请按照右侧目录浏览
傅里叶分析之掐死教程(完整版)更新于2014.06.06
f(t)
表示激励信号,y(t)
表示响应信号用一个单变量或多变量的函数来表示
自变量
以时间t
为自变量,信号可以表示为t
的函数,用函数f(t)
,y(t)
表征
信号在一定条件下又可分解为不同频率的正弦分量之和,正弦分量的振幅和初相位与频率之间的关系叫做信号的频率特性
t
都有确定的函数值与其对应,这样的信号称为确定信号时间域有始有终的信号,信号出现在[t1, t2]
f ( t ) = { f ( t ) , t 1 ≤ t ≤ t 2 0 , t < t 1 , t > t 2 f(t) = \begin{cases} f(t),&t_1 \le t \le t_2\\ 0,& t \lt t_1,t \gt t_2 \end{cases} f(t)={ f(t),0,t1≤t≤t2t<t1,t>t2
时间域无始有终的信号,(-∞, t0]
f ( t ) = { f ( t ) , t ≤ t 0 0 , t > t 0 f(t) = \begin{cases} f(t),&t \le t_0\\ 0,& t \gt t_0 \end{cases} f(t)={ f(t),0,t≤t0t>t0
时间域有始无终的信号,[t0, +∞)
f ( t ) = { f ( t ) , t ≥ t 0 0 , t < t 0 f(t) = \begin{cases} f(t),&t \ge t_0\\ 0,& t \lt t_0 \end{cases} f(t)={ f(t),0,t≥t0t<t0
有始信号在t = 0
时刻起始,[0, +∞)
f ( t ) = { f ( t ) , t ≥ 0 0 , t < 0 f(t) = \begin{cases} f(t),&t \ge 0\\ 0,& t \lt 0 \end{cases} f(t)={ f(t),0,t≥0t<0
起始信号的反转,,(-∞, 0]
f ( t ) = { f ( t ) , t ≤ 0 0 , t > 0 f(t) = \begin{cases} f(t),&t \le 0\\ 0,& t \gt 0 \end{cases} f(t)={ f(t),0,t≤0t>0
时间域无始无终的信号
f ( t ) = f ( t ) ( − ∞ < t < ∞ ) f(t) = f(t) (-\infin \lt t \lt \infin) f(t)=f(t)(−∞<t<∞)
周期信号的特点
非周期信号不具备这两个特点
两个及两个以上的周期信号的叠加可能是周期信号,也可能是非周期信号,其中能找到最小公倍周期的为周期信号,否则就是非周期信号。
f T ( t ) = f ( t − k T ) , k = 0 , ± 1 , ± 2 , . . . , T > 0 f_T(t) = f(t-kT), k=0, \pm1,\pm2,..., T\gt 0 fT(t)=f(t−kT),k=0,±1,±2,...,T>0
f N ( k ) = f ( k − m N ) , m = 0 , ± 1 , ± 2 , . . . , N > 0 f_N(k) = f(k-mN), m=0, \pm1,\pm2,..., N\gt 0 fN(k)=f(k−mN),m=0,±1,±2,...,N>0
1Ω的电阻上消耗的瞬时功率为
p ( t ) = u 2 ( t ) p ( t ) = i 2 ( t ) p(t) = u^2(t) \\ p(t) = i^2(t) p(t)=u2(t)p(t)=i2(t)
将电压和电流抽象为一般意义的信号
p ( t ) = f 2 ( t ) p(t) = f^2(t) p(t)=f2(t)
[-τ,τ]
区间归一化能量
E = ∫ − τ τ p ( t ) d t = ∫ − τ τ ∣ f ( t ) ∣ 2 d t E = \int^\tau_{-\tau}p(t)dt = \int^\tau_{-\tau}|f(t)|^2dt E=∫−ττp(t)dt=∫−ττ∣f(t)∣2dt
归一化平均功率
P = 1 2 τ ∫ − τ τ ∣ f ( t ) ∣ 2 d t P = \frac 1 {2\tau} \int^\tau_{-\tau}|f(t)|^2dt P=2τ1∫−ττ∣f(t)∣2dt
(-∞,∞)
归一化总能量
E 总 = lim τ → ∞ ∫ − τ τ ∣ f ( t ) ∣ 2 d t E_总 = \lim_{\tau \rightarrow \infin}\int^\tau_{-\tau}|f(t)|^2dt E总=τ→∞lim∫−ττ∣f(t)∣2dt
归一化平均功率
P = lim τ → ∞ 1 2 τ ∫ − τ τ ∣ f ( t ) ∣ 2 d t P = \lim_{\tau \rightarrow \infin} \frac 1 {2\tau} \int^\tau_{-\tau}|f(t)|^2dt P=τ→∞lim2τ1∫−ττ∣f(t)∣2dt
总能量 | 平均功率 | |
---|---|---|
功率信号 | ∞ | 有限 |
能量信号 | 有限 | ∞ |
非功非能信号 | ∞ | ∞ |
不存在功率有界能量也有界的信号
离散信号f(k)的归一化总能量
E 总 = lim n → ∞ ∑ k = − n n ∣ f ( k ) ∣ 2 ( − n ≤ k ≤ n ) E_总 = \lim_{n \rightarrow \infin} \displaystyle\sum_{k=-n}^n|f(k)|^2(-n \le k \le n ) E总=n→∞limk=−n∑n∣f(k)∣2(−n≤k≤n)
归一化平均功率
P = lim n → ∞ 1 2 n + 1 ∑ k = − n n ∣ f ( k ) ∣ 2 ( − n ≤ k ≤ n ) P = \lim_{n \rightarrow \infin} \frac 1 {2n+1}\displaystyle\sum_{k=-n}^n|f(k)|^2(-n \le k \le n ) P=n→∞lim2n+11k=−n∑n∣f(k)∣2(−n≤k≤n)
2n + 1
的1
指的是t = 0
时刻的信号
功率信号 |
---|
连续的周期信号 |
直流信号 |
单位阶跃信号 |
能量信号 |
---|
时限脉冲信号 |
单边指数衰减信号 |
非功非能信号 |
---|
指数增长信号 |
f ( t ) = A e s t s = σ + j ω σ 、 ω 为 实 数 f(t)=Ae^{st}\\ s = \sigma + j\omega\\ \sigma、\omega为实数 f(t)=Aests=σ+jωσ、ω为实数
s称为复频率
A e s t = A e ( σ + j ω ) t = A e σ t e j ω t \begin{aligned} Ae^{st} &= Ae^{(\sigma+j\omega)t}\\ &= Ae^{\sigma t}e^{j\omega t} \end{aligned} Aest=Ae(σ+jω)t=Aeσtejωt
欧拉公式
e i x = c o s x + i s i n x e^{ix} = cosx+isinx eix=cosx+isinx
A e σ t e j ω t = A e σ t ( c o s ω t + j s i n ω t ) Ae^{\sigma t}e^{j\omega t} = Ae^{\sigma t}(cos\omega t+jsin\omega t) Aeσtejωt=Aeσt(cosωt+jsinωt)
f(t)
为实指数信号f(t
)为虚指数信号,实部和虚部是正弦信号f ( t ) = A e σ t f(t) = Ae^{\sigma t} f(t)=Aeσt
f(t)
为指数增长信号f(t)
为指数衰减信号f(t)
为直流信号通常把|σ|的倒数称为指数信号的时间常数
τ = 1 ∣ σ ∣ \tau = \frac 1 {|\sigma|} τ=∣σ∣1
τ
越大指数信号增长或衰减越慢
f ( t ) = { 0 , t < 0 A e − t τ , t ≥ 0 f(t) = \begin{cases} 0,&t \lt 0\\ Ae^{- \frac t \tau},& t \ge 0 \end{cases} f(t)={ 0,Ae−τt,t<0t≥0
实指数信号对时间的微分和积分仍然是实指数信号
f ( t ) = A c o s ( ω t + φ ) f(t) = Acos(\omega t + \varphi ) f(t)=Acos(ωt+φ)
正弦信号的平均功率
P = A 2 2 P = \frac {A^2} 2 P=2A2
两个频率不同的正弦信号叠加,满足一定条件才是周期信号
f ( t ) = c o s ω 1 t + c o s ω 2 t f(t) = cos\omega_1t + cos\omega_2t\\ f(t)=cosω1t+cosω2t
ω 1 ω 2 = T 1 T 2 = m n \frac {\omega_1} {\omega_2} = \frac {T_1} {T_2} = \frac m n ω2ω1=T2T1=nm
m/n是最简分式,则f(t)
是周期信号,其周期为最小公倍周期
T = m T 1 = n T 2 T = mT_1 = nT_2 T=mT1=nT2
f ( t ) = A e σ t c o s ω t f(t) = Ae^{\sigma t} cos\omega t f(t)=Aeσtcosωt
复指数信号
A e σ t c o s ω t + ( A e σ t s i n ω t ) j Ae^{\sigma t}cos\omega t+(Ae^{\sigma t}sin\omega t)j Aeσtcosωt+(Aeσtsinωt)j
它的实部和虚部是变幅正弦振荡信号
f r ( t ) = R e [ A e s t ] = A e σ t c o s ω f_r(t) = Re[Ae^{st}] = Ae^{\sigma t}cos\omega fr(t)=Re[Aest]=Aeσtcosω
f i ( t ) = I m [ A e s t ] = A e σ t s i n ω t f_i(t) = Im[Ae^{st}] = Ae^{\sigma t}sin\omega t fi(t)=Im[Aest]=Aeσtsinωt
f ( t ) = s i n t t = S a ( t ) f(t) = \frac {sint} t = Sa(t) f(t)=tsint=Sa(t)
f ( t ) = A e − ( t τ ) 2 f(t) = Ae^{ {-(\frac t \tau)}^2} f(t)=Ae−(τt)2
R ( t ) = t ε ( t ) = { 0 , t < 0 t , t ≥ 0 R(t) = t\varepsilon(t) =\begin{cases} 0,&t \lt 0\\ t,& t \ge 0 \end{cases} R(t)=tε(t)={ 0,t,t<0t≥0
R ( t − t 0 ) = ( t − t 0 ) ε ( t − t 0 ) { 0 , t < t 0 t − t 0 , t ≥ t 0 R(t-t_0) = (t-t_0)\varepsilon(t-t_0) \begin{cases} 0,&t \lt t_0\\ t-t_0,& t \ge t_0 \end{cases} R(t−t0)=(t−t0)ε(t−t0){ 0,t−t0,t<t0t≥t0
f 1 ( t ) = R 1 ( t ) = { A τ R ( t ) , t < τ A , t ≥ τ f_1(t) = R_1(t) = \begin{cases} \frac A \tau R(t),&t \lt \tau\\ A,& t \ge \tau \end{cases} f1(t)=R1(t)={ τAR(t),A,t<τt≥τ
f 1 ( t ) = R 2 ( t ) = { A τ R ( t ) , t ≤ τ 0 , t > τ f_1(t) = R_2(t) = \begin{cases} \frac A \tau R(t),&t \le \tau\\ 0,& t \gt \tau \end{cases} f1(t)=R2(t)={ τAR(t),0,t≤τt>τ
f 3 ( t ) = A Δ 2 τ ( t ) = R 1 ( t + τ ) − R 1 ( t ) = { A ( 1 − ∣ t ∣ τ ) , ∣ t ∣ ≤ τ 0 , ∣ t ∣ > τ f_3(t) = A\Delta_{2\tau}(t) = R_1( t + \tau ) - R_1(t) = \begin{cases} A( 1 - \frac {|t|} \tau ),&|t| \le \tau\\ 0,& |t| \gt \tau \end{cases} f3(t)=AΔ2τ(t)=R1(t+τ)−R1(t)={ A(1−τ∣t∣),0,∣t∣≤τ∣t∣>τ
ε ( t ) = { 1 , t > 0 0 , t < 0 \varepsilon(t) = \begin{cases} 1,&t \gt 0\\ 0,& t \lt 0 \end{cases} ε(t)={ 1,0,t>0t<0
ε ( t − t 0 ) = { 1 , t > t 0 0 , t < t 0 \varepsilon(t-t_0) = \begin{cases} 1,&t \gt t_0\\ 0,& t \lt t_0 \end{cases} ε(t−t0)={ 1,0,t>t0t<t0
g τ ( t ) = ε ( t + τ 2 ) − ε ( t − τ 2 ) g_\tau(t) = \varepsilon(t+\frac \tau 2) - \varepsilon(t-\frac \tau 2) gτ(t)=ε(t+2τ)−ε(t−2τ)
单位阶跃信号用来表示信号的非零值时间定义域
一个函数乘以门函数,只留下门函数内的部分
s g n ( t ) = { 1 , t > 0 − 1 , t < 0 sgn(t) = \begin{cases} 1,&t \gt 0\\ -1,& t \lt 0 \end{cases} sgn(t)={ 1,−1,t>0t<0
s g n ( t ) = 2 ε ( t ) − 1 = ε ( t ) − ε ( − t ) sgn(t) = 2\varepsilon(t) - 1 = \varepsilon(t) - \varepsilon(-t) sgn(t)=2ε(t)−1=ε(t)−ε(−t)
ε ( t ) = d R ( t ) d t \varepsilon(t) = \frac {dR(t)} {dt} ε(t)=dtdR(t)
δ ( t ) = { ∞ , t = 0 0 , t ≠ 0 \delta(t) = \begin{cases} \infin,&t = 0\\ 0,& t \ne 0 \end{cases} δ(t)={ ∞,0,t=0t=0
单位冲激函数的强度
∫ ∞ ∞ δ ( t ) d t = 1 \int^\infin_\infin \delta(t)dt = 1 ∫∞∞δ(t)dt=1
若函数f(t)在t = 0时连续
f ( t ) δ ( t ) = f ( 0 ) δ ( t ) f(t)\delta(t) = f(0)\delta(t) f(t)δ(t)=f(0)δ(t)
若函数f(t)在t = 0时连续
∫ − ∞ ∞ f ( t ) δ ( t ) d t = f ( 0 ) \int^\infin_{-\infin}f(t)\delta(t)dt = f(0) ∫−∞∞f(t)δ(t)dt=f(0)
推论
若函数f(t)在t = t0时连续
f ( t ) δ ( t − t 0 ) = f ( t 0 ) δ ( t − t 0 ) f(t)\delta(t-t_0) = f(t_0)\delta(t-t_0) f(t)δ(t−t0)=f(t0)δ(t−t0)
∫ − ∞ ∞ f ( t ) δ ( t − t 0 ) d t = f ( t 0 ) \int^\infin_{-\infin}f(t)\delta(t-t_0)dt = f(t_0) ∫−∞∞f(t)δ(t−t0)dt=f(t0)