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§5.1 Digital Processing of Continuous-Time Signals §5.2 Sampling of Continuous-time Signals §5.3 Effect of Sampling in the Frequency Domain §5.4 Recovery of the Analog Signal §5.6 Sampling of Bandpass Signals §5.7 Analog Lowpass Filter Specifications §5.8 Analog Lowpass Filter Design
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第6章无限脉冲响应数字滤波器的设计 6.1数字滤波器的基本概念 6.2模拟滤波器的设计 6.3用脉冲响应不变法设计IR数字低通滤波器 6.4用双线性变换法设计IR数字低通滤波器 6.5数字高通、带通和带阻滤波器的设计 6.6IR数字滤波器的直接设计法
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§3.1 Discrete-Time Fourier Transform §3.2 DTFT Properties §3.3 Discrete Fourier Transform (DFT) §3.5 Circular Shift of a Sequence §3.6 Circular Convolution §3.7 z-transform §3.8 z-Transform Properties §3.9 Discrete Fourier Transform Computation
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课程性质与任务 MATLAB语言及其应用是本专业的一门基础工具课。 MATLAB是 MathWorks公司开 发的一套高性能的数值计算和可视化的仿真软件,包括 MATLAB主程序、 SIMUL INK 动态系统仿真包和各种专业工具箱。它基于矩阵运算,集数值计算、图形显示、图 形界面设计等功能和模糊逻辑等30多个专业工具箱于一体,具有极强大的计算功能 和极高的编程效率,特别适合于科学计算、数值分析、系统仿真和信号处理等任 务,对后续专业课程的学习有重要影响
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3.1 Discrete-Time Fourier Transform Definition- The discrete-time Fourier transform (DTFT) X(eio) of a sequence x[n] is given by jae In general,() is a complex function of the real variable and can be written as X(eio) Xre(eio) +j Xim(eio)
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3.1离散傅立叶变换的定义 DFT的定义 设x(n)是一个长度为M的有限长序列,则定义的N点离散傅立 叶变换为
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一、DF按频率特性分类 可分为低通、高通、带通、带阻和全通, 其特点为: (1)频率变量以数字频率O表示,=QT, Ω为模拟角频率,T为抽样时间间隔; (2)以数字抽样频率0=2·T=2元为周期; (3)频率特性只限于≤/2=π范围,这是因为依取样定理,实际频率特性只能为抽样频率的一半
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5.1 Digital Processing of Continuous-Time Signals Digital processing of a continuous-time signal involves the following basic steps: (1) Conversion of the continuous-time signal into discrete-time signal, ()Processing of the discrete-time signal, (3) Conversion of the processed discrete- time signal back into a continuous-time signal
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2.0 Introduction 2.1 Discrete-Time Signals: Sequences 2.2 Discrete-Time Systems 2.3 Linear Time-Invariant (LTI) Systems 2.4 Properties of LTI Systems 2.5 Linear Constant-Coefficient Difference Equations 2.6 Frequency-Domain Representation of Discrete-Time Signals and systems 2.7 Representation of Sequences by Fourier Transforms 2.8 Symmetry Properties of the Fourier Transform 2.9 Fourier Transform Theorems 2.10 Discrete-Time Random Signals 2.11 Summary
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◆8.0 Introduction ◆8.1 Representation of Periodic Sequence: the Discrete Fourier Series ◆8.2 Properties of the Discrete Fourier Series ◆8.3 The Fourier Transform of Periodic Signal ◆8.4 Sampling the Fourier Transform ◆8.5 Fourier Representation of Finite-Duration Sequence: the Discrete Fourier Transform ◆8.6 Properties of the Discrete Fourier Transform ◆8.7 Linear Convolution using the Discrete Fourier Transform ◆8.8 the discrete cosine transform (DCT)
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