尔雅Digital Signal Processing_1章节答案(学习通2023课后作业答案)

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尔雅Digital Signal Processing_1章节答案(学习通2023课后作业答案)

1st Week: Unit 1 Introduction

1.1 Signals and Digital Signals随堂测验

1、尔雅For the time signal,章作业 please select the correct answers in the following statement.
A、A continuous-time signal must be an analog signal
B、节答A discrete-time signal must be a digital signal
C、案学An analog signal must be a continuous-time signal
D、习通A digital signal must be a signal with discrete-valued amplitudes

1.2 Digital Signal Processing and Application随堂测验

1、课后The答案 reliability of digital system comes from the fact that digital signals are represented in two states: 0 and 1. 0 and 1 are represented by the level and the presence or absence of pulses, and can be well recognized and restored to 0 and 1, even if they are disturbed by noise within a certain range.

2nd Week: Unit 2 Discrete-Time Signals in the Time Domain

2.1 Time Domain Representation of Discrete-Time Signals随堂测验

1、
A、尔雅0
B、章作业5
C、节答4
D、案学uncertain

2、习通The课后 left-sided sequence is the anti-causal sequence.

2.2 Operations on Sequences随堂测验

1、
A、答案
B、尔雅
C、
D、The rest of the options are wrong

2.3 Operations on Finite-Length Sequences随堂测验

1、
A、-4
B、3
C、4
D、10

2.4 Classification of Sequences随堂测验

1、Let x[n] and y[n] be conjugate-symmetric and conjugate-antisymmetric sequences respectively, then the sequence u[n]=x[n]y[n] is
A、conjugate-symmetric sequence
B、conjugate-antisymmetric sequence
C、conjugate-symmetrical part
D、conjugate-antisymmetric part

2.5 Typical Sequences随堂测验

1、
A、
B、
C、
D、

3rd Week: Unit 3 Discrete-Time Signals in the Frequency Domain

3.1 Review of Continuous Time Fourier Transform (CTFT)随堂测验

1、The Fourier transform does not reduce the amount of data recording the signal.

3.2 Discrete-Time Fourier Transform (DTFT)随堂测验

1、
A、1
B、
C、
D、

3.3 Discrete-Time Fourier Transform (DTFT) Theorems随堂测验

1、
A、
B、
C、
D、

4th Week: Unit 4 Sampling and Recovery of Analog Signal

4.1 Analysis of Sampling in Time Domain随堂测验

1、Continuous-time sinusoidal signals of different frequencies may get the same discrete-time sequence after sampling.

4.2 Analysis of Sampling in Frequency domain and sampling theorem随堂测验

1、The relationship between the sampled signal spectrum and the original signal spectrum is
A、The sampled signal spectrum is a periodic copy of the original signal spectrum and multiplied by 1 / T (T is the sampling interval)
B、The sampled signal spectrum is the same as the original signal spectrum
C、The sampled signal spectrum has no relationship with the original signal spectrum
D、The rest of the options are wrong

2、A 4 second long continuous-time signal is sampled uniformly without aliasing to produce a finite-length sequence containing 8500 sample points. The highest frequency component that may exist in the continuous-time signal is
A、2125 Hz
B、1062.5Hz
C、4250Hz
D、uncertain

4.3 Recovery of analog signal随堂测验

1、Which of the following filters is the reconstruction filter that recovers the analog signal from the discrete-time signal?
A、Analog high-pass filter
B、Digital low-pass filter
C、Digital high-pass filter
D、Analog low-pass filter

5th Week: Unit 5 z-Transform

5.1 Overview of the z-Transform随堂测验

1、DTFT is the z-transform on the unit circle.

5.2 Region of Convergence of the z-Transform随堂测验

1、The possible shapes of the region of convergence of z-transform of a sequence are:
A、disc
B、sector
C、ring
D、entire z-plane

2、Different time-domain sequences may have the same z-transform expression and region of convergence.

5.3 Rational z-Transform and the Region of Convergence随堂测验

1、The shape of the region of convergence of the z-transform of the two-sided sequence is a ring domain or an empty set.

5.4 Properties of the z-Transform随堂测验

1、After the sequence shifts in time, the region of convergence of the z-transform may have to remove z=0 or z=∞.

5.5 The Inverse z-Transform随堂测验

1、The inverse z-transform of is
A、
B、
C、
D、

6th Week: Unit 6 Discrete-Time Systems in the Time Domain

6.1 Examples of Discrete-Time Systems随堂测验

1、The median of a set of (2K + 1) numbers refers to the number in the middle. For example, med { 2, -3,10,5, -1} = 10.

2、The median filter can effectively filter out random white noise.

6.2 Classification of Discrete-Time Systems随堂测验

1、y[n]=2x[n]+5 is a linear system.

2、Both the up-sampler and the down-sampler are time-varying systems.

6.3 Time Domain Representation of Discrete-Time Systems随堂测验

1、An LTI discrete-time system can be completely characterized by its impulse response.

2、In an LTI discrete-time system, if the input sequences are different, the impulse responses of the system are also different.

3、The output sequence of any discrete system is equal to the linear convolution of the input sequence and the impulse response of the system.

6.4 Time Domain Representation of Stability and Causality随堂测验

1、The impulse response of an LTI discrete-time system is h[n]=δ[n+4], and its causality and stability are respectively:
A、Causal, stable
B、Causal, unstable
C、Noncausal, stable
D、Noncausal, unstable

2、

7th Week: Unit 7 Discrete-Time Systems in the z-Domain and Frequency Domain (1)

7.1 z Domain Representation of LTI Discrete-Time Systems随堂测验

1、For the transfer function of an LTI discrete-time system, which of the following statements is correct?
A、The transfer function of a FIR filter has no poles.
B、The transfer function of a FIR filter must have no denominator polynomial.
C、The transfer function of an IIR filter must have denominator polynomial.
D、The transfer function of an IIR filter has no poles.

2、Which of the following are the expressions of transfer function in an LTI discrete-time system?
A、
B、
C、
D、

7.2 z Domain Representation of Stability and Causality随堂测验

1、The FIR filter with a bounded impulse response h[n] must be stable.

8th Week: Unit 7 Discrete-Time Systems in the z-Domain and Frequency Domain (2)

7.3 Frequency Domain Representation of LTI Discrete-Time Systems随堂测验

1、The frequency response can be computed from the transfer function ( ) of the z-plane?
A、on the unit circle
B、within the unit circle
C、in the left half plane
D、outside the unit circle

7.4 Geometric Interpretation of Frequency Response Computation随堂测验

1、Consider an LTI discrete-time system with transfer function . The system is a high-pass filter when
A、a = 0.7
B、a = -0.8
C、
D、a = j

7.5 The Concept of filtering随堂测验

1、A discrete-time signal is obtained by uniformly sampling a continuous-time signal composed of a weighted sum of three sinusoidal signals of frequencies 100Hz, 200Hz and 300Hz. In order to retain the frequency component at 200Hz and filter out other components, the type and cut-off frequency of the filter are:
A、Low pass filter, 150Hz
B、High pass filter, 250Hz
C、Bandpass filter, 150Hz and 250Hz
D、Band-stop filter, 150Hz and 250Hz

2、In order to filter out the power-line interference in the signal, the interfered signal can be passed through a notch filter with the notch frequency 50Hz.

9th Week: Unit 8 Discrete Fourier Transform (1)

8.1 Discrete Fourier Series (DFS)随堂测验

1、Do DFS on the time domain sequence with period N to get the frequency domain periodic sequence with period ( ).

8.2 Discrete Fourier Transform (DFT)随堂测验

1、Determine 2-point DFT of 2-point time sequence, the DFT transformation matrix is :
A、
B、
C、
D、

2、The DFT of a sequence is the uniform sampling of DTFT of the same sequence between
A、
B、
C、
D、the entire frequency axis

10th Week: Unit 8 Discrete Fourier Transform (2)

8.3 Circular Shift and Circular Convolution随堂测验

1、Consider two length-N sequences, both defined for , perform N-point circular convolution on them, the resulting sequence still falls on

8.4 Linear Convolution, Periodic Convolution and Circular Convolution随堂测验

1、Consider the linear convolution of two 4-points sequences is { -6, 3, 12, 7, 6, -1, 5}, their 4-point circular convolution is :
A、
B、
C、
D、

11th Week: Unit 9 Fast Fourier Transform

9.1 Application and Algorithms of FFT随堂测验

1、The number of complex multiplication and complex addition for direct calculation of 8-point DFT are respectively ( ) and ( )
A、32 28
B、64 56
C、28 32
D、56 64

9.2 Decimation in Time Radix-2 FFT (DIT) Algorithm随堂测验

1、( )-point radix-2 DIT FFT can be used on one input sequence with length of 9.
A、2
B、4
C、8
D、16

9.3 Decimation in Frequency Radix-2 FFT (DIF) Algorithm随堂测验

1、In 4-point DIF FFT, how many butterfly graph will appear when a 4-point DFT is decomposed into 2-point DFT?
A、1
B、2
C、3
D、5

9.4 IDFT Calculation with FFT随堂测验

1、Use FFT to get IDFT, the result is time domain sequence rather than frequency domain sequence.

9.5 Linear Convolution with FFT随堂测验

1、( )-point radix-2 FFT can realize the fast convolution of 11-point and 18-point sequence.
A、11
B、18
C、28
D、32

12th Week: Unit 10 IIR Digital Filters Design

10.1 Preliminary Considerations随堂测验

1、h[n] corresponding to each of the four ideal filters is non-causal and of infinite length.

10.2 Impulse Invariance Design Method随堂测验

1、The impulse invariance method is only suitable for designing band-limited filters due to the frequency aliasing effect.

10.3 Bilinear Transformation Method随堂测验

1、The bilinear transformation maps the left-half s-plane onto _____ of the z-plane, and the imaginary axis of the s-plane onto _______ of the z-plane.
A、outside the unit circle, the unit circle
B、inside the unit circle, the unit circle
C、upper half plane, upper half unit circle
D、left half plane,lower half unit circle

10.4 Analog Prototype Lowpass Filter Design随堂测验

1、The amplitude-frequency characteristics of Butterworth analog low-pass filters decrease monotonically with increasing frequency.

10.5 LP AF to LP DF and HP DF随堂测验

1、The bilinear transformation that directly maps the analog low-pass filter to a digital high-pass filter is .

13th Week: Unit 11 Linear Phase FIR Digital Filters

Linear Phase FIR Digital Filters随堂测验

1、The possible number of zeros of a linear-phase FIR digital filter can be
A、1
B、2
C、4
D、8

2、Compared with IIR filters, FIR filters have the advantage that FIR filters are all linear-phase.

3、The impulse response of a linear-phase FIR digital filter follows the equation h[n]=h[N-n] or h[n]=-h[N-n] where N is the order of the filter.

14th Week: Unit 12 FIR Digital Filters Design

12.1 FIR Filter Design Based on Windowed Fourier Series随堂测验

1、 is a real even function when designing linear phase low-pass filters by window method.

12.2 The Effect of Windowing on Filter Frequency Response随堂测验

1、The effect of increasing the window length is to improve the minimum stopband attenuation.

12.3 Design of FIR DF Based on Frequency Sampling Method随堂测验

1、The cut-off frequency of the frequency sampling method can be controlled.

15th Week: Unit 13 Digital Filter Structures

13.1 Classical Representation of Digital Filters随堂测验

1、Different network structures have different effects, which are reflected in ( ).
A、different computational complexity
B、different storage capacity
C、different operating errors
D、different levels of convenience when adjusting the frequency response

13.2 Basic FIR Digital Filter Structures随堂测验

1、A cascade realization of an FIR filter with length 9 requires ( ) second-order section.
A、9
B、4
C、8
D、5

2、The symmetry (or antisymmetry) property of a linear-phase FIR filter can be exploited to reduce the total number of multipliers into almost half of that in the direct-form implementation.

13.3 Basic IIR Digital Filter Structures随堂测验

1、Among all the realization structures of IIR filters, ( ) structure has the highest operation efficiency
A、direct-form I
B、direct-form II
C、cascade form
D、parallel form

2、Among the realization structures of IIR filters, ( ) structure is convenient to control the zeros and poles of the system.
A、direct-form I
B、direct-form II
C、cascade form
D、parallel form

3、For the same IIR filter, direct-form I realization requires fewer multipliers than direct-form II realization.

学习通Digital Signal Processing_1

Digital Signal Processing(数字信号处理,简称DSP)是一种数字处理技术,可以处理数字信号,并将其转换成有用的信息。DSP技术主要用于音频、视频、图像、通信等领域。

本课程为Digital Signal Processing(数字信号处理)的入门课程,主要介绍数字信号处理的基本概念和算法。课程内容包括:

  • 数字信号的基本概念
  • 数字信号的表示
  • 离散时间信号的基本运算
  • 时域分析与频域分析
  • 数字滤波器的设计与实现
  • 数字信号处理的应用

通过学习本课程,你将掌握数字信号处理的基本概念和算法。具体来说,你将学会:

  • 理解数字信号的基本概念
  • 掌握数字信号的表示方法
  • 掌握离散时间信号的基本运算
  • 掌握时域分析与频域分析的方法
  • 了解数字滤波器的设计与实现方法
  • 了解数字信号处理的应用领域

本课程为入门课程,不需要任何先修知识。但是,为了更好地学习本课程,建议学习者掌握以下基础知识:

  • 高中数学
  • 基本的计算机应用技能

首先,我们需要了解什么是数字信号。数字信号是一种用数字来表示的信号,它是由一连串数据点组成的。数字信号可以是离散时间信号或者离散频率信号,也可以是经过量化和编码的模拟信号。

在数字信号处理中,我们经常需要使用到的一些概念有:

  • 采样:将连续时间信号转化为离散时间信号的过程,采样频率是采样率的倒数,表示每秒采样的次数。
  • 量化:将连续信号的幅值转化为离散值的过程,量化精度是幅值分辨率的倒数,表示幅值可以分为多少个等级。
  • 编码:将量化后的离散值转化为二进制编码的过程,编码方式有很多种,例如PCM编码。

数字信号可以用多种方式表示。其中,最常用的方式是序列表示法和函数表示法。

  • 序列表示法:将数字信号表示为一个数列,通常使用花括号{ }表示。
  • 函数表示法:将数字信号表示为一个函数,通常使用小括号()表示。

离散时间信号的基本运算包括加法、乘法、卷积等。在DSP中,离散时间信号通常用序列表示法表示。

  • 加法:对于两个离散时间信号f(n)和g(n),它们的和为h(n)=f(n)+g(n)。
  • 乘法:对于两个离散时间信号f(n)和g(n),它们的乘积为h(n)=f(n)*g(n)。
  • 卷积:对于两个离散时间信号f(n)和g(n),它们的卷积为h(n)=f(n)*g(n)=∑f(k)g(n-k),k从0到无穷大。

时域分析和频域分析是数字信号处理中的两个重要概念。

  • 时域分析:研究信号在时间轴上的变化规律。时域分析的重要工具是差分方程和单位样本响应等。
  • 频域分析:研究信号在频率轴上的变化规律。频域分析的重要工具是傅里叶变换和滤波器等。

数字滤波器是数字信号处理中的重要组成部分,主要用于信号去噪、信号增强等。

数字滤波器的设计和实现包括:

  • IIR滤波器:基于差分方程实现的滤波器。
  • FIR滤波器:基于卷积实现的滤波器。

数字信号处理有广泛的应用领域,例如:

  • 音频处理:包括音乐、语音等的处理。
  • 图像处理:包括图像增强、图像压缩等的处理。
  • 视频处理:包括视频编解码、视频传输等的处理。
  • 通信系统:包括数字调制解调、信道编码解码等的处理。

通过本课程的学习,你应该已经掌握了数字信号处理的基本概念和算法,以及数字信号处理的应用领域。希望本课程可以对你学习数字信号处理和相关领域有所帮助。

学习通Digital Signal Processing_1

Digital Signal Processing(数字信号处理,简称DSP)是一种数字处理技术,可以处理数字信号,并将其转换成有用的信息。DSP技术主要用于音频、视频、图像、通信等领域。

本课程为Digital Signal Processing(数字信号处理)的入门课程,主要介绍数字信号处理的基本概念和算法。课程内容包括:

  • 数字信号的基本概念
  • 数字信号的表示
  • 离散时间信号的基本运算
  • 时域分析与频域分析
  • 数字滤波器的设计与实现
  • 数字信号处理的应用

通过学习本课程,你将掌握数字信号处理的基本概念和算法。具体来说,你将学会:

  • 理解数字信号的基本概念
  • 掌握数字信号的表示方法
  • 掌握离散时间信号的基本运算
  • 掌握时域分析与频域分析的方法
  • 了解数字滤波器的设计与实现方法
  • 了解数字信号处理的应用领域

本课程为入门课程,不需要任何先修知识。但是,为了更好地学习本课程,建议学习者掌握以下基础知识:

  • 高中数学
  • 基本的计算机应用技能

首先,我们需要了解什么是数字信号。数字信号是一种用数字来表示的信号,它是由一连串数据点组成的。数字信号可以是离散时间信号或者离散频率信号,也可以是经过量化和编码的模拟信号。

在数字信号处理中,我们经常需要使用到的一些概念有:

  • 采样:将连续时间信号转化为离散时间信号的过程,采样频率是采样率的倒数,表示每秒采样的次数。
  • 量化:将连续信号的幅值转化为离散值的过程,量化精度是幅值分辨率的倒数,表示幅值可以分为多少个等级。
  • 编码:将量化后的离散值转化为二进制编码的过程,编码方式有很多种,例如PCM编码。

数字信号可以用多种方式表示。其中,最常用的方式是序列表示法和函数表示法。

  • 序列表示法:将数字信号表示为一个数列,通常使用花括号{ }表示。
  • 函数表示法:将数字信号表示为一个函数,通常使用小括号()表示。

离散时间信号的基本运算包括加法、乘法、卷积等。在DSP中,离散时间信号通常用序列表示法表示。

  • 加法:对于两个离散时间信号f(n)和g(n),它们的和为h(n)=f(n)+g(n)。
  • 乘法:对于两个离散时间信号f(n)和g(n),它们的乘积为h(n)=f(n)*g(n)。
  • 卷积:对于两个离散时间信号f(n)和g(n),它们的卷积为h(n)=f(n)*g(n)=∑f(k)g(n-k),k从0到无穷大。

时域分析和频域分析是数字信号处理中的两个重要概念。

  • 时域分析:研究信号在时间轴上的变化规律。时域分析的重要工具是差分方程和单位样本响应等。
  • 频域分析:研究信号在频率轴上的变化规律。频域分析的重要工具是傅里叶变换和滤波器等。

数字滤波器是数字信号处理中的重要组成部分,主要用于信号去噪、信号增强等。

数字滤波器的设计和实现包括:

  • IIR滤波器:基于差分方程实现的滤波器。
  • FIR滤波器:基于卷积实现的滤波器。

数字信号处理有广泛的应用领域,例如:

  • 音频处理:包括音乐、语音等的处理。
  • 图像处理:包括图像增强、图像压缩等的处理。
  • 视频处理:包括视频编解码、视频传输等的处理。
  • 通信系统:包括数字调制解调、信道编码解码等的处理。

通过本课程的学习,你应该已经掌握了数字信号处理的基本概念和算法,以及数字信号处理的应用领域。希望本课程可以对你学习数字信号处理和相关领域有所帮助。



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