Home » Kurikulum » Silabus dan Satuan Acara Pengajaran (SAP) » Semester 5 » ELS3103 Pengolahan Sinyal Digital

# ELS3103 Pengolahan Sinyal Digital

 Kode Matakuliah: ELS3103 Bobot sks: 3 Semester: 5 KK / Unit Penanggung Jawab: Prodi S1 Teknik Elektro Sifat: Wajib Nama Matakuliah Pengolahan Sinyal Digital Digital Signal Processing Silabus Ringkas Sejarah dan Tinjauan Pengolahan Sinyal Digital, Teori dan Konsep, Sinyal dan Sistem Waktu Diskrit, Analisis Sistem LTI dengan transformasi-z, Analisis frekuensi dari sinyal dan sistem, Discrete Fourier Transform (DFT) dan Fast Fourier Transform (FFT), Analisis Spektrum, Implementasi Sistem Waktu Diskrit, Perancangan Filter Digital History and Overview in Digital Signal Processing, Theories and Concepts, Discrete Time Signals and Systems, Analysis of LTI Systems Using z-Transfoms, Frequency Analysis of Signals and Systems, The Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT), Spectrum analysis, Implementation of Discrete-Time Systems, Design of Digital Filter Silabus Lengkap Sejarah dan tinjauan pengolahan sinyal digital; Teori dan konsep sinyal dan sistem, Konsep frekuensi di dalam sinyal waktu kontinyu dan sinyal waktu diskrit, dan Analog-to-Digital and Digital-to-Analog Conversion; Sinyal dan sistem waktu diskrit, Analisis sistem LTI waktu diskrit, dan Sistem LTI dikarakterisasi persamaan differens dengan koefisien konstan; Konsep transformasi-z dan inversinya, analisis sistem LTI menggunakan transformasi-z; Analisis frekuensi dari sinyal dan sistem, Sistem LTI sebagai frekuensi pemilih frekuensi; Discrete Fourier Transform (DFT) dan Fast Fourier Transform (FFT);  Analisis spektrum dengan DFT dan konsep fungsi window; Implementasi sistem waktu diskrit untuk sistem FIR dan IIR; Perancangan filter digital, perancangan FIR, perancangan IIR dari filter analog yang ditransformasi menggunakan transformasi bilinear. History and overview in digital signal processing field; Theories and concepts of signal and system, the concept of frequency in continuous-time and discrete-time signals, and Analog-to-Digital and Digital-to-Analog Conversion; Discrete-time signals and systems, analysis of discrete-time LTI systems, and LTI system characterized by constant-coefficient difference equation (LCCDE); The concept of z-transform and its inversion, analysis of LTI systems using z-transfoms; Frequency analysis of signals and systems, LTI systems as frequency selective filters; The Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT);  Spectrum Analysis using DFT and concept of window function; Implementation of Discrete-Time Systems for FIR and IIR systems; Design of digital filter, FIR designs, IIR designs from analog filters transformed using bilinear transformation. Luaran (Outcomes) 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) Matakuliah Terkait ELS2204 Sinyal dan Sistem Prasyarat ELS3104 Prakt. Pengolahan Sinyal Digital Bersamaan Kegiatan Penunjang Tugas Proyek Pustaka [PrMa07]  J.G. Proakis and D. G. Manolakis, Digital Signal Processing, Principles, Algorithms, and Applications.  Upper Saddle River, NJ: Prentice Hall, 2007. ISBN 0–13–2287315.  (pustaka utama) [InPr97] V. K. Ingle and  J. G. Proakis, Digital Signal Processing Using Matlab v.4.  Boston, MA: PWS Publishing Company, 1997. (pustaka pendukung untuk Tugas Proyek) Panduan Penilaian Pretest (5%), Posttest (30), Tugas Proyek (30%), UAS (35%) Catatan Tambahan Website penunjang perkuliahan ada di http://kuliah.itb.ac.id/course/view.php?id=287

 Mg# Topik Sub Topik Capaian Belajar Mahasiswa Sumber Materi 1 History and Overview 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 2 Theories and Concepts 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 3 Discrete Time Signals and Systems 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 4 Discrete Time Signals and Systems Discrete-Time Systems Described by Difference Equations Implementation of Discrete-Time Apply the techniques for the analysis of Linear Systems [PrMa07] 4-2.5 5 Analysis of LTI Systems Using z-Transfoms 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 6 Analysis of LTI Systems Using z-Transfoms 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 7 Frequency Analysis of Signals and Systems 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 8 Frequency Analysis of Signals and Systems 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 9 Frequency Analysis of Signals and Systems LTI Systems as Frequency Selective Filters Apply the filter (LTI system) to perform spectral shaping or frequency-selective filtering [PrMa07] 3 10 The Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) 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 11 The Discrete Fourier Transform (DFT) and Fast Fourier Transform (FFT) 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 12 Spectrum Analysis 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 13 Implementation Discrete-Time Systems 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 14 Design of Digital Filter 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 15 Design of Digital Filter 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