《数字信号处理》课程是高等工科院校通信与电子信息类专业的一门重要学科基础学位课程。该课程主要讲授离散时间信号和数字信号及系统分析的基本理论、原理和基本分析、实现方法。通过本课程的学习,使学生掌握离散时间信号与系统的时域分析、频域分析和Z变换、离散傅里叶变换及其快速算法、数字滤波器的基本网络结构、IIR和FIR数字滤波器的设计理论和设计方法、数字信号处理的基本实现方法等;为学生后续专业课程如信号采集和信号检测、数字图像处理、通信原理、数字语音处理、统计信号处理和DSP原理及应用等课程的学习和进一步研究现代数字信号处理理论与实现技术实现打下良好的基础,提高学生分析和解决实际问题的能力。
Text: Oppenheim, Schafer and Buck, Discrete-Time Signal Processing, 3rd ed., Prentice Hall, 2010
教材:《离散时间信号处理》第三版,奥本海姆,电子工业出版社,2015
Recommended: Ingle and Proakis, Digital Signal Processing using Matlab, 2nd ed., Thomson-Engineering, 2006
Discrete-time signals and systems (chapter 2)(第2章:离散时间信号与系统)
Discrete-time signals as sequences(离散时间序列)
Properties of discrete-time systems(离散时间系统的性质)
Linear time-invariant systems(线性时不变系统)
Difference equations(差分方程)
Frequency domain and Fourier transforms(频域与傅里叶变换)
z-Transforms (chapter 3)(第3章:z变换)
Definition of the z-transform(z变换的定义)
Convergence(收敛性)
Inverse z-transform(z逆变换)
Properties(z变换的性质)
Sampling continuous-time signals (chapter 4)(第4章:连续时间信号的采样)
Frequency domain representation of sampling(采样的频域描述)
Reconstruction(重构)
Multirate signal processing(多速率信号处理)
A/D and D/A conversion(A/D与D/A转换)
Transform analysis of LTI systems (chapter 5)(第5章:LTI系统的变换分析)
Frequency response(频率响应)
System functions(系统函数)
Analysis of magnitude and phase(幅度和相位分析)
Structure for d-t systems (chapter 6)(第6章:离散时间系统的结构)
Structures for FIR and IIR filters(FIR和IIR滤波器的结构)
Quantization and noise(量化与噪声)
Filter design (chapter 7)(第7章:滤波器设计方法)
IIR systems(IIR系统)
FIR-windowing methods(FIR窗函数设计法)
FIR-optimal approximation methods(FIR最优逼近法)
Discrete Fourier Transforms (chapter 8 & 9)(第8、9章:离散傅里叶变换)
DFT(离散傅里叶变换)
Discrete cosine transform(离散余弦变换)
Fast Fourier transform(快速傅里叶变换)
This course is aimed at students who want a deeper presentation of digital signal processing than offered in an introductory undergraduate course on DSP. The course emphasizes the mathematical development of the fundamental principles of DSP, i.e., theory. As a result, less emphasis will be given to computer demonstrations and programming than in an introductory course.
Students are expected to have a good background in continuous-time signals and systems, including linear time-invariant signals and systems, the Fourier transform, and the Laplace transform. It may be helpful if students have already had an introductory course that includes some of the principles of DSP such as sampled systems, the z-transform and FIR filters. However, these are not a requirement, but the class will move somewhat quickly through the chapter on discrete-time signals and systems (chapter 2 of Oppenheim and Schafer).
After completing the course, students should have a solid background in the principles of digital signal processing and be prepared for more specialized and advanced topics in DSP and communication theory.