数字信号处理 答案 第三章

合集下载

数字信号处理 Chapter03答案

数字信号处理 Chapter03答案

11
3.2 Properties of the z-Transform
Ex. ( linearity) x(n) = [3(2n) – 4(3n)] u(n) 3 4 – 1 – 2z –1 1 – 3z –1
X(z) =
ROC: |z| > 3
12
3.2 Properties of the z-Transform
z = re

=
n =−∞
∑ x ( n )r
−n

− n − jθ n
e
X ( z) ≤
n =−∞


−1
x (n) r
+∑
n=0


x ( n) rn
x (n) rn
≤ ∑ x ( −n ) r + ∑
n n =1 n =0
7
3.1 The z-Transform
3.1.1 The Direct z-Transform
3.2 Properties of the z-Transform
X(z) = ∑ x(n) z – n
14
3.2 Properties of the z-Transform
X(z) = ∑ x(n) z – n
15
X(z) = ∑ x(n) z – n
16
3.3 Rational z-Transforms
1 2 −1 1 2 2
X ( z ) = 1+ z + (
X ( z) = 1 1− z
1 2 −1
)
z + .... + (
−2
1 n 2
)
z −n

数字信号处理课后第三章习题答案

数字信号处理课后第三章习题答案

第3章
离散傅里叶变换(DFT)及其快速算法 (FFT)
题3解图
第3章
离散傅里叶变换(DFT)及其快速算法 (FFT)
4. 证明DFT的对称定理, 即假设X(k)=DFT[x(n)], 证明 DFT[X(n)]=Nx(N-k) 证: 因为
kn X (k ) x(n)WN n 0 N 1
1 x(n) N
所以
DFT[ X (n)] X (n)W
n 0
N 1
N 1
kn N
N 1 mn kn x(m)WN WN n 0 m 0
N 1
n ( m k ) x(m)WN m 0 n 0
N 1
第3章
由于
离散傅里叶变换(DFT)及其快速算法 (FFT)

n 0
N 1
n( m k ) WN
N 0
m N k m N k , 0≤ m ≤ N 1
k=0, 1, …, N-1
所以 DFT[X(n)]=Nx(N-k)
5. 如果X(k)=DFT[x(n)], 证明DFT的初值定理
证: 由IDFT定义式
1 N 1 x(0) X (k ) N k 0
- j mn - j kn 1 j N mn 2π kn (6) X (k ) cos mn WN (e e N )e N 2 N n 0 n 0

N 1

N 1



1 e 2 n 0
N 1
j
2π ( mk ) n N
1 e 2 n 0
1knnknnnnknnnnknnwkx2j2j102j10e1e1e1??????????????????????12100nkkn?离散傅里叶变换dft及其快速算法fft第3章211001011nnknnnnxknwnkn????????????30010010011nknnnnknknnnxknnwwnnwkn?????????????00nnn??1j10sin1e1sinkmmmkknnnnnknnmkwnxkwrkwkn??????????????????????4离散傅里叶变换dft及其快速算法fft第3章52j2j102j102je1eekmnkmnnnnkmnknnnnmnnwkx??????????????je1kmn?????????mkmkn00kn1离散傅里叶变换dft及其快速算法fft第3章6knnnnnnmnnmnnknnwmnnkx2j10102j2jeee212cos????????????????2211jj0011ee22nnmknmknnnnn?????????????????????????????????2j2j2j2je1e1e1e121kmnnkmnkmnnkmn离散傅里叶变换dft及其快速算法fft第3章20nkmknmkmknm????????????0kn170002j211jj71eeeknnnnknnknnnxkw?????????????072j00ee1enknnnxkw???????0210j202sin2e0112sin2nknnknknkn???????????????????????离散傅里叶变换dft及其快速算法fft第3章或110e1e12jj700??????nkkxknn????8解法一直接计算

数字信号处理课后习题答案(全)1-7章

数字信号处理课后习题答案(全)1-7章

第 1 章 时域离散信号和时域离散系统
(3) 这是一个延时器, 延时器是线性非时变系统, 下面证明。 令输入为
输出为
x(n-n1)
y′(n)=x(n-n1-n0) y(n-n1)=x(n-n1-n0)=y′(n) 故延时器是非时变系统。 由于
T[ax1(n)+bx2(n)]=ax1(n-n0)+bx2(n-n0) =aT[x1(n)]+bT[x2(n)]
(5)y(n)=x2(n)
(6)y(n)=x(n2)
(7)y(n)=
n
(8)y(n)=x(n)sin(ωxn(m) )
m0
解: (1) 令输入为
输出为
x(n-n0)
y′(n)=x(n-n0)+2x(n-n0-1)+3x(n-n0-2) y(n-n0)=x(n-n0)+2x(n—n0—1)+3(n-n0-2)
第 1 章 时域离散信号和时域离散系统
题8解图(一)
第 1 章 时域离散信号和时域离散系统
(5) 画x3(n)时, 先画x(-n)的波形(即将x(n)的波形以纵轴为中心翻转180°), 然后再右移2位, x3(n)波形如题2解图(四)所示。
第 1 章 时域离散信号和时域离散系统
题2解图(一)
第 1 章 时域离散信号和时域离散系统
题2解图(二)
第 1 章 时域离散信号和时域离散系统
题2解图(三)
分别求出输出y(n)。
(1) h(n)=R4(n), x(n)=R5(n) (2) h(n)=2R4(n), x(n)=δ(n)-δ(n-2) (3) h(n)=0.5nu(n), xn=R5(n)
解: (1) y(n)=x(n)*h(n)=

数字信号处理第三版(姚天任、江太辉) 答案 第三章

数字信号处理第三版(姚天任、江太辉) 答案 第三章
第三章 离散傅里叶变换及其快速算法习题答案参考
3.1 图 P3.1 所示的序列 x(n) 是周期为 4 的周期性序列。请确定其傅里叶级数的系数 X (k) 。
∑ ∑ ∑ 解: X (k)
=
N −1
x(n)WNnk
=
N −1
x(−n)WNnk
=
−( N −1)
x(n)WN−nk
=
X (−k)
解:图 P3.5_1 所示的是计算这两个序列的周期卷积 x3 (n) 的过程,可以看出,x3 (n) 是 x1 (n) 延时 1 的结果, 即 x3(n) = x1(n −1) 。
3.6 计算下列序列的N点DFT:
(1) x(n) = δ (n)
(2) x(n) = δ [(n − n0 )]N * RN (n), 0 < n0 < N
总计需要时间: (105 + 21)s = 126s
用 FFT 计算 DFT:
复数乘法:
N 2
log2
N
=
5120次, 5120 ×100μ s

0.512s
复数加法: N log2 N = 10240次,10240× 20μs ≈ 0.2048s
总计需要时间: (0.512 + 0.2048)s = 0.7168s
(2) x2 (n) = x ⎡⎣(2 − n)⎤⎦4 R4 (n)
解: x1(n) 和 x2 (n) 的图形如图 P3.7_1 所示:
3.8 图 P3.8 表示一个 4 点序列 x(n) 。 (1)绘出 x(n) 与 x(n) 的线性卷积结果的图形。 (2)绘出 x(n) 与 x(n) 的 4 点循环卷积结果的图形。 (3)绘出 x(n) 与 x(n) 的 8 点循环卷积结果的图形,并将结果与(1)比较,说明线性卷积与循环卷

数字信号处理(方勇)第三章习题答案

数字信号处理(方勇)第三章习题答案

数字信号处理(方勇)第三章习题答案3-1 画出)5.01)(25.01()264.524.14)(379.02()(211211------+--+--=z zz z z z z H 级联型网络结构。

解:23-2 画出112112(23)(465)()(17)(18)z z z H z z z z --------+=--+级联型网络结构。

解:()x n ()y n 243-3 已知某三阶数字滤波器的系统函数为1211252333()111(1)(1)322z z H z z z z -----++=-++,试画出其并联型网络结构。

解:将系统函数()H z 表达为实系数一阶,二阶子系统之和,即:()H z 11122111111322z z z z ----+=+-++ 由上式可以画出并联型结构如题3-3图所示:)题3-3图3-4 已知一FIR 滤波器的系统函数为121()(10.70.5)(12)H z z z z ---=-++,画出该FIR 滤波器的线性相位结构。

解: 因为121123()(10.70.5)(12)1 1.30.9H z zz z z z z ------=-++=+-+,所以由第二类线性相位结构画出该滤波器的线性相位结构,如题3-4图所示:()x n 1-1-1z -题3-4图3-5 已知一个FIR 系统的转移函数为:12345()1 1.25 2.75 2.75 1.23H z z z z z z -----=+--++求用级联形式实现的结构流图并用MATLAB 画出其零点分布及其频率响应曲线。

解: 由转移函数可知,6=N ,且)(n h 偶对称,故为线性相位系统,共有5个零点,为5阶系统,因而必存在一个一阶系统,即1±=z 为系统的零点。

而最高阶5-z 的系数为+1,所以1-=z 为其零点。

)(z H 中包含11-+z 项。

所以:11()()(1)H z H z z -=+。

数字信号处理第三版(姚天任、江太辉) 答案 第三章

数字信号处理第三版(姚天任、江太辉) 答案 第三章

第三章离散傅里叶变换及其快速算法习题答案参考3.1 图P3.1所示的序列(xn 是周期为4的周期性序列。

请确定其傅里叶级数的系数(X k。

解:(111*0((((((N N N nk nk nk N N N n n n X k x n W x n W x n W X k X k −−−−−=====−= =−=∑∑∑3.2 (1设(xn 为实周期序列,证明(x n 的傅里叶级数(X k 是共轭对称的,即*((X k X k =− 。

(2证明当(xn 为实偶函数时,(X k 也是实偶函数。

证明:(1 111**((([(]((N nk N n N N nk nkNNn n Xk x n W Xk x n W xn W X−−=−−−==−=−===∑∑∑ k(2因(xn 为实函数,故由(1知有 *((Xk X k =− 或*((X k X k −= 又因(xn 为偶函数,即((x n x n =− ,所以有(111*0((((((N N N nk nk nk N N N n n n X k x n W x n W x n W X k X k −−−−−=====−= =−=∑∑∑3.3 图P3.3所示的是一个实数周期信号(xn 。

利用DFS 的特性及3.2题的结果,不直接计算其傅里叶级数的系数(Xk ,确定以下式子是否正确。

(1,对于所有的k; ((10Xk X k =+ (2((Xk X k =− ,对于所有的k; (3; (00X=(425(jkX k eπ,对所有的k是实函数。

解:(1正确。

因为(x n 一个周期为N =10的周期序列,故(X k 也是一个周期为N=10的周期序列。

(2不正确。

因为(xn 一个实数周期序列,由例3.2中的(1知,(X k 是共轭对称的,即应有*((Xk X = k −,这里(X k 不一定是实数序列。

(3正确。

因为(xn (0n ==在一个周期内正取样值的个数与负取样值的个数相等,所以有 10(0N n Xx −=∑ (4不正确。

数字信号处理—原理、实现及应用(第4版)第3章 离散傅里叶变换及其快速算法 学习要点及习题答案

数字信号处理—原理、实现及应用(第4版)第3章  离散傅里叶变换及其快速算法 学习要点及习题答案

·54· 第3章 离散傅里叶变换(DFT )及其快速算法(FFT )3.1 引 言本章是全书的重点,更是学习数字信号处理技术的重点内容。

因为DFT (FFT )在数字信号处理这门学科中起着不一般的作用,它使数字信号处理不仅可以在时域也可以在频域进行处理,使处理方法更加灵活,能完成模拟信号处理完不成的许多处理功能,并且增加了若干新颖的处理内容。

离散傅里叶变换(DFT )也是一种时域到频域的变换,能够表征信号的频域特性,和已学过的FT 和ZT 有着密切的联系,但是它有着不同于FT 和ZT 的物理概念和重要性质。

只有很好地掌握了这些概念和性质,才能正确地应用DFT (FFT ),在各种不同的信号处理中充分灵活地发挥其作用。

学习这一章重要的是会应用,尤其会使用DFT 的快速算法FFT 。

如果不会应用FFT ,那么由于DFT 的计算量太大,会使应用受到限制。

但是FFT 仅是DFT 的一种快速算法,重要的物理概念都在DFT 中,因此重要的还是要掌握DFT 的基本理论。

对于FFT 只要掌握其基本快速原理和使用方法即可。

3.2 习题与上机题解答说明:下面各题中的DFT 和IDFT 计算均可以调用MA TLAB 函数fft 和ifft 计算。

3.1 在变换区间0≤n ≤N -1内,计算以下序列的N 点DFT 。

(1) ()1x n =(2) ()()x n n δ=(3) ()(), 0<<x n n m m N δ=- (4) ()(), 0<<m x n R n m N = (5) 2j()e, 0<<m n N x n m N π=(6) 0j ()e n x n ω=(7) 2()cos , 0<<x n mn m N N π⎛⎫= ⎪⎝⎭(8)2()sin , 0<<x n mn m N N π⎛⎫= ⎪⎝⎭(9) 0()cos()x n n ω=(10) ()()N x n nR n =(11) 1,()0n x n n ⎧=⎨⎩,解:(1) X (k ) =1N kn N n W -=∑=21j0eN kn nn π--=∑=2jj1e1ekN n k nπ---- = ,00,1,2,,1N k k N =⎧⎨=-⎩(2) X (k ) =1()N knNM n W δ-=∑=10()N n n δ-=∑=1,k = 0, 1, …, N -1(3) X (k ) =100()N knNn n n W δ-=-∑=0kn NW 1()N n n n δ-=-∑=0kn NW,k = 0, 1, …, N -1为偶数为奇数·55·(4) X (k ) =1m knN n W -=∑=11kmN N W W --=j (1)sin esin k m N mk N k N π--π⎛⎫⎪⎝⎭π⎛⎫ ⎪⎝⎭,k = 0, 1, …, N -1 (5) X (k ) =21j 0e N mn kn N N n W π-=∑=21j ()0e N m k nNn π--=∑=2j()2j()1e1em k N N m k Nπ--π----= ,0,,0≤≤1N k mk m k N =⎧⎨≠-⎩(6) X (k ) =01j 0eN nknN n W ω-=∑=021j 0e N k nN n ωπ⎛⎫-- ⎪⎝⎭=∑=002j 2j 1e1ek NN k N ωωπ⎛⎫- ⎪⎝⎭π⎛⎫- ⎪⎝⎭--= 0210j 202sin 2e2sin /2N k N N k N k N ωωωπ-⎛⎫⎛⎫- ⎪⎪⎝⎭⎝⎭⎡⎤π⎛⎫- ⎪⎢⎥⎝⎭⎣⎦⎡⎤π⎛⎫- ⎪⎢⎥⎝⎭⎣⎦,k = 0, 1, …, N -1或 X (k ) =00j 2j 1e 1e Nk N ωωπ⎛⎫- ⎪⎝⎭--,k = 0, 1, …, N -1(7) X (k ) =102cos N kn N n mn W N -=π⎛⎫ ⎪⎝⎭∑=2221j j j 01e e e 2N mn mn kn N N N n πππ---=⎛⎫ ⎪+ ⎪⎝⎭∑=21j ()01e 2N m k n N n π--=∑+21j ()01e 2N m k n N n π--+=∑=22j ()j ()22j ()j ()11e 1e 21e 1e m k N m k N N N m k m k N N ππ--+ππ--+⎡⎤--⎢⎥+⎢⎥⎢⎥--⎣⎦=,,20,,N k m k N mk m k N M ⎧==-⎪⎨⎪≠≠-⎩,0≤≤1k N - (8) ()22j j 21()sin ee 2j mn mnN N x n mn N ππ-π⎛⎫== ⎪-⎝⎭ ()()112222j j j ()j ()0011()=e e ee 2j 2j j ,2=j ,20,(0≤≤1)N N kn mn mn m k n m k n N N N N N n n X k W Nk m N k N mk k N --ππππ---+===--⎧-=⎪⎪⎨=-⎪⎪-⎪⎩∑∑其他(9) 解法① 直接计算χ(n ) =cos(0n ω)R N (n ) =00j j 1[e e ]2n n ωω-+R N (n )X (k ) =1()N knNn n W χ-=∑=0021j j j 01[e e ]e 2N kn n n N n ωωπ---=+∑=0000j j 22j j 11e 1e 21e 1e N N k k N N ωωωω-ππ⎛⎫⎛⎫--+ ⎪ ⎪⎝⎭⎝⎭⎡⎤--⎢⎥+⎢⎥⎢⎥--⎣⎦,k = 0, 1, … , N -1 解法② 由DFT 共轭对称性可得同样的结果。

数字信号处理英文版课后答案(3)

数字信号处理英文版课后答案(3)

Chapter 3 Solutions3.1 (a) (i) x[0] = 3(ii) x[3] = 5(iii) x[–1] = 2(b) (i)(ii) The sketch for x[n+1] does not show the value of the sample x[5], since this information is not provided in the question.3.2 The impulse function is zero everywhere except n = 0.(a) δ[–4] = 0(b) δ[0] = 1(c) δ[2] = 03.3 (a) This function is a mirror image of the impulse function across the verticalaxis, which means no change occurs.(b) This function shifts the impulse two steps to the right and increases its amplitude to 2.(c) This function is the sum of two impulse functions.3.4 The step function is zero for n < 0 and one everywhere else.(a) u[–3] = 0(b) u[0] = 1(c) u[2] = 13.5 (a) x[n] = 4u[n–1](b) x[n] = –2u[n](c) x[n] = 2u[–n](d) x[n] = u[n–2](e) x[n] = u[2–n]3.6(a)(b)3.7 (a) This signal is a sum of shifted step functions, each with amplitude one. x[n] = 0.1u[n –1] + 0.1u[n –2] + 0.1u[n –3] + …(b) This signal is a sum of impulse functions with increasing amplitude. x[n] = 0.1δ[n –1] + 0.2δ[n –2] + 0.3δ[n –3] + …3.8 x[n] = (u[n] – u[n –2]) + (u[n –5] – u[n –7]) + (u[n –10] – u[n –12])3.9 x[n] = 2δ[n] – 3δ[n –1] + δ[n –2] – δ[n –3] + 3δ[n –4]3.10 (a)x[n] = δ[n –3] + δ[n –4] + δ[n –5] + δ[n –6] – δ[n –7] – δ[n –8] – δ[n –9] – δ[n –10] – δ[n –11] ∑∑==-δ--δ=117k 63k ]k n []k n [(b) x[n] = u[n –3] – 2u[n –7] + u[n –12] 3.11 x[n] = u[n] + 2u[n –4]3.123.13 The signal has values 1, 0.5, 0.25, 0.125, etc. These values can be generated from the function 0.5n , where each value is the amplitude of an impulse function. The signal may be expressed as ∑∞=-δ=0k k ]k n [)5.0(]n [x = δ[n] + 0.5δ[n –1] + 0.25δ[n –2] + 0.125δ[n –3] + …3.14 (a)By Euler’s identity, ⎪⎭⎫ ⎝⎛π-⎪⎭⎫ ⎝⎛π==π-4n sin j 4n cos e]n [x 4n j(b)From (a), 4π=Ω. Therefore, 18422=ππ=Ωπ. The digital period is 8 samples.3.15 (a)⎪⎭⎫⎝⎛π-⎪⎭⎫ ⎝⎛π==π-3n sin j 3n cos e ]n [x 3n j(b) The magnitude of any complex number is the square root of the sum of the squares of the real and imaginary parts. The magnitudes in the last column in (a) show that 3n j eπ- = 1. This equation is true for all n.3.16 The frequency of the analog signal is f = ω/2π = 200/2π Hz. The samplingfrequency f S = 1/T S = 1/(25x10–3) = 40 Hz. The digital frequency is Ω = 2πf/f S = 200/40 = 5 rads. The sampled signal is x[n] = 5sin(n Ω) = 5sin(5n).3.17 Check 2π/Ω for each function. The function is periodic if this ratio is rational. (a) 2π/Ω = 2π/(4/5) = 10π/4 = 5π/2This ratio is not rational, so the sinusoid is not periodic. (b) 2π/Ω = 2π/(6π/7) = 14/6 = 7/3This ratio is rational, and in lowest terms. The number in the numerator, 7, is the number of samples before the sequence repeats. (c) 2π/Ω = 2π/(2π/3) = 3This result may be seen as 3/1. Thus, the sinusoid is periodic with period 3.3.18 (a) From the equation for x(t), ω = 2πf = 1000π, so f = 500 Hz. Since seven samples are collected every three cycles, N = 7 and M = 3, so37M N 2==ΩπThis means SS f 5002f f 276π=π=π=Ω. Solving S f 500276π=π gives f S = 1167 Hz. (b) Since f S > 2f, the sampling rate is adequate to avoid aliasing.3.19 (a) The following samples are graphed below.(b) The ratio 2π/Ω is 2π/(4π/5)=10/4 = 5/2. The numerator, 5, indicates the sinusoidal sequence repeats every five samples. Because the denominator of the ratio is 2, these five samples are collected over two analog periods.(c) The analog signal is superimposed over the digital signal with a dashed line in the figure below.3.20 The analog frequency of x(t) is f = ω/(2π) = 2500π/(2π) = 1250 Hz. The digital frequency of x[n] is π/3 radians. These frequencies must be related through the equationSS f 12502f f 23π=π=π=ΩThe solution to this equation is f S = 7500 Hz. One other solution is possible, since⎪⎭⎫⎝⎛π=⎪⎭⎫ ⎝⎛π-π=⎪⎭⎫ ⎝⎛π3n 5cos 3n n 2cos 3n cos . This view givesSf 1250235π=π=Ωor f S = 1500 Hz. At this frequency, aliasing occurs. The signal appears at a frequency of 250 Hz. This explains why this second sampling rate works:315002502f f 2S π=π=π=Ω3.21 (a) From 052n 92=π+π, n = 59-. The shift moves the function left by 9/5samples. (b) The samples in the two signals do not match, because the shift is not an integer.(c) 951.052)0(92sin ]0[x 1=⎪⎭⎫ ⎝⎛π+π=927.052)1(92sin ]1[x 1=⎪⎭⎫ ⎝⎛π+π=(d) For a phase shift of two samples to the right,0)2(92n 92=θ+π=θ+π, so 94π-=θ. Thus, ⎪⎭⎫ ⎝⎛π-π=94n 92sin ]n [x 1. One period of this signal contains the same sample values as one period of x 2[n]. 3.22 (a)(b)(c)(d) 3.23(a)Since the digital sinusoid is periodic,M 10M N 2==Ωπ. Since Sf f 2π=Ω, M10f f S =. Therefore, 10Mf f S=. Possible frequencies f of the analog signal are defined by M = 1, 3, 7, 9, 11, …, that is, all integers that do not share any factors with 10. Other integers M result in a digital period less than 10. For 4 kHz sampling, the possible frequencies f are 400, 1200, 2800, 3600, 4400, … Hz. (b) The only two frequencies from (a) that lie within the Nyquist range are 400 Hz and 1200 Hz. All other frequencies f, when sampled at 4 kHz, produce aliases at 400 or 1200 Hz.3.24 A 16-bit image uses 16 bits to represent the gray scale level for each pixel in the image. A total of 65,536 gray scale values can be represented with 16 bits.3.25 Each square on the checkerboard is recorded by a 16 x 16 block of pixels. All pixels in the white squares have gray scale value 255. All pixels in the black squares have gray scale value 0.。

第三章数字信号处理课后答案刘顺兰版

第三章数字信号处理课后答案刘顺兰版

第三章数字信号处理课后答案刘顺兰版第三章部分习题解答(数字信号处理(第二版),刘顺兰,版权归作者所有,未经许可,不得在互联网传播)3.1如果一台通用计算机的速度为平均每次复乘需100μs ,每次复加需20μs ,今用来计算N=1024点的)]([n x DFT ,问用直接运算需要多少时间,用FFT 运算需要多少时间?解:∑?=====101010,21024,)()(N n nk N M N Wn x k X直接运算所需的总时间为s N N s N T d μμ20)1(1002×?+×=秒分62126201023102410010242=≈××+×=s s s μμFFT 运算所需总时间为s NM s M N T F μμ201002×+×=s s s 717.02010102410010102421=××+×××=μμ3.2在基-2FFT 算法中,最后一级或开始一级运算的系数10==N p N W W ,即可以不做乘法运算。

问(1)乘法可节省多少次,所占百分比为多少?解:可节省2N 次,所占百分比为 %100log 1%100log 2222×=×N N N N 如 8=N 则为%3.33%10031≈×3.11以20kHz 的采样率对最高频率10kHz 的带限信号()a x t 采样,然后计算)(n x 的1000N =个采样点的DFT ,即210()()N j nk N n X k x n eπ??==∑,1000N =.(1)试求频谱采样点之间的频率间隔是多少?(2)在()X k 中,200k =对应的模拟频率是多少?(3)在()X k 中,700k =对应的模拟频率是多少?解:(1)频谱采样点之间的频率间隔为:20000201000s f f Hz N Δ=== (2)200k =对应的模拟频率为20000200400041000s k f f k Hz kHz N ==×== (3)因700k =大于N/2,故其对应的模拟频率为 20000()300600061000s k f f N k Hz kHz N =?=×== 3.12 对一个连续时间信号)(t x α采样1s 得到一个4096个采样点的序列:(1) 若采样后没有发生频谱混叠,)(t x α的最高频率是多少?(2) 若计算采样信号的4096点DFT,DFT 系数之间的频率间隔是多少Hz?(3) 假定我们仅仅对Hz f Hz 300200≤≤频率范围所对应的DFT 采样点感兴趣,若直接用DFT,要计算这些值需要多少次复乘?若用按时间抽取FFT 则需要多少次?解:(1)由题意可知:4096s f Hz =,故)(t x α的最高频率/22048h s f f Hz == (2)409614096s f f Hz N Δ=== (3)直接用DFT 计算,所需要的复乘次数为(3002001)1014096413696d M N =?+=×=若用按时间抽取FFT 则需要的复乘次数为10log 204812245762F N M N ==×= 3.17若给定两个实序列)(1n x 、)(2n x ,令:)()()(21n jx n x n g +=,)(kG 为其傅里叶变换,可以利用快速傅里叶变换来实现快速运算,试利用傅里叶变换的性质求出用)(k G 表示的)(1n x 、)(2n x 的离散傅里叶变换)(1k X 、)(2k X 。

数字信号处理第三章习题作业答案

数字信号处理第三章习题作业答案

1 e 当 k 2, 4, 6,... 时,X 1 (k ) 0

序列3:
x3 (n) x1 (n) x1 (n 4)
根据序列移位性质可知
X 3 (k ) X1 ( k ) e j k X1 ( k ) (1 e j k )
即 x(n) 是以 n 0 对称轴的奇对称
故这三个序列都不满足这个条件
(3)由于是8点周期序列,其DFS:
nk X (k ) x(n )WN x (n )e n 0 n 0 N 1 7 j 2 nk 8
序列1:
X 1 (k ) e
n 0
3
y 解: 序列 x(n) 的点数为 N1 6 , (n) 的点数为 N 2 15, 故 x(n) y (n) 的点数应为
N N1 N 2 1 20
是线性卷积以15为周期周期延拓后取主值序列 19( N 1) 0
15 ( L)
又 f (n) 为 x(n) 与 y (n) 的15点的圆周卷积,即L=15。
第三章习题讲解
n 1, 0 n 4 h(n) R4 (n 2) 3.设 x(n) 其他n 0, h 令 x(n) x((n))6 , ( n) h((n)) 6 ,
试求 x(n) 与 h (n) 的周期卷积并作图。
解:
y ( n ) x ( m )h ( n m )
4 ( L N 1)
15 ( L)
34 ( L N 1)
混叠点数为N-L=20-15=5 n 0 ~ n 4( N L 1) 故 f (n)中只有 n 5到 n 14的点对应于 x(n) y (n)

数字信号处理习题第三章

数字信号处理习题第三章

第3章频域中的离散时间信号3.16 求下面每个序列的DTFT:(a) x1[n]=αnμ[n−1],|α|<1(b) x2[n]=nαnμ[n],|α|<1(e) x5[n]= αnμ[−n−1],|α|>1答案:(a)X1(e jω)=∑αn e−jωn∞n=1=∑(αe−jω)n=∞n=1∑(αe−jω)n−1=αe−jω1−αe−jω∞n=0(b)X2(e jω)=j dX(e jω)dω=j ddω(11−αe−jω)=αe−jω(1−αe−jω)2(e)X5(e jω)=∑αn e−jωn=∑α−m e jωm=∑α−m e jωm−1=∞m=0∞m=1−1n=−∞e jωα−e jω3.17 求下面每个序列的DTFT:(a) xa[n]= μ[n+2]−μ[n−3](b) xb[n]=αn(μ[n−1]− μ[n−4]),|α|<1(c) xc[n]= 2nαnμ[n],|α|<1答案:(a)设μ[n]的DTFT变换为:μ(e jω)=11−e−jω+∑πδ(ω+2kπ)∞k=−∞Xa(e jω)=(e j2ω−e−j3ω)μ(e jω)=(e j2ω−e−j3ω)[11−e−jω+∑πδ(ω+2kπ)]∞k=−∞(b)设x[n]= αnμ[n],|α|<1,其DTFT变换为:X(e jω)=11−αe−jωXb (e jω)=e−jωX(e jω)−e−j4ωX(e jω)=e−jω−e−j4ω1−αe−jω(c)xc[n]= 2nαnμ[n]=2(n+1)αnμ[n]−2αnμ[n],|α|<1X C (e jω)=2(1−αe−jω)2−21−αe−jω=2αe−jω(1−αe−jω)23.21 求下面每个DTFT的逆DTFT:(a) Xa (e jω)=∑δ(ω+2πk)∞k=−∞(b) Xb (e jω)=e jω(1−e jωN)1−e jω(c) Xc (e jω)=1+2∑cosωιNι=0(d) Xd (e jω)=−αe−jω(1−αe−jω)2,|α|<1答案:(a) xa [n]=12π∫δ(ω)e jωn∞−∞dω=1(b ) X b (e jω)=e jω(1−e jωN )1−e jω=e jω∑ejωnN−1n=0 令m =−n X(ejω)=∑e−jωm −N+1m=0 x[n]={1,−(N −1)≤n ≤00,其他X b (e jω)=e jω∑e−jωm−N+1m=0=e jωX(e jω) X b [n]=x[n+1]={1,−N ≤n ≤−10,其他(c )X c (e jω)=1+2∑cosωιN ι=0=2+∑e−jωιN ι=−N , x c [n]={3,n =01,0<|n |<N 0,其他(d )X 0(e jω)=11−αe −jω x o [n]=αn μ[n]X d (ejω)=−αe −jω(1−αe −jω)2=dX0(e jω)dωx d [n]=n x o [n]=nαn μ[n]3.26 X (e jω)是实序列x[n]的DTFT 。

数字信号处理(方勇)第三章习题答案

数字信号处理(方勇)第三章习题答案

3-1 画出)5.01)(25.01()264.524.14)(379.02()(211211------+--+--=z zz z z z z H 级联型网络结构。

解:243-2 画出112112(23)(465)()(17)(18)z z z H z z z z --------+=--+级联型网络结构。

解:()x n ()y n 243-3 已知某三阶数字滤波器的系统函数为1211252333()111(1)(1)322z z H z z z z -----++=-++,试画出其并联型网络结构。

解:将系统函数()H z 表达为实系数一阶,二阶子系统之和,即:()H z 11122111111322z z z z ----+=+-++ 由上式可以画出并联型结构如题3-3图所示:)题3-3图3-4 已知一FIR 滤波器的系统函数为121()(10.70.5)(12)H z zz z ---=-++,画出该FIR滤波器的线性相位结构。

解: 因为121123()(10.70.5)(12)1 1.30.9H z zz z z z z ------=-++=+-+,所以由第二类线性相位结构画出该滤波器的线性相位结构,如题3-4图所示:1-1-1z -题3-4图3-5 已知一个FIR 系统的转移函数为:12345()1 1.25 2.75 2.75 1.23H z z z z z z -----=+--++求用级联形式实现的结构流图并用MATLAB 画出其零点分布及其频率响应曲线。

解: 由转移函数可知,6=N ,且)(n h 偶对称,故为线性相位系统,共有5个零点,为5阶系统,因而必存在一个一阶系统,即1±=z 为系统的零点。

而最高阶5-z 的系数为+1,所以1-=z 为其零点。

)(z H 中包含11-+z 项。

所以:11()()(1)H z H z z -=+。

1()H z 为一四阶子系统,设12341()1H z bzcz bz z ----=++++,代入等式,两边相等求得12341()10.2530.25H z zz z z ----=+-++,得出系统全部零点,如图3-5(b )所示。

数字信号处理—基于计算机的方法第3章答案

数字信号处理—基于计算机的方法第3章答案

3-2 (a) Sketch the naturally sampled PAM waveform that results from sampling a 1-kHz sine wave at a 4-kHz rate.(b) Repeat part (a) for the case of a flat-topped PAM waveform.Solution:3-4 (a)Show that an analog output waveform (which is proportional to the original input analog waveform) may be recovered from a naturally sampled PAM waveform by using the demodulation technique showed in Fig.3-4.(b) Find the constant of proportionality C, thatis obtained with this demodulation technique , where w(t) is the oriqinal waveform and Cw(t) is the recovered waveform. Note that C is a function of n ,where the oscillator frequency isnfs.Solution:()()()()()()1111sin sin 2cos sin 2cos cos sin [cos 2cos cos sin 2cos s s jk ts k k k jk ts k k s s k s s s s s k n kt kT s t c ek d k d ded d k tk dk dk d w t w t d d k t k d v t w t n tk d w t d n t n d dd k t n tn k ddωωτππωπππωπωππωππωω∞∞-=-∞=-∞∞∞-=-∞=∞=∞=≠-⎡⎤=∏=⎢⎥⎣⎦==+⎡⎤=+⎢⎥⎣⎦==++∑∑∑∑∑∑2]s n t ω211cos cos 222s s n t n tωω=+after LPF:()()()sin sin o w t w t n d d n d n ddn dcw t c ππππ==∴=3-7 In a binary PCM system, if the quantizing noise is not to exceed P ± percent of the peak-to-peak analog level, show that the number of bits in each PCM word needs to be⎪⎭⎫⎝⎛=⎥⎦⎤⎢⎣⎡⎪⎪⎭⎫ ⎝⎛≥P pn 50log 32.350log 10] [log 10102(Hint: Look at Fig. 3-8c.)Solution:Binary PCM M=n2levelsforPPq V P n 100||≤We need)50(log)10(log 50log 5025011002 size step 1022pP n PM P M V P MV nPPPP ≥⎪⎭⎫⎝⎛≥≥=≤≤==δ)(log )(log )(log )(log )(log x b a x x b a b b a ==3-8 The information in an analog voltagewaveform is to be transmitted over a PCM system with a ±0.1% accuracy (full scale). The analog waveform has an absolute bandwidth of 100 Hz and an amplitude range of –10 to +10V .(a) Determine the minimum sampling rate needed.(b) Determine the number of bits needed in each PCM word.(c) Determine the minimum bit rate required in the PCM signal.(d) Determine the minimum absolute channel bandwidth required for transmission of this PCM signal. Solution:(a) Determine the minimum sampling rate needed./sec samples 200)100(22===B f s(b) Determine the number of bits needed in each PCM word.Using the results given in prob. 3-7.(c) Determine the minimum bit rate required in the PCM signal.s f w ords n bits K bits (9)200 1.8 w ord sec sec R ⎛⎫⎛⎫=== ⎪ ⎪⎝⎭⎝⎭(d) Determine the minimum absolute channelbandwidth required for transmission of this920.1%0.1%24250025125009V V V M and n bits a PC M w ord δδδ±=±→====>=→PCM signal.For binary PCM D=RHz9002==⇒D B3-9 An 850-Mbyte hard disk is used to store PCM data. Suppose that a voice-frequency (VF) signal is sampled at 8 ksamples/s and the encoded PCM is to have an average SNR of at least 30dB. How many minutes of VF conversation (i.e., PCM data) can be stored on the hard disk? Solution:53002.6230lg 1022=→=∴=≥=⎪⎭⎫⎝⎛n n M dB MM N S nsec 58sec 40sec 405sec 8kbytes bits byte kbits R kbits sample bits ksamples n f R s =⎪⎭⎫ ⎝⎛⎪⎭⎫ ⎝⎛=⇒=⎪⎪⎭⎫⎝⎛⎪⎭⎫ ⎝⎛==min13,47min 833,2minsec/60sec 10170sec 10170sec10170sec 10510850sec585033336hrs T kbytes Mbytes T ==⨯=⨯=⇒⨯=⨯⨯==3-10 An analog signal with a bandwidth of 4.2 MHz is to be converted into binary PCM and transmitted over a channel, The peak-signal quantizing noise ratio at the receiver output must be at least 55 dB.(a) If we assume that 0=Pe and that there is no ISI, what will be the word length and the number of quantizing steps needed?(b) What will be the equivalent bit rate? (c) What will be the channel null bandwidth required if rectangular pulse shapes are used? Solution:(a) If we assume that 0eP = and that there is no ISI, what will be the word length and the num-ber of quantizing steps needed? Using(3-18),lengthword 9 34.85577.402.6bitsn use n n dB N S peak =⇒≥⇒≥+=⎪⎭⎫⎝⎛steps quantizing 512229===nM(b)sec Mbits6.75Sample bits 9sec 4.8ecMsamples/s4.8)MHz 2.4(22log=⎪⎪⎭⎫ ⎝⎛⎪⎭⎫⎝⎛=====Msamplesn f R f f s anasFor rectangular pulse shapeMHz 6.75==R B null3-12 G iven an audio signal with spectralcomponents in the frequency band 300 to 3000Hz, assume that a sampling rate of 7KHz will be used to generate a PCM signal .Design an appropriate PCM system as follows:a. Draw a block diagram of the PCM system , including the transmitter, channel, receiver.b. S pecify the number of uniform quantization steps needed and the channel null bandwidth required , assume that the peak signal-to-noise ratio at the receiver output needs to be at least 30dB and that polar NRZ signaling is used.c. Discuss how nonuniform quantization canbe used to improve the performance of the system.Solution: (a) 略 (b)lengthword 5 10.43077.402.6bitsn use n n dB N S peak=⇒≥⇒≥+=⎪⎭⎫ ⎝⎛stepsquantizing 32225===nM7sam ples/sec 7 5bits K bits 35 sec Sam ple sec s s f K K sam plesR f n =⎛⎫⎛⎫===⎪⎪⎝⎭⎝⎭()KHzR B null 35==∴( c) uniform quantizing : for all samples,the quantizing noise power is the same 122δ=N↑→↓→NS signal big N S signal smalluniform quantizing is not good for small signal.Nonuniform quantizing: samples are nonlinear processed,Small signal is amplified↑→N S(or small signal ---using small step size ↑→N S )3-14 In a PCM system , the bits error rate dueto channel noise is 10-4. Assume that peak signal-to-noise ratio on the received analog signal needed to be at least 30dB.(a) Find the minimum number of quantizing steps that can be used to encode the analog signal into a PCM signal.(b) If the original analog signal had an absolute bandwidth of 2.7kHz , what is the null bandwidth of PCM signal for the polar NRZ signaling case.Solution: (a) 410-=PedB N S PKout30≥⎪⎭⎫⎝⎛()2231000141PK out S M N M Pe⎛⎫=≥ ⎪+-⎝⎭52206.19===≥n M M use M nKz f s 4.57.22=⨯=27KHz R /274.55===⨯==nullsB sKb nf R 3-17 For a 4 bit PCM system , calculate and sketch a plot of the output SNR(in decibels) as a function of the relative input level , ()20lg rmsx V for(a) A PCM system that uses 10μ= law companding(b) A PCM system that uses uniform quantizationWhich of these system is better to use in practice? Why?Solution: n = 4 bits ---- a PCM word (a)()()()6.02 4.7720lg ln 16.024 4.7720lg ln 11021.25dB SNn dBμ=+-+⎡⎤⎣⎦=⨯+-+⎡⎤⎣⎦=(b)() 6.02 4.7720lg ()6.024 4.7720lg ()28.8520lg ()rm s dBrm s rm s S N n x V x V x V =++=⨯++=+3-19 A multilevel digital communication system sends one of 16 possible levels over the channel every 0.8 ms .(a) What is the number of bits corresponding to each level? (b) What is the baud rate? (c) What is the bit rate? Solution:(a) What is the number of bits corresponding to each level?2164/lL l bits level==⇒=(b) What is the baud rate?311,2500.810secN sym bol D baudT -===⨯(c) What is the bit rate?kbits/sec5)250,1(4===lD R3-20 A multilevel digital communication system is to operate at a data rate of 9,600 bits/s.(a) If 4-bit words are encoded into each level for transmission over the channel, what is the minimum required bandwidth for the channel?(b) Repeat part (a) for the case of 8-bit encoding into each level. Solution:(a) If 4-bit words are encoded into each level for transmission over the channel. What is the min-imum required bandwidth for the channel?(b) Repeat part (a) for the case of 8-bit encoding into each level.600600)1200(2121baud 120089600minHz B HzD B D ===≥==3-24 Consider a random data pattern consisting of binary 1’s and 0’s, where the probability of obtaining either a binary 1 or abinary 0 is21. Calculate the PSD for thefollowing types of signaling formats as a function of b T ,the time needed to send 1 bit of data:(a) Polar RZ signaling where the pulse width isbT 21=τ.(b) Manchester RZ signaling where the pulse width isbT 41=τ. What is the first nullbandwidth of these signals? What is the spectral efficiency for each of these signaling cases? Solution:(a) Polar RZ signaling where the pulse width is bT 21=τ.sin(/2)()[()]2/2b b b T fT F f F f t fT ππ==and the data are independent from bit to bit1:1:210,2n n b a AV AV →+→-,依概率依概率()222:01,221,2nn knFor k A a a a and I A +=⎧⎪⎪===⎨⎪-⎪⎩依概率依概率()2222111(0)()22n n i ii R a a P A A A ===⨯+-⨯=∑The first-null bandwidth is RT B bnull 22==andthe bandwidth efficiency is12R B η==(b) Manchester RZ signaling where the pulse width isbT 41=τ. What is the first nullband-width of these signals? What is the spectral efficiency for each of these signaling cases?()()2,0:3400,0A k Thus R k k ⎧==-⎨≠⎩()()22S s2222222()P ()336T sin (/2)12(/2)sin (/2)4(/2)sj k f T k b b b b b b b F f fR k a T fT A T fT A T fT fT eπππππ∞=-∞=-⎛⎫= ⎪⎝⎭=∑Equation (3-36) can also be used to evaluate the PSD for RZ Manchester signaling where the pulse shape is shown in the figure.⎥⎦⎤⎢⎣⎡-⎪⎪⎭⎫ ⎝⎛=-22)sin()(τωτωτπτπτj j ee f f f F⎪⎭⎫⎝⎛⎪⎪⎭⎫ ⎝⎛=⇒2sin )sin(2)(ωττπτπτf f j f FUsing (3-40) and (3-36), the PSD forManchester signaling is()()2222)][sin(sin 4)(τπτπτπτf f f T A f p b⎥⎦⎤⎢⎣⎡=IfbT 41=τ, this becomes2224sin 44sin 41)(⎥⎦⎤⎢⎣⎡⎪⎭⎫ ⎝⎛⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡⎪⎭⎫⎝⎛⎪⎭⎫ ⎝⎛=b b b b fT fT fT T A f p πππThe first-null bandwidth is RT B bnull 44==and thespectral efficiency is41=η(bits/sec)/Hz.3-29 The data stream 01101000101 appears at the input of a differential encoder. Depending on the initial start-up condition of the encoder, find out two possible differential encoded data streams that can appear at the output. Solution:3-30 Create a practical block diagram for a differential encoding system. Explain how thesystem work by showing the encoding and decoding for the sequence 001111010001. Assume that the reference digit is a binary 1. Show that error propagation can not occur. Solution:3-34 The information in an analog waveform is first encoded into binary PCM and then converted to a multilevel signal for transmission over the channel. The number of multilevels is eight. Assume that the analog signa has a bandwidth of 2700Hz and is tobe reproduced at the receiver output with an accuracy of 1%±(full scall).(a) Determine the minimum bit rate of the PCM signal.(b) Determine the minimum baud rate of the multilevel signal.(c) Determine the minimum absolute channel bandwidth required for transmission of this PCM signal. Solution:1221%50624100V M n V V δδδ±=±→=→==→= m in ()62270032.4/()28332.410.83()5.42s la R nf kb s b L L l R D kBdlD c B kH z==⨯⨯=========3-35 A binary waveform of 9600bits/s is converted into an octal (Multilevel) waveform that is pass through a channel with a raisedcosine-rolloff Nyquist filter characteristic . The channel has a conditioned (equalized) phase response out to 2.4kHz .(a) What is the baud rate of the multilevel signal?(b) What is the rolloff factor of the filtercharacteristic?Solution:09600()8332003()(1)(1) 2.40.52R a L l D Bdl D b B f r r kH z r =→=====+=+=→=3-37 A binary communication system uses polar signal. The overall impulse response is designed to be of thesin x xtype, as given byEq(3-67),so that there will be no ISI. The bitrate is 300/s R f bit s ==.(a) What is the baud rate of the polar signal? (b) Plot the waveform of polar signal at the system output when the input binary data is 01100101. Can you discern the data by looking at this polar waveform? Solution:1502s T f B H z==(b)sin ()s e s f t h t f t ππ=1()eSsf H f f f ⎛⎫= ⎪⎝⎭∏1Ss f DT ==3-43 Using the results of prob.3-42, demonstrate that the following filter characteristics do or do not satisfy Nyquist ’s criterion for eliminating ISI (0022s f f T ==).()()00122eT a H f fT ⎛⎫=⎪⎝⎭∏()()00223eT b H f fT ⎛⎫=⎪⎝⎭∏Solution:()()000012222e T T f a H ffT f ⎛⎫⎛⎫==⎪ ⎪⎝⎭⎝⎭∏∏()()0000232322eT T f b H f fT f ⎛⎫⎪⎛⎫==⎪⎪⎝⎭⎪⎝⎭∏∏3-45 An analog signal is to be converted into a PCM signal that is a binary polar NRZ line code. The signal is transmitted over a channel that is absolutely bandlimited to 4kHz. Assume that the PCM quantizer has 16 steps and that the overall equivalent system transfer function is of the raised cosine-rolloff type with r =0.5.(a) Find the maximum PCM bit rate that can be supported by this system without introducing ISI.(b) Find the maximum bandwidth that canbe permitted for the analog signal . Solution:()0:164 a PC M w ord 40.522 5.33/1T T M n B kH zr B a R D f kb sr==→=====⨯=+量化器()analog analog 2 5.331000667224s b R nf n B R B H zn=≥⋅⨯∴≤==⨯3-47 Multilevel data with an equivalent bit rate of 2,400 bits/s is sent over a channel using a four-level line code that has a rectangular pulse shape at the output of the transmitter. The overall transmission system (i.e., the transmitter, channel, and receiver) has an r =0.5 raised cosine-rolloff Nyquist filtercharacteristic.(a) Find the baud rate of the received signal.(b) Find the 6-dB bandwidth for this transmission system.(c) Find the absolute bandwidth for the system. Solution:(a) Find the baud rate of the received signal.242=⇒==l L l2400/1200aud2D R l B ===(b) Find the 6-dB bandwidth for thistransmission system.611(1200)600H z 22dB B D ===(c) Find the absolute bandwidth for the system.113(1)(10.5)(1200)(1200)900224absolute T B B r D H z==+=+==3-54 One analog waveform w 1(t ) is bandlimited to 3 kHz, and another, w 2(t), is bandlimited to 9 kHz. These two signals are to be sent by TDM over a PAM-type system. (a) Determine the minimum sampling frequency for each signal, and design a TDM commutator and decommutator to accommodate the signals.(b) Draw some typical waveforms for w 1(t ) and w 2(t ), and sketch the corresponding TDM PAM waveform. Solution:(a) Determine the minimum sampling frequency for each signal, and design a TDM commutator and decommutator to accommodate the signals. TDM1122(): 3kH z 6ksam ples/sec (): 9kH z 18ksam ples/secs s t B f t B f ωω=⇒==⇒=(b) Draw some typical waveforms for w 1(t ) and w 2(t ), and sketch the corresponding TDM PAM waveform.3-56 Twenty-three analog signals , each with a bandwidth of 3.4kHz, are sampled at an 8-kHz rate and multiplexed together with a synchronization channel (8kHz)into a TDM PAM signal. This TDM signal is passed through a channel with an overall raised cosine-rolloff Nyquist filter characteristic of r=0.75.(a) Draw a block diagram for the system, indicating the fc of the commutator and the overall pulse rate of the TDM PAM signal.(b) Evaluate the absolute bandwidth required for the channel.Solution:248k pulses/sec=192k pulses/sec D =⨯()()192k pulse/sec110.75168kH z 22D B r =+=+=3-58 Rework Prob.3-56 for a TDM pulse code modulation system in witch an 8-bit quantizer is used to generate the PCM words for each of the analog inputs and an 8-bit synchronization word is used in the synchronization channel.Solution:3-59 Design a TDM PCM system that will accommodate four 300-bit/s (synchronous) digital inputs and one analog input that has a bandwidth of 500Hz. Assume that the analog samples will be encoded into 4-bit PCM word. Draw a block diagram for your design, analogous to Fig.3-39, indicating the data rates at the various points on the diagram. Explain how your design works.Solution:3-60 Design a TDM PCM system that will accommodate two 2400-bit/s synchronous digital inputs and an analog input that has a bandwidth of 2700 Hz. Assume that the analog input is sampled at 1.11111 times the Nyquist rate and converted into 4-bit PCM word. Draw a block diagram for your design, and indicate the data rates at the various points on your diagram. Explain how your TDM scheme works.Solution:。

数字信号处理 刘顺兰第三章完整版习题解答

数字信号处理 刘顺兰第三章完整版习题解答

数字信号处理刘顺兰第三章完整版习题解答一、题目解答1. 题目利用时域抽样、频域抽样、零填充、插值法等,实现信号的变换。

1.1 时域抽样时域抽样是指将一个连续时间信号在时间轴上的等间隔位置上进行采样,可以得到一个离散时间信号。

时域抽样的原理是,将时间轴上的信号按照一定的时间间隔进行采样,每个采样点的振幅值就是该点对应的连续时间信号的振幅值。

时域抽样可以通过以下步骤进行实现:1.假设连续时间信号为x(t),采样频率为Fs(采样频率是指每秒采样的次数),采样间隔为Ts(采样间隔是指相邻两个采样点之间的时间间隔)。

2.根据采样频率和采样间隔,计算出采样点数N:N =Fs * T,其中T为采样时长。

为Ts。

4.在每段的中点位置进行采样,得到N个采样点。

5.将N个采样点按照时域顺序排列,即可得到离散时间信号。

1.2 频域抽样频域抽样是指将一个连续频谱信号在频率轴上的等间隔位置上进行采样,可以得到一个离散频谱信号。

频域抽样的原理是,将频率轴上的信号按照一定的频率间隔进行采样,每个采样频率点上的能量值就是该频率点对应的连续频谱信号的能量值。

频域抽样可以通过以下步骤进行实现:1.假设连续频谱信号为X(f),采样频率为Fs(采样频率是指每秒采样的次数),采样间隔为Δf(采样间隔是指相邻两个采样频率点之间的频率间隔)。

2.根据采样频率和采样间隔,计算出采样点数N:N =Fs / Δf,其中Δf为采样频率点之间的频率间隔。

为Δf。

4.在每段的中点位置进行采样,得到N个采样频率点。

5.将N个采样频率点按照频域顺序排列,即可得到离散频谱信号。

1.3 零填充零填充是指在信号的末尾添加一些零值样本,使得信号的长度变长。

零填充的原理是,通过增加信号的长度,可以在时域和频域上提高信号的分辨率,从而更精确地观察信号的特征。

零填充可以通过以下步骤进行实现:1.假设原始信号为x(n),长度为N。

2.计算需要填充的长度L,L > 0。

数字信号处理答案第三章

数字信号处理答案第三章
1 . Note the pole-zero cancellation at z = 2
= = =
0 0 1 j 2πn e 10 , n = 1, 2, . . . , k. 2
3.3
(a) X1 (z ) = = = = The ROC is (b)
1 3 ∞ 0
1 1 ( )n z −n − 1 ( )n z −n + 3 2 n=−∞ n=0 1
1 −1 1− 3 z
+ +
1 ( )n z n − 1 2 n=0 1 − 1, 1− 1 2z −1 2 z)

1
1−1 −1 3zFra bibliotek(1 −
5 6 1 −1 )(1 3z
< |z | < 2. X2 (z ) = = = 1 ( )n z −n − 2n z −n 3 n=0 n=0 1 1−
1 −1 3z ∞ ∞
nan cosw0 nz −n nan ejw0 n + e−jw0 n −n z 2 60
© 2007 Pearson Education, Inc., Upper Saddle River, NJ. All rights reserved. This material is protected under all copyright laws as they currently exist. No portion of this material may be reproduced, in any form or by any means, without permission in writing from the publisher. For the exclusive use of adopters of the book Digital Signal Processing, Fourth Edition, by John G. Proakis and Dimitris G. Manolakis. ISBN 0-13-187374-1.

数字信号处理课后答案+第3章(高西全丁美玉第三版)

数字信号处理课后答案+第3章(高西全丁美玉第三版)


N [δ( k ) − 1] X (k ) = k 1 − WN
k = 1, 2, ⋯, N − 1
当k=0时, 可直接计算得出X(0)为
N ( N − 1) X ( 0) = ∑ n ⋅ W = ∑ n = 2 n=0 n =0
N −1 0 N N −1
这样, X(k)可写成如下形式:
N ( N − 1) 2 X (k ) = −N k 1 − W N , k =0 k = 1, 2, ⋯ , N − 1
解法二 由DFT共轭对称性可得同样结果。 因为
x9 (n) = cos(ω 0 n) ⋅ R N (n) = Re[ x 7 (n)]
1 * X 9 (k ) = X 7e (k ) = [ X 7 (k ) + X 7 ( N − k )] 2
jω 0 N − jω 0 N 1 1− e 1− e = + 2π 2π 2 j(ω0 − k ) − j(ω0 + ) k N N 1 − e 1− e
=
1− e
−j
2π (m−k ) N N 2π (m−k ) N
1− e
−j
N = 0
k =m k≠m
0≤k≤N-1
(6) X (k ) = ∑ cos
n =0
N −1
1 2π kn mn ⋅ WN = (e 2 N n =0

N −1
j
2π mn N
+e
-j
2π 2π mn - j kn N )e N
1 x ( 0) = N
∑ X (k )
n = 0, 1, ⋯ , N − 1
1 x( n) = N

数字信号处理 答案 第三章

数字信号处理 答案 第三章

解: x1 ( n) 和 x2 (n) 的图形如图 P3.7_1 所示:
3.8 图 P3.8 表示一个 4 点序列 x( n) 。 (1)绘出 x( n) 与 x( n) 的线性卷积结果的图形。 (2)绘出 x( n) 与 x( n) 的 4 点循环卷积结果的图形。 (3)绘出 x( n) 与 x( n) 的 8 点循环卷积结果的图形,并将结果与(1)比较,说明线性卷积与循环卷 积之间的关系。
j [(2π k /10) + (π /10)]
={
3.7
N ,k=m或 k=−m 2 0,其 他
图 P3.7 表示的是一个有限长序列 x( n) ,画出 x1 ( n) 和 x2 (n) 的图形。 (1) x1 ( n) = x ⎡ ⎣( n − 2 ) ⎤ ⎦ 4 R4 (n)
(2) x2 ( n) = x ⎡ ⎣( 2 − n ) ⎤ ⎦ 4 R4 (n)
解: (1) X ( k )
= ∑ δ (n)WNnk = δ (0) = 1, 0 ≤ k ≤ N − 1
n=0
N −1
(2) X ( k ) =
∑ δ [(n − n )]
n =0 0
N −1
N
RN (n)WNnk = WNn0 k , 0 ≤ k ≤ N − 1
(3) (4)
X (k ) = ∑ a W
− jω N
−j
N ω 2
j
N ω 2
−j
N ω 2
⎛N ⎞ sin ⎜ ω ⎟ N −1 ) ⎝ 2 ⎠ e− j 2 ω = sin
ω
2
⎛N ⎞ sin ⎜ ω ⎟ ⎝ 2 ⎠ , ϕ (ω ) = − N − 1 ω | X (e jω ) |= ω 2 sin 2

数字信号处理第三章习题答案

数字信号处理第三章习题答案
1 最小记录时间 ; 2 最大取样间隔 ; 3 最少采样点数 ; (4)在频带宽度不变的情况下, 将频率分辨率提高一倍的N值。
解 (1) 已知F=50Hz (2) (3)
(4)频带宽度不变就意味着采样间隔T不变, 应该使记录时间 扩大一倍为0.04s实现频率分辨率提高1倍(F变为原来的1/2).



(a)、(b)、(c)所示。
分别如题3解图
x1(n) (a)
x2(n) (b)
y (n)
(a)
(b)
(c) (c)
5.如果X(k)=DFT[ x(n)], 证明DFT的初值定 理 证明 由IDFT定义式
可知
14.两个有限长序列x(n)和y(n)的零值区间为 x(n)=0, n<0, 8≤n y(n)=0, n<0, 20 ≤ n
对每个序列作20点DFT, 即
X (k)=DFT [x(n)],
Y(k)=DFT [y(n)],
如果
F(k)=X(k)▪Y(k),
k=0,1,…,19 k=0,1,…,19 k=0,1,…,19
f(n)=IDFT [F(k)], k=0,1,…,19
试问在哪些点上f(n)=x(n)*y(n)?为什么?
解 如前所述, 记
,而
fl(n)长度为27,f(n)长度为20.前面已推出二者的关系为
只有在如上周期延拓序列中无混叠的点上, 才满足f(n)=fl(n)7
21-47
41-67
1-7
21-27
8-20
7-19 当从0开始时候
15.用微处理器对实数序列作谱分析, 要求谱分辨率F≤50Hz, 信号最高频率为1kHz, 试确定以下各参数;
教材第三章习题解答

《数字信号处理》朱金秀第三章习题及参考答案

《数字信号处理》朱金秀第三章习题及参考答案

第三章习题答案 3.1 (1)非周期(2)N=1 (3)N=10 (4)N=4 (5)N=20 3.2 02s f f ωπ=,1s sf T = (1)0153,2f ωπ==;0.3s T =,05f π= (2)010,25f ωπ==;0.3s T =,0503f =(3)0,0.55f πω==;0.3s T =,013f =(4)03.5,8.75f ωπ==;0.3s T =,0356f =(5) ()()()(){}0.20.210.20.20.20.2(0.2)(0.2)1cos(0.2)()2130.6cos(0.2)() 1.8()0.6()211.80.6()0.6()2110.910.610.6j n j n n n j n j n n nj n j n j j n e e F n u n F e e u n F e u n F e u n ee ππππππωπωπππ-+-----+=+⎡⎤⎡⎤-=-•+-⎢⎥⎣⎦⎣⎦⎡⎤⎡⎤=-•-+-⎣⎦⎣⎦⎛⎫=-+ ⎪++⎝⎭3.3 function [X]=myDTFT(x, n, w)% 计算DTFT% [X]=myDTFT(x, n, w) %X=输出的DTFT 数组 %x=输入的有限长序列 %n=样本位置行向量 %w=频率点位置行向量 X=x*exp(-j*n ’*w)3.4 (1) 7()10.3j j X e eωω-=- (2)20.51()(10.5)10.5j j j j e X e e e ωωωω---=---(3)2()0.80.1610.4j j j e X e e ωωω--=⨯⨯-(4)112210.920.9()(10.9)10.9(10.9)j j j j j j e e X e e e e ωωωωωω-----⨯-⨯=-=---3.5(1) 23456()642246j j j j j j j X e e e e e e e ωωωωωωω------=++++++(2)234567()642246j j j j j j j j X e e e e e e e e ωωωωωωωω-------=+++++++ (3)234567()642246j j j j j j j j X e e e e e e e e ωωωωωωωω-------=+++---- (4)235678()642246j j j j j j j j X e e e e e e e e ωωωωωωωω-------=+++----3.6 00()()11()211j j j A X e ae ae ωωωωω---+⎡⎤=+⎢⎥--⎣⎦3.7 N=5,()5611()11j j j j j j e ee X e e e ωωωωωω----=+--N=25,()252611()11j j j j j j e e eX e e e ωωωωωω----=+-- N=100,()10010111()11j j j j j j e ee X e e e ωωωωωω----=+-- N=5,》n = -5:5; x =ones(1,11); % x(n)k = -500:499; w = (pi/500)*k; % [-pi, pi] X =1/11* x*exp(-j*pi/500*n'*k); % DTFT magX = abs(X); angX = angle(X); realX = real(X); imagX = imag(X); subplot(2,2,1); plot(w/pi,magX); gridxlabel('以pi 为单位的频率'); title('幅度部分'); ylabel('幅值') subplot(2,2,2); plot(w/pi,angX); gridxlabel('以pi 为单位的频率'); title('相位部分'); ylabel('弧度')-1-0.500.5100.51以pi 为单位的频率幅度部分幅值-1-0.500.51-4-2024以pi 为单位的频率相位部分弧度N=25,>> n = -25:25; x =ones(1,51); % x(n)k = -500:499; w = (pi/500)*k; % [-pi, pi] X =1/51* x*exp(-j*pi/500*n'*k); % DTFT magX = abs(X); angX = angle(X); realX = real(X); imagX = imag(X); subplot(2,2,1); plot(w/pi,magX); gridxlabel('以pi 为单位的频率'); title('幅度部分'); ylabel('幅值') subplot(2,2,2); plot(w/pi,angX); gridxlabel('以pi 为单位的频率'); title('相位部分'); ylabel('弧度')-1-0.8-0.6-0.4-0.200.20.40.60.81以pi 为单位的频率相位部分弧度-1-0.8-0.6-0.4-0.200.20.40.60.81以pi 为单位的频率幅度部分幅值N=100,>> n = -100:100; x =ones(1,201); % x(n)k = -500:499; w = (pi/500)*k; % [-pi, pi] X =1/201* x*exp(-j*pi/500*n'*k); % DTFT magX = abs(X); angX = angle(X); realX = real(X); imagX = imag(X); subplot(2,2,1); plot(w/pi,magX); gridxlabel('以pi 为单位的频率'); title('幅度部分'); ylabel('幅值') subplot(2,2,2); plot(w/pi,angX); gridxlabel('以pi 为单位的频率'); title('相位部分'); ylabel('弧度')-1-0.500.5100.51以pi 为单位的频率幅度部分幅值-1-0.500.51-4-2024以pi 为单位的频率相位部分弧度随着N 的增大,DTFT 的幅度特性主瓣越尖锐,旁瓣越小,越接近于1)(=n x 的DTFT 特性。

  1. 1、下载文档前请自行甄别文档内容的完整性,平台不提供额外的编辑、内容补充、找答案等附加服务。
  2. 2、"仅部分预览"的文档,不可在线预览部分如存在完整性等问题,可反馈申请退款(可完整预览的文档不适用该条件!)。
  3. 3、如文档侵犯您的权益,请联系客服反馈,我们会尽快为您处理(人工客服工作时间:9:00-18:30)。
j [(2π k /10) + (π /10)]
jω jω jω
X ( z) =
n =−∞


RN (n) z − n = ∑ z − n =
n =0 N −1 −k N
N −1
1− z−N 1 − z −1
N −1 −k N N −1 j 2π k N
=
∏ (z −W ) ∏ (z −W ) ∏ (z − e z N −1 k =0 = = k =1 N −1 = k =1 N −1 N −1 N −1 z ( z − 1) z ( z − 1) z z
j 2π k N
)
极点: z0 = 0( N − 1阶) ;零点: z pk = e 图 P3.11_1(1)是极-零点分布图。
, k = 1, 2,..., N − 1
(2) X (e

) = X ( z ) |z =e jω =
1− e (e e −e = 1 1 1 − jω j ω −j ω −j ω 1− e 2 2 e (e − e 2 )
− jω N
−j
N ω 2
j
N ω 2
−j
N ω 2
⎛N ⎞ sin ⎜ ω ⎟ N −1 ) ⎝ 2 ⎠ e− j 2 ω = sin
ω
2
⎛N ⎞ sin ⎜ ω ⎟ ⎝ 2 ⎠ , ϕ (ω ) = − N − 1 ω | X (e jω ) |= ω 2 sin 2
图 P3.11_1(2)所示的是频谱幅度 | X (e ) | 的函数曲线。

(3)
X ( k ) = ∑ RN ( n)W
n =0
N −1
nk N
1 − WNNk 1 − e − j 2π k N ,k =0 = = = X (e jω ) 2π = { 0, k =1,2,..., N −1 2π k ω= k k −j 1 − WN N N 1− e
2π (k = 0,1, 2,..., N − 1) 上的取样值。 N
r =−∞


n + rN
an u (n + rN ) = , n = 0,1,..., N − 1 1− aN
3.11 若长为 N 的有限长序列 x( n) 是矩阵序列 x( n) = RN ( n) 。 (1)求 Ζ[ x( n)] ,并画出及其-零点分布图。 (2)求频谱 X (e ) ,并画出幅度 | X (e ) | 的函数曲线。 (3)求 x(n) 的 DFT 的闭式表示,并与 X (e ) 对照。 解: (1)
证明: (1)
(− k ) = ∑ x ( n )WN− nk X
n =0
N −1
* (− k ) = [∑ x (k ) ( n )WN− nk ]* = ∑ x ( n )W Nnk = X X
n=0 n=0
N −1
N −1
(n) 为实函数,故由(1)知有 (2)因 x (k ) = X * (−k ) 或 X (−k ) = X * (k ) X (n) 为偶函数,即 x (n) = x (− n) ,所以有 又因 x
nk nk (k ) = ∑ x (n)WN (−n)WN X = ∑x = n =0 n =0 N −1 N −1 − ( N −1)

n =0
− nk (−k ) = X * (k ) (n)WN x =X
3.3
(n) 。利用 DFS 的特性及 3.2 题的结果,不直接计算其傅里叶级 图 P3.3 所示的是一个实数周期信号 x (k ) ,确定以下式子是否正确。 数的系数 X (k ) = X (k + 10) ,对于所有的 k; (1) X (k ) = X (− k ) ,对于所有的 k; (2) X (0) = 0 ; (3) X
3.9 x( n) 是一个长度为 N 的序列,试证明 x[(− n)]N = x[( N − n)]N 。 证明:因为 x[( − n)]N 是由 x( n) 周期性重复得到的周期序列,故可表示为 x[(− n)]N = x[( − n + rN )]N 取 r=1,上式即为 x[(− n)]N = x[( N − n)]N 。 3.10 已 知 序 列 x( n) = a u ( n), 0 < a < 1 。 现 在 对 其 Z 变 换 在 单 位 圆 上 进 行 N 等 分 取 样 , 取 值 为
( k )e (4) X
jk
2π 5
,对所有的 k 是实函数。
(k ) 也是一个周期为 N=10 的周期序列。 (n) 一个周期为 N=10 的周期序列,故 X 解: (1)正确。因为 x (k ) 是共轭对称的,即应有 (n) 一个实数周期序列,由例 3.2 中的(1)知, X (2)不正确。因为 x (k ) 不一定是实数序列。 (k ) = X * (− k ) ,这里 X X ( n) 在 一 个 周 期 内 正 取 样 值 的 个 数 与 负 取 样 值 的 个 数 相 等 , 所 以 有 (3)正确。因为 x
n
X (k ) = X ( z ) |z =W − k ,求有限长序列的 IDFT。
N
解:在 z 平面的单位圆上的 N 个等角点上,对 z 变换进行取样,将导致相应时间序列的周期延拓,延 拓周期为 N,即所求有限长序列的 IDFT 为
x p ( n) =
r =−∞
∑ x(n + rN ) = ∑ a
第三章 离散傅里叶变换及其快速算法习题答案参考
3.1
(k ) 。 (n) 是周期为 4 的周期性序列。请确定其傅里叶级数的系数 X 图 P3.1 所示的序列 x
(n)WNnk = ∑ x (−n)WNnk = 解: X ( k ) = ∑ x
n =0 n =0
N −1
N −1
− ( N −1)

n =0
(−k ) = X * (k ) (n)WN− nk = X x
*
3.2
(k ) = X (−k ) 。 (k ) 是共轭对称的,即 X (n) 为实周期序列,证明 x (n) 的傅里叶级数 X (1)设 x (k ) 也是实偶函数。 (n) 为实偶函数时, X (2)证明当 x
(0) = 1 X (2) = X (4) = 0 X 2 = 1− j 3 1 − (1 − j 3) / 2 (3) = 2 = 1 X 1 − e − jπ (1) = X (5) = X 2 = 1+ j 3 1 − (1 + j 3)
(k ) 的图形如图 3.4_1 所示: ( n) 和 X x
解: (1)图 P3.8_1(1)所示的是 x( n) 与 x( n) 的线性卷积结果的图形。 (2)图 P3.8_1(2)所示的 x( n) 与 x( n) 的 4 点循环卷积结果的图形。 (3)图 P3.8_1(3)所示的 x( n) 与 x( n) 的 8 点循环卷积结果的图形。 可以看出, x( n) 与 x( n) 的 8 点循环卷积结果的图形与(1)中 x( n) 与 x( n) 的线性卷积结果 的图形相同。
解: x1 ( n) 和 x2 (n) 的图形如图 P3.7_1 所示:
3.8 图 P3.8 表示一个 4 点序列 x( n) 。 (1)绘出 x( n) 与 x( n) 的线性卷积结果的图形。 (2)绘出 x( n) 与 x( n) 的 4 点循环卷积结果的图形。 (3)绘出 x( n) 与 x( n) 的 8 点循环卷积结果的图形,并将结果与(1)比较,说明线性卷积与循环卷 积之间的关系。
={
3.7
N ,k=m或 k=−m 2 0,其 他
图 P3.7 表示的是一个有限长序列 x( n) ,画出 x1 ( n) 和 x2 (n) 的图形。 (1) x1 ( n) = x ⎡ ⎣( n − 2 ) ⎤ ⎦ 4 R4 (n)
(2) x2 ( n) = x ⎡ ⎣( 2 − n ) ⎤ ⎦ 4 R4 (n)
3.5 计算下列序列的 N 点 DFT: (1) x(n) = δ (n) (2) x(n) = δ [( n − n0 )]N * RN (n), 0 < n0 < N (3) x(n) = a , 0 ≤ n ≤ N − 1
n
(4) x(n) = cos(
2π nm), 0 ≤ n ≤ N − 1, o < m < N N
n n =0
N −1
nk N
1 − a NWNNk 1− aN = = , 0 ≤ k ≤ N −1 k 1 − aWNk 1 − aWN
π 2π 2π nm − j nm ⎞ − j nk 2π 1 N−1⎛ j 2N nk +e N ⎟e N X(k) = ∑cos( nmW ) N = ∑⎜e N 2 n=0 ⎝ n=0 ⎠
N−1 − j 2π (k−m) − j 2π (k+m) ⎞ − − e e 1⎛ 1 1 ⎟ = ⎜ + 2π 2π − j (k+m) ⎟ 2⎜ − j N (k−m) 1−e N ⎝1−e ⎠ N+1 N+1 ⎞ − jπ (k−m) − jπ (k+m) jπ (k−m) jπ (k+m) −j −j (k+m)π (k−m)π − − e e e e 1⎛ N N ⎟ = ⎜ π + π e e π π j (k+m) − j (k+m) ⎟ 2⎜ j N(k−m) − j N(k−m) −e e N −e N ⎝e ⎠ N+1 N+1 sin ⎡ −j (k−m)π −j (k+m)π ⎫ ( k −m) π⎤ ( k +m) π⎤ 1⎧ ⎪ sin ⎡ ⎪ ⎣ ⎦ ⎣ ⎦ N N e e = ⎨ + ⎬ 2⎪ k m N k m N sin π / sin π / − + ⎡ ⎤ ⎡ ⎤ ) ⎦ ) ⎦ ⎪ ⎣( ⎩ ⎣( ⎭
相关文档
最新文档