信号与系统 Signals and Systems
卞海溢
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1 Signals and Systems
1.1 Continuous-Time and Discrete-Time Signals
1.1.1 Signal energy and power
1.2 Transformation of the Independent Variable
1.2.1 Scale transformation operation of the signal
1.2.2 Periodic signals
1.3 Exponential and sinusoidal signal
1.3.1 continuous-time complex exponential and sinusoidal signal
1.3.2 Discrete-time complex exponential and sinusoidal signal
1.3.3 Periodicity properties of discrete-timecomplex exponentials
1.4 The Unit Impulse and Unit Step Function
1.5 Continuous-Time and Discrete-Time Systems
1.6 Basic System Properties
2 Linear Time-Invariant(LTI) Systems
2.1 Discrete-Time LTI Systems: The Convolution Sum
2.1.1 Mathod3,4
2.2 Countinuous-Time LTI Systems: The Convolution Integral
2.2.1 The Representation of Continuous-time signal in Terms of Impulses
2.2.2 The Continuous-time Unit Impulse Response and the ConvolutionIntegral Representation of LTI Systems
2.3 Properties of Linear Time-Invariant Systems
2.3.1 Part one
2.3.2 Part two
2.4 Causal LTI Systems Described by Differential and Difference Equations
2.4.1 Part-1
2.4.2 Part-2
2.5 Singularity Functions
2.6 Exercise lesson(CH1~CH2)
2.6.1 Exercise-1
2.6.2 Exercise-2
2.6.3 Exercise-3
2.6.4 Exercise-4
2.6.5 Exercise-5
3 Fourier Series Representation of Periodic Signals
3.1 Introduction+A Historical Perspective
3.1.1 Part-1
3.1.2 Part-2
3.2 The Response of LTI System to Complex Exponentials
3.3 Fourier Series Representation of Continuous-Time Periodic Signals
3.4 Convergence of the Fourier series
3.5 Properties of continuous-time Fourier series
3.6 Fourier series representation of discrete-time periodic signals
3.7 Properties of discrete-time Fourier series
3.8 Fourier series and LTI systems
3.9 Filtering
3.10 Examples of continuous-time filters described by differential equations
3.11 Examples of discrete-time filters described by difference equations
4 The Continuous-Time Fourier Transform
4.1 Representation of Aperiodic Signals: The Continuous-Time Fourier Transform
4.2 The Fourier Transform for Periodic Signals
4.3 Properties of the Continuous-Time Fourier Transform
4.3.1 Part-1
4.3.2 Part-2
4.4 The Convolution Property
4.5 The Multiplication Property
4.6 Tables of Fourier Properties and of Basic Fourier Transform Paris
4.7 Systems Characterized by Linear Constant-Coefficient Differential Equations
5 The Discrete-time Foyrier transform
5.1 Representation of Aperiodic Signals: The Discrete-Time Fourier Transform
5.2 The Fourier Transform for Periodic Signals
5.3 Properties of the Discrete-Time Fourier Transform
5.3.1 Part-1
5.3.2 Part-2
5.4 The Convolution Property
5.5 The Multiplication Property
5.6 Tables of Fourier Properties and of Basic Fourier Transform Paris
5.7 Duality
5.8 Systems Characterized by Linear Constant-Coefficient Differencel Equations
6 Sampling
6.1 Representation of a Continous-time signal by its samples: The sampling theorem
6.1.1 Part-1
6.1.2 Part-2
6.2 Reconstruction of a signal fro its samples using interpolation
6.3 The effect of undersampling: aliasing
6.4 Discrete-time processing of continuous-time signals
6.5 Sampling of discrete-time signals
7 The Laplace transform
7.1 The Laplace transform
7.1.1 Part-1
7.1.2 Part-2
7.2 The region of convergence for Laplace transform
7.2.1 Part-1
7.2.2 Part-2
7.3 The inverse Laplace transform
7.4 Gometric evaluation of the Fourier transform from the pole-zero plot
7.5 Properties of the Laplace transform
7.6 Some Laplace transform pairs
7.7 Analysis and characterization of LTI system using the Laplace transform
7.8 System function algebra and black diagram representation
7.9 The unilateral Laplace tranform
7.10 Excise
8 The Z-Transform
8.1 The Z-Transform
8.2 The Region of Convergence for the Z-Transform
8.3 The Inverse Z-Transform
8.4 Geometric Evaluation of the Fourier Transform from the Pole-Zero Plot
8.5 Properties of the Z-Transform
8.6 Some Common Z-Transform Pairs
8.7 Analysis and Characterization of LTI Systems Using the Z-Transform
8.8 System Function Algebra and Block Diagram Representations
8.9 The Unilateral Z-Transform
Representation of a Continous-time signal by its samples: The sampling theorem
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