Kode Matakuliah:

ELS3103

Bobot sks:

3

Semester:

5

KK / Unit Penanggung Jawab:

Prodi S1 Teknik Elektro

Sifat:

Wajib

Identify the difference between analog and discrete signals, Indicate some of the characteristic of filters; Describe the concept of frequency, amplitude, and phase of discrete time signals and continuous time signals and its properties, Explain the concept of Harmonically Related Complex Exponentials and fundamental frequency, Explain the process of analog-to-digital conversion (sampling, quantization, coding); Describe the discrete-time representation of signals, Distinguish between energy signals and power signals, periodic and aperiodic signals, symetric and antisymetric signals, Describe the input-output description of the  systems and the their block diagram representation, Distinguish between time-invariant and time-variant systems, linear and nonlinear systems, causal and noncausal systems, stable and unstable systems, Apply the techniques for the analysis of Linear Systems; Describe the definition of z-transform and Region of Convergence (RoC), Explain the important properties of z-transform such as linearity, time shifting, scaling, and time reversal, Explain z-transform to characterize signals in terms of their pole-zero patterns, Explain the definition of inversion of the z-transform, Explain the methods for inverting the z-transform of a signal so as to obtain the time-domain representation of the signal, Apply the z-transform in the analysis of LTI systems; Explain the Fourier series representation for continuous-time periodic (power) signals and the Fourier transform for finite energy aperiodic signals, Explain the Fourier series representation for discrete-time periodic (power) signals and the Fourier transform for finite energy aperiodic signals, Explain the properties of the Fourier Transform (linearity, time shifting, and time-reversal), Explain the characterization of LTI systems in the frequency domain that is described by its frequency response, Produce the frequency response of LTI systems that have rational system functions, Apply the filter (LTI system) to perform spectral shaping or frequency-selective filtering; Explain the DFT and its properties (periodicity, linearity and circular symmetry), Apply the DFT to perform linear filtering in the frequency domain, Apply the DFT for frequency analysis of signals, Explain the FFT as a method for computing the DFT efficiently; Apply the DFT for spectrum analysis, Apply the linear filtering to compute DFT, Explain how window functions improve transform properties; Explain the issues in realization of Discrete-Time Systems, Explain the structures for FIR Systems (Direct Form, Cascade Form, Frequency Sampling Structure, Lattice Structure), Explain the structures for IIR Systems (Direct Form, Signal Flow Graphs and Transposed, Cascade Form, Parallel Form, Lattice and Lattice-Ladder Structures); Design Linear-Phase FIR Filters using windows (Rectangular, Berlett, Hanning, Hamming, Blackman), Design Linear-Phase FIR Filters by Frequency-Sampling Method, Design Optimum Equiripple Linear-Phase FIR Filters, Explain the concept of designing IIR filters from analog filters by the Bilinear Transformation, Design analog low pass filters (Butterworth, Chebyshev, Elliptic, and Bessel), Design IIR Filters from Analog Filters by the Bilinear Transformation (Low Pass, High Pass, Bandpass, Bandstop)

• Reasons for studying DSP
• Highlight some people that contributed in the area of DSP
• The need for using transform
• Some technique of transformations
• Identify the difference between analog and discrete signals
• Indicate some of the characteristic of filters, in particular low- and high-pass filters
• Describe how computer engineering uses or benefits from digital signal processing and multimedia

• Signals, systems, and signal processing
• Classification of Signals
• The concept of frequency in Continuous-Time and Discrete-Time Signals
• Analog-to-Digital and Digital-to-Analog Conversion

• Express the definition and mathematical representation of signals and systems
• Describe the basic elements of DSP systems
• Distinguish between real and complex signals, multichannel and single channel, multidimensional and single dimensional, continuous time and discrete time, continuous valued and discrete valued, digital signal and analog signal, deterministic and random
• Describe the concept of frequency, amplitude, and phase of discrete time signals and continuous time signals and its properties
• Explain the concept of Harmonically Related Complex Exponentials and fundamental frequency
• Explain the process of analog-to-digital conversion (sampling, quantization, coding)
• Explain the concept of aliasing
• Describe the process of digital-to-analog conversion
• [PrMa07] 1-1.5

• Discrete-Time Signals
• Discrete-Time Systems
• Analysis of Discrete-Time Linear Time-Invariant Systems
• Describe the discrete-time representation of signals
• Explain the elementary signals (sample, step, ramp, exponential, complex exponential, sinusoidal)
• Distinguish between energy signals and power signals, periodic and aperiodic signals, symetric and antisymetric signals
• Explain the basic operation on signals (shifting, folding, addition, product, scaling)
• Describe the input-output description of the systems and the their block diagram representation
• Distinguish between static and dynamic systems, time-invariant and time-variant systems, linear and nonlinear systems, causal and noncausal systems, stable and unstable systems
• [PrMa07] 1-2.3

• Discrete-Time Systems Described by Difference Equations
• Implementation of Discrete-Time

• Apply the techniques for the analysis of Linear Systems
• [PrMa07] 4-2.5

• The z-Transform
• Properties of the z-Transform
• Rational z-Transforms
• Inversion of the z-Transform
• Analysis of LTI in the z-Domain

• Describe the definition of z-transform and Region of Convergence (RoC)
• Explain the important properties of z-transform such as linearity, time shifting, scaling, and time reversal
• Explain z-transform to characterize signals in terms of their pole-zero patterns
• Explain the definition of inversion of the z-transform
• Explain the methods for inverting the z-transform of a signal so as to obtain the time-domain representation of the signal
• [PrMa07] 1-3.4

• One-Sided z-Transform
• Analysis of LTI in the z-Domain

• Explain the definition of one-sided z-transform
• Explain the properties of one-sided z-transform
• Apply the z-transform in the analysis of LTI systems
• [PrMa07] 5

• Frequency Analysis of Continuous-Time Signals
• Frequency Analysis of Discrete-Time Signals
• Explain the Fourier series representation for continuous-time periodic (power) signals and the Fourier transform for finite energy aperiodic signals
• Explain the Fourier series representation for discrete-time periodic (power) signals and the Fourier transform for finite energy aperiodic signals
• [PrMa07] 1-4.3

• Properties of the Fourier Transform for Discrete-Time Signals
• Frequency-Domain Characteristics of LTI Systems
• Explain the properties of the Fourier Transform (linearity, time shifting, and time-reversal)
• Explain the characterization of LTI systems in the frequency domain that is described by its frequency response
• Produce the frequency response of LTI systems that have rational system functions
• [PrMa07] 4, 5.1-5.2

• LTI Systems as Frequency Selective Filters
• Apply the filter (LTI system) to perform spectral shaping or frequency-selective filtering
• [PrMa07] 3

• The Discrete Fourier Transform (DFT) and Its Properties
• Linear Filtering Methods Based on the DFT
• Explain the DFT and its properties (periodicity, linearity and circular symmetry)
• Apply the DFT to perform linear filtering in the frequency domain
• [PrMa07] 1-7.3

• Frequency Analysis of Signals Using the DFT
• The Fast Fourier Transform (FFT)
• Apply the DFT for frequency analysis of signals
• Explain the FFT as a method for computing the DFT efficiently
• Explain the divide-and-conquer approach to derive fast algortihm for computing DFT (Radix-2 and Radix-4 FFT algorithms)
• [PrMa07] 4, 8.1-8.2

• Spectrum Analysis using DFT
• Definition and purpose of a window function
• Apply the DFT for spectrum analysis
• Explain the concept of zero padding
• Apply the linear filtering to compute DFT and implement this on Goertzel Algorithm
• Explain the definition of a window function
• Explain why window functions are important to digital signal processing
• Explain how window functions improve transform properties
• [PrMa07] 3-8.4

• Structures for the Realization of Discrete-Time Systems
• Structures for FIR Systems
• Structures for IIR Systems
• Explain the issues in realization of Discrete-Time Systems
• Explain the structures for FIR Systems (Direct Form, Cascade Form, Frequency Sampling Structure, Lattice Structure)
• Explain the structures for IIR Systems (Direct Form, Signal Flow Graphs and Transposed, Cascade Form, Parallel Form, Lattice and Lattice-Ladder Structures)
• [PrMa07] 1-9.3

• FIR Filters
• The concept of symmetric and antisymmetric FIR filters
• Design Linear-Phase FIR Filters using windows (Rectangular, Berlett, Hanning, Hamming, Blackman)
• Design Linear-Phase FIR Filters by Frequency-Sampling Method
• Design Optimum Equiripple Linear-Phase FIR Filters
• [PrMa07] 1-10.2

• IIR Filters
• Explain the concept of designing IIR filters from analog filters by the Bilinear Transformation
• Design analog low pass filters (Butterworth, Chebyshev, Elliptic, and Bessel)
• Design IIR Filters from Analog Filters by the Bilinear Transformation (Low Pass, High Pass, Bandpass, Bandstop)
• Design IIR Filters by the Matched-z Transformation
• [PrMa07] 3-10.4