01 - Introduction. Pemrosesan Sinyal Digital 1 (MII3605) Dr. Agfianto Eko Putra

Transkripsi

1 01 - Introduction Pemrosesan Sinyal Digital 1 (MII3605) Dr. Agfianto Eko Putra agfi@ugm.ac.id

2 Tujuan Pembelajaran 1. Memahami konsep-konsep dasar Pemrosesan Sinyal Digital dan beberapa aplikasinya. 2. Memahami konsep-konsep sinyal dan sistem waktu-diskrit dalam ranah waktu. 3. Memahami konsep pencuplikan dan rekonstruksi sinyal analog, serta penyajian sinyal dan sistem waktu diskrit dalam ranah frekuensi (Analisis Fourier Waktu-diskrit). 4. Memahami dan menerapkan Transformasi-Z untuk memecahkan permasalahan pada persamaan beda (difference equation). 5. Memahami konsep Transformasi Fourier dan menerapkannya (termasuk memahami konsep Transformasi Fourier Cepat). 6. Memahami dan mampu menjelaskan tentang struktur tapis digital, tipe-tipe tapis dasar serta merealisasikan tapis digital. 7. Memahami konsep dan mampu merancang dan menerapkan tapis jenis FIR (Finite Impulse Response). 8. Memahami konsep dan mampu merancang dan menerapkan tapis jenis IIR (Infinite Impulse Response).

3 Materi Pembelajaran (mg.1 dan 2) 1. Pendahuluan (1x3) Konsep dasar Pemrosesan Sinyal Digital (PSD) Pendahuluan MATLAB singkat Aplikasi Pemrosesan Sinyal Digital (PSD) 2. Sinyal dan Sistem Waktu-diskrit (1x3) Sinyal-sinyal Waktu-diskrit Sistem Diskrit Konvolusi Persamaan Beda

4 Materi Pembelajaran (mg.3 dan 4) 3. Analisis Fourier Waktu-diskrit (1x3) Transformasi Fourier Waktu-diskrit (DTFT) Sifat-sifat DTFT Penyajian Sistem LTI pada Ranah Frekuensi Pencuplikan dan Rekonstruksi Sinyal2 Analog 4. Transformasi Z (1x3) Transformasi Z Bilateral Sifat-sifat penting Transformasi Z Inversi Transformasi Z Penyajian Sistem dalam Ranah Z Solusi Persamaan Beda

5 Materi Pembelajaran (mg.5 dan 6) 5. Transformasi Fourier Diskrit (2x3) Deret Fourier Diskrit Pencuplikan dan Rekonstruksi dalam Ranah Z Transformasi Fourier Diskrit (DFT) Konvolusi Linear menggunakan DFT The Fast Fourier Transform (FFT)

6 Materi Pembelajaran (mg.7,8,9,10) 6. Implementasi Tapis Waktu-diskrit (2x3) Elemen-elemen Dasar Struktur Tapis IIR Struktur Tapis FIR Struktur Tapis Lattice Gambaran Efek Numerik Presisi-yang-terbatas Penyajian bilangan Proses Karakterisasi Kuantisasi dan Ralat Kuantisasi Koefisien-koefisien Tapis 7. Perancangan Tapis Finite Impulse Response (FIR) (2x3) Persiapan Sifat-sifat Tapis FIR Fase-linear Teknik Perancangan Jendela Teknik Perancangan Pencuplikan Frekuensi Teknik Perancangan Equiripple Optimal

7 Materi Pembelajaran (mg.11 dan 12) 8. Perancangan Tapis Infinite Impulse Response (IIR) (2x3) Beberapa Persiapan Beberapa Tipe Tapis Khusus Karakteristik Tapis Analog Purwarupa Transformasi Tapis Analog-to-Digital Perancangan Tapis Lowpass menggunakan MATLAB Transformasi Frequency-band Total 14 minggu (12 pertemuan, UTS dan UAS)

8 Perhatikan! Asumsi bahwa para mahasiswa sudah terbiasa menggunakan MATLAB; Inti kuliah adalah memberikan dasar-dasar alat analisis yang diperlukan dalam dunia pemrosesan sinyal nyata (alias sinyal2 analog) menggunakan teknik digital; Banyak berurusan dengan sinyal2 dan sistem2 waktudiskrit yang dianalisa baik dalam ranah waktu maupun frekuensi; The analysis and design of processing structures called filters and spectrum analyzers are among of the most important aspects of DSP and are treated in great detail in this lecture.

9 1 - Overview

10 Some important advantages of DSP are these 1. Systems using the DSP approach can be developed using software running on a general-purpose computer. Therefore DSP is relatively convenient to develop and test, and the software is portable. 2. DSP operations are based solely on additions and multiplications, leading to extremely stable processing capability for example, stability independent of temperature. 3. DSP operations can easily be modified in real time, often by simple programming changes, or by reloading of registers. 4. DSP has lower cost due to VLSI technology, which reduces costs of memories, gates, microprocessors, and so forth. The principal disadvantage of DSP is the limited speed of operations limited by the DSP hardware, especially at very high frequencies.

11 Kunjungi website... /dsp-the-most-powerful-technologies/ /latar-belakang-dan-cakupan-aplikasi-psd-dsp/ /kelebihan-pemrosesan-sinyal-digital/

12 Categories of DSP

13 Signal Analysis Signal analysis This task deals with the measurement of signal properties. It is generally a frequency-domain operation. Some of its applications are spectrum (frequency and/or phase) analysis speech recognition speaker verification target detection

14 Signal Filtering Signal filtering This task is characterized by the signal-in signal-out situation. The systems that perform this task are generally called filters. It is usually (but not always) a time-domain operation. Some of the applications are removal of unwanted background noise removal of interference separation of frequency bands shaping of the signal spectrum

15 2 - Using MATLAB (Example 1.1)

16 1st approach

17 2nd approach

18 Last approach (1/3)

19 Last approach (2/3)

20 Last approach (3/3)

21 Others... Script and Functions (p.13) Plotting (p.14) /tips-dsp-bagaimana-membuat-menggambarsinusoidal-di-matlab/

22 3 Applications of DSP speech/audio (speech recognition/synthesis, digital audio, equalization, etc.), image/video (enhancement, coding for storage and transmission, robotic vision, animation, etc.), military/space (radar processing, secure communication, missile guidance, sonar processing, etc.), biomedical/health care (scanners, ECG analysis, X-ray analysis, EEG brain mappers, etc.) consumer electronics (cellular/mobile phones, digital television, digital camera, Internet voice/music/video, interactive entertainment systems, etc) and many more.

23 Musical Sound Processing In the music industry, almost all musical products (songs, albums, etc.) are produced in basically two stages. First, recording single or multi-track; Then, storing processing (adding special effects etc) audio file or CD For example: Echo generation Echo removal Digital Reverberation

24 To be continued!