신호처리
- 건국대학교
- 임창훈
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- 주제분류
- 공학 >컴퓨터ㆍ통신 >소프트웨어공학
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- 강의학기
- 2018년 1학기
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- 조회수
- 15,717
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- 평점
- 5/5.0 (2)
- 강의계획서
- 강의계획서
본 교과목은 디지털 신호처리의 기본 개념인 주파수 표현, sampling, FIR 필터, 주파수 응답, Fourier 변환을 다룬다. 수학 지식과 공학 이론을 응용하여 신호와 sampling 과정을 주파수 영역에서 이해하고 표현할 수 있다.
IT 분야의 신호처리 관련 공학적 문제를 sampling과 FIR 필터 지식을 응용하여 분석할 수 있다. 신호처리 관련 차세대 성장 동력 관련 핵심 기술 습득에 주파수 스펙트럼, sampling, FIR 필터 지식을 적용할 수 있다.
IT 분야의 신호처리 관련 공학적 문제를 sampling과 FIR 필터 지식을 응용하여 분석할 수 있다. 신호처리 관련 차세대 성장 동력 관련 핵심 기술 습득에 주파수 스펙트럼, sampling, FIR 필터 지식을 적용할 수 있다.
- 수강안내 및 수강신청
- ※ 수강확인증 발급을 위해서는 수강신청이 필요합니다
Sinusoids
차시별 강의
| 1. | |
Sinusoids | Sampling and plotting sinusoids, Complex exponential and phasors, Phasor addition, Time Signals |  |
| 2. | |
Sinusoids | Sampling and plotting sinusoids, Complex exponential and phasors, Phasor addition, Time Signals | |
| 3. | |
Sinusoids | Sampling and plotting sinusoids, Complex exponential and phasors, Phasor addition, Time Signals | |
| 4. | |
Sinusoids, Spectrum representation | Phasor addition, Time Signals, The spectrum of sum of sinusoids, Beat notes, Periodic waveforms | |
| 5. | |
Spectrum representation | The spectrum of sum of sinusoids, Beat notes, Periodic waveforms | |
| 6. | |
Spectrum representation | The spectrum of sum of sinusoids, Beat notes, Periodic waveforms | |
| 7. | |
Spectrum representation | Periodic waveforms, Fourier series, Spectrum of Fourier series | |
| 8. | |
Spectrum representation | Fourier analysis of periodic signals, Fourier series synthesis, Time-frequency spectrum, Frequency modulation | |
| 9. | |
Spectrum representation | Fourier analysis of periodic signals, Fourier series synthesis, Time-frequency spectrum, Frequency modulation | |
| 10. | |
Spectrum representation | Fourier analysis of periodic signals, Fourier series synthesis, Time-frequency spectrum, Frequency modulation | |
| 11. | |
FIR filters | Discrete-time system, Running-average filter, General FIR filter, Convolution of FIR filter | |
| 12. | |
FIR filters | Discrete-time system, Running-average filter, General FIR filter, Convolution of FIR filter | |
| 13. | |
FIR filters | Impulse response, Implementation of FIR filters, Linear time-invariant system, Convolution and LTI system, Cascaded LTI system, Example of FIR filtering | |
| 14. | |
FIR filters | Impulse response, Implementation of FIR filters, Linear time-invariant system, Convolution and LTI system, Cascaded LTI system, Example of FIR filtering | |
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Continuous-time Fourier transform | Filtering sampled continuous-time signals, Definition of Fourier transform, Fourier transform and the spectrum | |
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| 15. | |
FIR filters | Impulse response, Implementation of FIR filters, Linear time-invariant system, Convolution and LTI system, Cascaded LTI system, Example of FIR filtering | |
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Sampling and aliasing | Sampling, Spectrum view of sampling and reconstruction | |
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Sampling and aliasing | Sampling, Spectrum view of sampling and reconstruction | |
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Sampling and aliasing | Spectrum interpretation, Discrete-to-continuous conversion | |
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Frequency response of FIR filters | Sinusoidal response of FIR systems, Superposition and frequency response | |
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Frequency response of FIR filters | Superposition and frequency response, Steady-state and transient state, Properties of frequency response | |
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Frequency response of FIR filters | Properties of frequency response, Graphical representation of frequency response, Cascaded LTI system, Running-average filtering | |
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Frequency response of FIR filters, Continuous-time Fourier transform | Graphical representation of frequency response, Cascaded LTI system, Running-average filtering | |
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