''$, students often forget the $y'(0)$ term or attach the initial values to the wrong power of $s$, writing $s^{2}Y - y(0) - s\,y'(0)$. The correct pattern is $\mathcal{L}\{y''\} = s^{2}Y - s\,y(0) - y'(0)$: the higher power of $s$ multiplies the lower-order initial value $y(0)$, and the bare constant is $y'(0)$. A reliable mnemonic is that the exponents on $s$ count down from $n-1$ while the derivative order of the initial data counts up from $0$.
After transforming $y'' + y = 0$ with $y(0) = 0$ and $y'(0) = 5$, what is $Y(s)$?
4.1
$\dfrac{5s}{s^{2}+1}$
$\dfrac{s}{s^{2}+1}$
$\dfrac{1}{s^{2}+1}$
$\dfrac{5}{s^{2}+1}$
Correct. We get $s^{2}Y - s(0) - 5 + Y = 0$, so $(s^{2}+1)Y = 5$ and $Y = 5/(s^{2}+1)$, giving $y = 5\sin t$.
Substituting $y(0)=0$, $y'(0)=5$ gives $s^{2}Y - 5 + Y = 0$, so $Y = 5/(s^{2}+1)$.
Which feature distinguishes the Laplace method from undetermined coefficients?
4.2
Initial conditions are built in from the first step
It cannot handle nonhomogeneous terms
It requires guessing a particular solution form
It only works for first-order equations
Correct. The derivative rules insert $y(0)$ and $y'(0)$ directly, so no arbitrary constants need to be fixed at the end.
The defining advantage is that $\mathcal{L}\{y'\}$ and $\mathcal{L}\{y''\}$ carry the initial data, so they are incorporated immediately.

Step Functions and Shifting阶跃函数与平移

Key idea. The unit step function $u_{c}(t)$ switches on at $t = c$. Combined with the second shift theorem it lets us transform forcing terms that turn on or off at specified times, which is exactly the language of piecewise inputs.
Unit step (Heaviside) function
$$ u_{c}(t) = \begin{cases} 0, & t < c \\ 1, & t \ge c \end{cases}, \qquad \mathcal{L}\{u_{c}(t)\} = \frac{e^{-cs}}{s}. $$
Second shift theorem (t-shift)
$$ \mathcal{L}\{u_{c}(t)\, f(t-c)\} = e^{-cs} F(s), \qquad \mathcal{L}^{-1}\{e^{-cs} F(s)\} = u_{c}(t)\, f(t-c). $$

The factor $e^{-cs}$ in the $s$ domain always signals a time delay of $c$ in the $t$ domain. To apply the forward rule, first rewrite the function so its argument reads $t - c$.

Worked Example 5.1: transform of $u_{2}(t)(t-2)^{2}$例题 5.1:$u_{2}(t)(t-2)^{2}$ 的变换

Here $f(t-2) = (t-2)^{2}$, so $f(t) = t^{2}$ with $\mathcal{L}\{t^{2}\} = 2/s^{3}$. Apply the second shift theorem with $c = 2$:

$$ \mathcal{L}\{u_{2}(t)(t-2)^{2}\} = e^{-2s}\cdot \frac{2}{s^{3}} = \frac{2 e^{-2s}}{s^{3}}. $$

$f(t)=t^{2}$,$\mathcal{L}\{t^{2}\}=2/s^{3}$。第二平移定理($c=2$):

$$ \mathcal{L}\{u_{2}(t)(t-2)^{2}\} = \frac{2e^{-2s}}{s^{3}}. $$
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Worked Example 5.2: inverse of $\dfrac{e^{-3s}}{s^{2}+1}$例题 5.2:$\dfrac{e^{-3s}}{s^{2}+1}$ 的逆变换

The factor $e^{-3s}$ means a delay of $c = 3$. The remaining $F(s) = 1/(s^{2}+1)$ inverts to $f(t) = \sin t$. By the inverse second shift theorem we replace $t$ by $t - 3$ and gate with the step:

$$ \mathcal{L}^{-1}\left\{ \frac{e^{-3s}}{s^{2}+1} \right\} = u_{3}(t)\sin(t-3). $$

$F(s)=1/(s^{2}+1)$ 逆变换为 $\sin t$;$e^{-3s}$ 表示延迟 $c=3$:

$$ \mathcal{L}^{-1}\left\{\frac{e^{-3s}}{s^{2}+1}\right\} = u_{3}(t)\sin(t-3). $$
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Worked Example 5.3: transform of $u_{1}(t)\, t^{2}$ (argument not yet in $t-c$ form)例题 5.3:$u_{1}(t)\,t^{2}$ 的变换(变量尚未化为 $t-c$ 形式)

The second shift theorem needs the function written as $f(t-c)$, but here the factor is $t^{2}$, not $(t-1)^{2}$. Rewrite $t = (t-1)+1$ and expand so every appearance of $t$ becomes a power of $t-1$:

$$ t^{2} = \big((t-1)+1\big)^{2} = (t-1)^{2} + 2(t-1) + 1. $$

Now the gated function is $u_{1}(t)\big[(t-1)^{2} + 2(t-1) + 1\big]$, a sum of three terms each in clean $t-1$ form. With $c = 1$ and the table entries $\mathcal{L}\{t^{2}\}=2/s^{3}$, $\mathcal{L}\{t\}=1/s^{2}$, $\mathcal{L}\{1\}=1/s$, the second shift theorem multiplies each by $e^{-s}$:

$$ \mathcal{L}\{u_{1}(t)\, t^{2}\} = e^{-s}\left( \frac{2}{s^{3}} + \frac{2}{s^{2}} + \frac{1}{s} \right). $$

令 $t=(t-1)+1$ 展开:$t^{2}=(t-1)^{2}+2(t-1)+1$,分别对每项用第二平移定理($c=1$):

$$ \mathcal{L}\{u_{1}(t)\,t^{2}\} = e^{-s}\left(\frac{2}{s^{3}}+\frac{2}{s^{2}}+\frac{1}{s}\right). $$
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Going deeper: the second form $\mathcal{L}\{u_c(t) g(t)\} = e^{-cs}\mathcal{L}\{g(t+c)\}$深入探讨:第二形式 $\mathcal{L}\{u_c(t)g(t)\}=e^{-cs}\mathcal{L}\{g(t+c)\}$

Rewriting by hand, as in Example 5.3, is the algebra behind a compact rule. Start from the definition, where the step $u_c$ cuts the lower limit to $c$:

$$ \mathcal{L}\{u_c(t) g(t)\} = \int_{c}^{\infty} e^{-st} g(t)\, dt. $$

Substitute $\tau = t - c$, so $t = \tau + c$ and $dt = d\tau$, and the limits become $\tau \in [0,\infty)$:

$$ = \int_{0}^{\infty} e^{-s(\tau+c)} g(\tau + c)\, d\tau = e^{-cs}\int_{0}^{\infty} e^{-s\tau} g(\tau + c)\, d\tau = e^{-cs}\,\mathcal{L}\{g(t+c)\}. $$

This packages the rewrite automatically: to transform $u_c(t) g(t)$, shift the argument forward to $g(t+c)$, transform, and multiply by $e^{-cs}$. Applying it to $g(t)=t^2$, $c=1$ reproduces Example 5.3 since $g(t+1)=(t+1)^2 = t^2+2t+1$.

$(s^{2}+1)Y=e^{-\pi s}$,故 $Y=e^{-\pi s}/(s^{2}+1)$。t 平移定理:

$$ y(t) = u_{\pi}(t)\sin(t-\pi) = -u_{\pi}(t)\sin t. $$
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Common error. The most common mistake with the second shift theorem is to read $\mathcal{L}\{u_c(t) g(t)\} = e^{-cs} G(s)$ where $G$ is the transform of $g$ as written. That is wrong unless $g$ is already a function of $t-c$. The correct rule is $\mathcal{L}\{u_c(t) f(t-c)\} = e^{-cs} F(s)$, so the argument must read $t-c$ before you transform. If it reads $t$, first rewrite it in powers of $t-c$ (or use the second form above). Skipping this step silently drops the cross terms and gives the wrong transform.
What is $\mathcal{L}\{u_{5}(t)\}$?
5.1
$\dfrac{1}{s}$
$\dfrac{e^{-5s}}{s}$
$\dfrac{e^{5s}}{s}$
$e^{-5s}$
Correct. The step turning on at $c = 5$ has transform $e^{-cs}/s = e^{-5s}/s$.
The Heaviside step $u_{c}(t)$ transforms to $e^{-cs}/s$, so with $c = 5$ the answer is $e^{-5s}/s$.
$\mathcal{L}^{-1}\left\{ \dfrac{e^{-2s}}{s} \right\}$ equals which function?
5.2
$\sin(t-2)$
$e^{-2t}$
$u_{2}(t)$
$u_{2}(t)(t-2)$
Correct. Since $\mathcal{L}^{-1}\{1/s\} = 1$, the factor $e^{-2s}$ delays it to the step $u_{2}(t)$.
Here $F(s) = 1/s$ inverts to the constant $1$; the $e^{-2s}$ gates it on at $t = 2$, giving $u_{2}(t)$.

The Dirac Delta狄拉克 δ 函数

Key idea. The Dirac delta $\delta(t-c)$ models an idealized impulse: a force applied over a vanishingly short interval but carrying unit total impulse. It is not a function in the ordinary sense, but it behaves predictably under integration and under the Laplace transform.
Sifting property and transform
$$ \int_{-\infty}^{\infty} \delta(t-c)\, g(t)\, dt = g(c), \qquad \mathcal{L}\{\delta(t-c)\} = e^{-cs} \;\;(c \ge 0). $$

In particular $\mathcal{L}\{\delta(t)\} = 1$, taking the limiting case $c = 0$. An impulse delivered to a system at time $c$ produces a sudden jump in the response; the delta is the right hand side that models a hammer blow or a switching spike.

Worked Example 6.1: solve $y'' + y = \delta(t-\pi)$, $y(0) = 0$, $y'(0) = 0$例题 6.1:求解 $y''+ y=\delta(t-\pi)$,$y(0)=0$,$y'(0)=0$

Transform both sides, using $\mathcal{L}\{\delta(t-\pi)\} = e^{-\pi s}$:

$$ (s^{2}+1)Y = e^{-\pi s} \;\Longrightarrow\; Y(s) = \frac{e^{-\pi s}}{s^{2}+1}. $$

Since $1/(s^{2}+1)$ inverts to $\sin t$, the second shift theorem with $c = \pi$ gives

$$ y(t) = u_{\pi}(t)\sin(t-\pi) = -u_{\pi}(t)\sin t. $$

The system is at rest until $t = \pi$, then the impulse sets it oscillating.

$(s^{2}+1)Y=e^{-\pi s}$,故 $Y=e^{-\pi s}/(s^{2}+1)$。t 平移定理:

$$ y(t) = u_{\pi}(t)\sin(t-\pi) = -u_{\pi}(t)\sin t. $$
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Going deeper: the delta as a limit of tall narrow pulses深入探讨:δ 函数作为高窄矩形脉冲的极限

Define the boxcar $d_{\varepsilon}(t-c)$ equal to $1/\varepsilon$ on $[c, c+\varepsilon]$ and $0$ elsewhere, so its total area is $1$. Its transform is

$$ \mathcal{L}\{d_{\varepsilon}(t-c)\} = \frac{1}{\varepsilon}\cdot \frac{e^{-cs} - e^{-(c+\varepsilon)s}}{s} = e^{-cs}\cdot \frac{1 - e^{-\varepsilon s}}{\varepsilon s}. $$

As $\varepsilon \to 0^{+}$, the factor $(1 - e^{-\varepsilon s})/(\varepsilon s) \to 1$ (its first order Taylor expansion is $1 - \tfrac{\varepsilon s}{2} + \cdots$). Hence $\mathcal{L}\{d_{\varepsilon}(t-c)\} \to e^{-cs}$, which we adopt as the definition $\mathcal{L}\{\delta(t-c)\} = e^{-cs}$.

$(s+1)^{2}Y=3e^{-s}$,$1/(s+1)^{2}$ 逆变换为 $te^{-t}$,t 平移得

$$ y(t) = 3u_{1}(t)(t-1)e^{-(t-1)}. $$
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Worked Example 6.2: an impulse into a damped system, $y'' + 2y' + y = 3\delta(t-1)$, rest data例题 6.2:阻尼系统冲激响应,$y''+ 2y'+y=3\delta(t-1)$,零初始条件

With $y(0)=y'(0)=0$ and $\mathcal{L}\{\delta(t-1)\} = e^{-s}$, transform both sides:

$$ (s^{2}+2s+1)Y = 3 e^{-s} \;\Longrightarrow\; Y(s) = \frac{3 e^{-s}}{(s+1)^{2}}. $$

The factor $1/(s+1)^{2}$ inverts to $t e^{-t}$ (repeated factor at $a=-1$). The $e^{-s}$ is a delay of $c=1$, so by the inverse second shift theorem we replace $t$ by $t-1$ and gate with the step:

$$ y(t) = 3\, u_{1}(t)\,(t-1)\, e^{-(t-1)}. $$

Before $t=1$ the system sits at rest. The unit impulse at $t=1$ injects momentum, and the critically damped response $(t-1)e^{-(t-1)}$ rises then decays back to zero. The impulse produces a jump in $y'$, not in $y$ itself, which is why $y$ stays continuous through $t=1$.

$(s+1)^{2}Y=3e^{-s}$,$1/(s+1)^{2}$ 逆变换为 $te^{-t}$,t 平移得

$$ y(t) = 3u_{1}(t)(t-1)e^{-(t-1)}. $$
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Common error. The delta and the step have transforms that look similar but differ by a crucial factor of $s$: $\mathcal{L}\{\delta(t-c)\} = e^{-cs}$ while $\mathcal{L}\{u_c(t)\} = e^{-cs}/s$. Writing $\mathcal{L}\{\delta(t-c)\} = e^{-cs}/s$ is the most frequent slip in this section. The clean way to remember it: the delta is the derivative of the step, so its transform is $s$ times the step's transform, $s\cdot e^{-cs}/s = e^{-cs}$, and the $1/s$ cancels.
What is $\mathcal{L}\{\delta(t-4)\}$?
6.1
$e^{-4s}$
$\dfrac{e^{-4s}}{s}$
$\dfrac{1}{s}$
$4 e^{-s}$
Correct. The impulse at $c = 4$ transforms to $e^{-cs} = e^{-4s}$, with no $1/s$ factor.
Unlike the step, the delta transforms to $e^{-cs}$ with no division by $s$, so $\mathcal{L}\{\delta(t-4)\} = e^{-4s}$.
Evaluate $\displaystyle\int_{-\infty}^{\infty} \delta(t-2)\, e^{t}\, dt$.
6.2
$0$
$1$
$e^{t}$
$e^{2}$
Correct. The sifting property evaluates the integrand at the spike location $t = 2$, giving $e^{2}$.
By the sifting property, $\int \delta(t-c) g(t)\,dt = g(c)$; with $g(t) = e^{t}$ and $c = 2$ the value is $e^{2}$.

Convolution卷积

Key idea. The inverse transform of a product is not the product of the inverses; it is their convolution. Convolution gives a clean formula for the response of a system to an arbitrary forcing function in terms of its impulse response.
Convolution and the convolution theorem
$$ (f * g)(t) = \int_{0}^{t} f(\tau)\, g(t-\tau)\, d\tau, \qquad \mathcal{L}\{f * g\} = F(s)\, G(s). $$

Equivalently $\mathcal{L}^{-1}\{F(s)G(s)\} = (f*g)(t)$. The operation is commutative, $f*g = g*f$, which is often used to put the simpler factor inside the shifted slot. It also lets us invert products that resist partial fractions.

Convolution is more than a trick for inverting products; it is the natural language of linear time-invariant systems. If a system has impulse response $h(t)$, meaning its output when forced by $\delta(t)$, then its output for any input $g(t)$ is the convolution $h * g$. In transform language the system multiplies by the transfer function $H(s) = \mathcal{L}\{h\}$, so $Y(s) = H(s) G(s)$ and the time-domain output is the convolution of the impulse response with the input. This is why Example 7.2 produced a single formula valid for every forcing: $1/(s^{2}+1)$ is the transfer function of the undamped oscillator, and $\sin t$ is its impulse response. The convolution beside the transform product is the same statement read in two domains.

Worked Example 7.1: invert $\dfrac{1}{s^{2}(s^{2}+1)}$ by convolution例题 7.1:用卷积求 $\dfrac{1}{s^{2}(s^{2}+1)}$ 的逆变换

Write the product as $F(s)G(s)$ with $F = 1/s^{2}$ and $G = 1/(s^{2}+1)$, so $f(t) = t$ and $g(t) = \sin t$. Then

$$ \mathcal{L}^{-1}\left\{ \frac{1}{s^{2}(s^{2}+1)} \right\} = \int_{0}^{t} \tau\, \sin(t-\tau)\, d\tau. $$

Integrating by parts gives

$$ \int_{0}^{t} \tau\, \sin(t-\tau)\, d\tau = t - \sin t. $$

$f(t)=t$,$g(t)=\sin t$,卷积:

$$ \int_{0}^{t}\tau\sin(t-\tau)\,d\tau = t-\sin t. $$
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Worked Example 7.2: write the solution of $y'' + y = g(t)$, rest initial data, as a convolution例题 7.2:将 $y''+ y=g(t)$(零初始条件)的解写成卷积形式

Transforming with $y(0) = y'(0) = 0$ gives $(s^{2}+1)Y = G(s)$, so

$$ Y(s) = \frac{1}{s^{2}+1}\, G(s). $$

The factor $1/(s^{2}+1)$ is the transform of $\sin t$, the impulse response. By the convolution theorem,

$$ y(t) = \int_{0}^{t} \sin(t-\tau)\, g(\tau)\, d\tau, $$

a single formula valid for any forcing $g$.

$Y=G(s)/(s^{2}+1)$,冲激响应为 $\sin t$,卷积定理给出

$$ y(t) = \int_{0}^{t}\sin(t-\tau)\,g(\tau)\,d\tau. $$
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Worked Example 7.3: evaluate $(e^{t} * 1)(t)$ directly and check by transform例题 7.3:直接计算 $(e^{t}*1)(t)$ 并用变换验证

Take $f(t) = e^{t}$ and $g(t) = 1$. From the definition,

$$ (e^{t} * 1)(t) = \int_{0}^{t} e^{\tau}\cdot 1\, d\tau = \big[ e^{\tau} \big]_{0}^{t} = e^{t} - 1. $$

Check against the convolution theorem. Here $F(s) = 1/(s-1)$ and $G(s) = 1/s$, so the product is

$$ F(s)G(s) = \frac{1}{s(s-1)} = \frac{-1}{s} + \frac{1}{s-1} = \mathcal{L}\{-1 + e^{t}\}, $$

using partial fractions. Inverting gives $e^{t} - 1$, matching the direct integral. The two routes agreeing is the convolution theorem in action: a product of transforms is the transform of a convolution.

直接积分:$(e^{t}*1)(t)=\int_{0}^{t}e^{\tau}d\tau=e^{t}-1$。变换验证:$\mathcal{L}\{1/(s(s-1))\}=\mathcal{L}\{e^{t}-1\}$,两者一致。

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Going deeper: proof of the convolution theorem $\mathcal{L}\{f*g\} = F(s)G(s)$深入探讨:卷积定理 $\mathcal{L}\{f*g\}=F(s)G(s)$ 的证明

Write out the transform of the convolution as a double integral over the triangular region $0 \le \tau \le t < \infty$:

$$ \mathcal{L}\{f*g\} = \int_{0}^{\infty} e^{-st} \left( \int_{0}^{t} f(\tau) g(t-\tau)\, d\tau \right) dt = \iint_{0 \le \tau \le t} e^{-st} f(\tau) g(t-\tau)\, d\tau\, dt. $$

Both functions are of exponential order, so the double integral converges absolutely for large $s$ and Fubini's theorem permits swapping the order of integration. Fix $\tau$ and let $t$ range over $[\tau, \infty)$. Substitute $\sigma = t - \tau$, so $t = \sigma + \tau$, $dt = d\sigma$, and $\sigma \in [0, \infty)$:

$$ = \int_{0}^{\infty} f(\tau) \left( \int_{0}^{\infty} e^{-s(\sigma+\tau)} g(\sigma)\, d\sigma \right) d\tau = \int_{0}^{\infty} e^{-s\tau} f(\tau)\, d\tau \cdot \int_{0}^{\infty} e^{-s\sigma} g(\sigma)\, d\sigma. $$

The integrals separate because $e^{-s(\sigma+\tau)} = e^{-s\tau} e^{-s\sigma}$, and the two factors are exactly $F(s)$ and $G(s)$. Hence $\mathcal{L}\{f*g\} = F(s) G(s)$. The same change of variables, applied to the inner integral alone, also proves commutativity $f*g = g*f$.

将卷积的变换展开为三角形区域 $0le aule t

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Common error. The single biggest trap is to assume $\mathcal{L}^{-1}\{F(s)G(s)\} = f(t)\,g(t)$, treating the inverse transform as multiplicative. It is not. The inverse of a product is the convolution $\int_0^t f(\tau)g(t-\tau)\,d\tau$, which in general differs from the pointwise product. For instance $\mathcal{L}^{-1}\{(1/s)(1/s)\} = t$, not $1\cdot 1 = 1$. Whenever you face a product of transforms with no clean partial-fraction split, reach for convolution rather than multiplying inverses.
According to the convolution theorem, $\mathcal{L}^{-1}\{F(s)G(s)\}$ equals which expression?
7.1
$f(t)\, g(t)$
$f(t) + g(t)$
$\displaystyle\int_{0}^{t} f(\tau)\, g(t-\tau)\, d\tau$
$\displaystyle\int_{0}^{\infty} f(\tau)\, g(\tau)\, d\tau$
Correct. A product of transforms inverts to the convolution $\int_{0}^{t} f(\tau) g(t-\tau)\, d\tau$, not to a pointwise product.
The inverse of a product is the convolution integral $\int_{0}^{t} f(\tau) g(t-\tau)\,d\tau$, with limits from $0$ to $t$.
Which property of convolution lets you write $f * g = g * f$?
7.2
Commutativity
Linearity of the transform
The sifting property
Exponential order
Correct. Convolution is commutative, which follows from the substitution $\sigma = t - \tau$ in the defining integral.
The identity $f*g = g*f$ is the commutativity of convolution, provable by the change of variable $\sigma = t - \tau$.

Flashcards闪卡

0 / 12 flipped
Definition of $\mathcal{L}\{f(t)\}$定义 $\mathcal{L}\{f(t)\}$
$F(s) = \int_{0}^{\infty} e^{-st} f(t)\, dt$
defined where the integral converges.在积分收敛处有定义。
$\mathcal{L}\{1\}$ and $\mathcal{L}\{t^{n}\}$$\mathcal{L}\{1\}$ 和 $\mathcal{L}\{t^{n}\}$
$\mathcal{L}\{1\} = \dfrac{1}{s}$
$\mathcal{L}\{t^{n}\} = \dfrac{n!}{s^{n+1}}$
$\mathcal{L}\{e^{at}\}$$\mathcal{L}\{e^{at}\}$ 的值
$\dfrac{1}{s-a}$
valid for $s > a$.当 $s > a$ 时成立。
$\mathcal{L}\{\cos bt\}$ and $\mathcal{L}\{\sin bt\}$$\mathcal{L}\{\cos bt\}$ 和 $\mathcal{L}\{\sin bt\}$
$\dfrac{s}{s^{2}+b^{2}}$ and $\dfrac{b}{s^{2}+b^{2}}$.
First shift theorem第一平移定理
$\mathcal{L}\{e^{at} f(t)\} = F(s-a)$
Multiplying by $e^{at}$ shifts $s$ to $s-a$.乘以 $e^{at}$ 将 $s$ 平移为 $s-a$。
Transform of derivatives导数的变换
$\mathcal{L}\{y'\} = sY - y(0)$ and $\mathcal{L}\{y''\} = s^{2}Y - s\,y(0) - y'(0)$.
Unit step transform单位阶跃变换
$\mathcal{L}\{u_{c}(t)\} = \dfrac{e^{-cs}}{s}$
where $u_{c}$ switches on at $t = c$.$u_{c}$ 在 $t = c$ 处开启。
Second shift theorem第二平移定理
$\mathcal{L}\{u_{c}(t) f(t-c)\} = e^{-cs} F(s)$
A factor $e^{-cs}$ means a delay of $c$.因子 $e^{-cs}$ 表示延迟 $c$。
Dirac delta transformDirac delta 变换
$\mathcal{L}\{\delta(t-c)\} = e^{-cs}$
with the sifting property $\int \delta(t-c) g\, dt = g(c)$.筛选性质:$\int \delta(t-c) g\, dt = g(c)$。
Convolution theorem卷积定理
$\mathcal{L}\{f * g\} = F(s) G(s)$
$(f*g)(t) = \int_{0}^{t} f(\tau) g(t-\tau)\, d\tau$
Two inverse patterns两种逆变换模式
$\dfrac{1}{(s-a)^{2}} \mapsto t e^{at}$ and $\dfrac{1}{(s-a)^{2}+b^{2}} \mapsto \dfrac{1}{b} e^{at}\sin bt$.
Three step IVP recipe三步求解初值问题
Transform each term (insert initial data), solve for $Y(s)$, then invert with partial fractions.逐项取变换(代入初始数据),代数求解 $Y(s)$,再用部分分式求逆变换。

Unit Quiz单元测验

What is $\mathcal{L}\{\cos 7t\}$?$\mathcal{L}\{\cos 7t\}$ 等于什么?
Q1
$\dfrac{7}{s^{2}+49}$
$\dfrac{s}{s^{2}+49}$
$\dfrac{s}{s^{2}-49}$
$\dfrac{1}{s-7}$
Correct. $\mathcal{L}\{\cos bt\} = s/(s^{2}+b^{2})$ with $b = 7$.
Use $\mathcal{L}\{\cos bt\} = s/(s^{2}+b^{2})$; here $b = 7$ gives $s/(s^{2}+49)$.
Transforming $y' + 2y = 0$ with $y(0) = 3$ gives which $Y(s)$?对 $y' + 2y = 0$($y(0)=3$)取变换,得到哪个 $Y(s)$?
Q2
$\dfrac{1}{s+2}$
$\dfrac{3}{s-2}$
$\dfrac{3s}{s+2}$
$\dfrac{3}{s+2}$
Correct. $sY - 3 + 2Y = 0$ gives $(s+2)Y = 3$, so $Y = 3/(s+2)$ and $y = 3 e^{-2t}$.
From $sY - y(0) + 2Y = 0$ with $y(0) = 3$, we get $(s+2)Y = 3$, so $Y = 3/(s+2)$.
$\mathcal{L}^{-1}\left\{ \dfrac{e^{-4s}}{s^{2}} \right\}$ equals which function?$\mathcal{L}^{-1}\left\{ \dfrac{e^{-4s}}{s^{2}} \right\}$ 等于哪个函数?
Q3
$t - 4$
$u_{4}(t)\, t$
$u_{4}(t)\,(t-4)$
$\sin(t-4)$
Correct. $1/s^{2}$ inverts to $t$; the factor $e^{-4s}$ delays it, giving $u_{4}(t)(t-4)$.
Since $\mathcal{L}^{-1}\{1/s^{2}\} = t$, the delay $e^{-4s}$ replaces $t$ by $t-4$ and gates with $u_{4}$.
What is $\mathcal{L}\{\delta(t-6)\}$?$\mathcal{L}\{\delta(t-6)\}$ 等于什么?
Q4
$e^{-6s}$
$\dfrac{e^{-6s}}{s}$
$6 e^{-s}$
$\dfrac{1}{s+6}$
Correct. The impulse at $c = 6$ has transform $e^{-cs} = e^{-6s}$.
The Dirac delta transforms to $e^{-cs}$ with no $1/s$ factor, so $\mathcal{L}\{\delta(t-6)\} = e^{-6s}$.
If $f(t) = 1$ and $g(t) = e^{t}$, what is $(f*g)(t)$?若 $f(t)=1$,$g(t)=e^{t}$,$(f*g)(t)$ 等于什么?
Q5
$e^{t}$
$e^{t} - 1$
$t e^{t}$
$1 + e^{t}$
Correct. $(f*g)(t) = \int_{0}^{t} 1\cdot e^{t-\tau}\, d\tau = e^{t}\int_{0}^{t} e^{-\tau}\,d\tau = e^{t}(1 - e^{-t}) = e^{t} - 1$.
Compute $\int_{0}^{t} e^{t-\tau}\,d\tau = e^{t}(1 - e^{-t}) = e^{t} - 1$.
By the first shift theorem, $\mathcal{L}\{e^{3t} t^{2}\}$ equals which expression?由第一平移定理,$\mathcal{L}\{e^{3t}t^{2}\}$ 等于哪个表达式?
Q6
$\dfrac{2}{s^{3}}$
$\dfrac{2}{(s+3)^{3}}$
$\dfrac{2}{(s-3)^{3}}$
$\dfrac{1}{(s-3)^{2}}$
Correct. Start from $\mathcal{L}\{t^{2}\} = 2/s^{3}$ and replace $s$ by $s - 3$, giving $2/(s-3)^{3}$.
The shift $s \mapsto s - 3$ applied to $\mathcal{L}\{t^{2}\} = 2/s^{3}$ yields $2/(s-3)^{3}$.

Readiness Checklist掌握清单

Tap each item you can do without notes. 0 / 8 mastered