數(shù)字信號處理英文版課件：Chap 1 Signals and Signal Processing

1、 NJUSTDiscrete-Time Signal Processing(DTSP）2014DSP group chap1-ed12 DTSPCredits = 3.5 (56 hours) Course = Lectures (48 hours) + Experiments (8 hours) Score = Examination (70%) + Experiment (10%) + Exercise(10%) + Matlab (10%)Auxiliary tool software: MatlabDSP group chap1-ed13f = 10Hz, fs = 100HzDSP

2、group chap1-ed14 DTSPTextbook: Digital Signal Processing A computer-Based Approach, 4th Edition.Authors: Sanjit K.Mitra, 闊永紅 ModifiedReference books：*1. A.V. Oppenheim, R.W.Schafer Discrete-Time Signal Processing. 2nd Ed., McGraw-Hill; 2. 程佩青,數(shù)字信號處理教程, 第二版, 清華大學(xué)出版社,2001 3王世一 數(shù)字信號處理，北京理工大學(xué)出版社, 2000 4

3、. 胡廣書 數(shù)字信號處理理論、算法與實現(xiàn)清華大學(xué)出版社DSP group chap1-ed15 DTSPReference books： 5. 高息權(quán)，丁玉美 數(shù)字信號處理學(xué)習(xí)指導(dǎo), 西安電子科技大學(xué)出版社, 2001 6. A.V. 奧本海姆，R.W. 謝弗著，黃建國，劉樹棠譯 離散時間信號處理 北京：科學(xué)出版社，2001 7. Vinay K. Ingle, John G.Proakis, 陳懷琛等譯：數(shù)字信號處理及其Matlab實現(xiàn), 電子工業(yè)出版社, 1998 DSP group chap1-ed16 IntroductionDSP group chap1-ed17 Introduct

4、ionDigital Signal Processing Theory, method, algorithm A kind of microprocessor used to implement digital signal processing algorithmDigital Signal ProcessorDSP group chap1-ed18 IntroductionThe foundation of information technology is digitalization.The kernel of digitalization is digital signal proc

5、essingMost of digital signal processing, especially real-time processing are implemented by DSP processor or ASIC based on DSP core DSP technology is growing up rapidly.DSP group chap1-ed19 DSP Solution DSP group chap1-ed110 Applications of DSPDVD Blu-Ray Disk = 405nm = Data Capacity 25GB/Layer DSP

6、group chap1-ed111 Applications of DSPNetwork DSP group chap1-ed112 DTSP Outlines Discrete -Time Signals (Chap 2, 3) Sampling of continuous-Time Signals (Chap 2) Discrete-Time Fourier Transform (DTFT) (Chap 3) Discrete-Time Systems (Chap 4) Finite-Length Discrete Transform (DFT) (Chap 5) The z-transf

7、orm (Chap 6) Transform Analysis of LTI systems (Chap 7) Digital Filter Structures (Chap 8) Filter Design Techniques (Chap 9-10) DFT Algorithm Implementation (Chap 11)DSP group chap1-ed113 Chap 1 Signals and Signal Processing Characterization and Classification of Signals; Typical Signal Processing O

8、perations; Examples of Typical Signals Typical Signal Processing Applications; Why Digital Signal ProcessingDSP group chap1-ed114 Signals Signals play an important role in our daily life. A signal is a function of independent variables such as time, distance, speed, position, temperature, pressure e

9、tc. Signal processing is concerned with the mathematical representation of the signal and the algorithmic operation carried out on it to extract the information present. A signal carries information; the objective of signal processing is to extract useful information carried by the signal. DSP group

10、 chap1-ed115Continuous-time signalDiscrete-time signal Types of Signal depends on the nature of the independ- ent variables and the value of the function defining the signal.Real-valued signalComplex-valued signal Analog/ Digital 1.1 Characterization & Classification of SignalsDSP group chap1-ed116

11、Digital signals/ Analog signalsDSP group chap1-ed117 1.1 Characterization & Classification of SignalsDeterministic signalRandom signal Signal classifications:1-D signalM-D signal DSP group chap1-ed118 1.2 Typical Signal Processing Operations Operations can be implemented in real-time, near real-time

12、 and off-line.1.2.1 Simple Time-Domain Operations: Operations can be carried out in the time-domain, or in frequency-domain. Scaling; Delay; Addition; Production Integration: Differentiation:DSP group chap1-ed1191.2.2 Filtering Filtering is one of the most widely used complex signal processing opera

13、tions. The system implementing this operation is called a Filter. A Filter passes certain frequency components in a signal without any distortion and blocks other frequency components. DSP group chap1-ed1201.2.2 Filtering For continuous-time signal: LTI system ( h(t) ) output signal of LTI analog fi

14、lter convolution or in frequency-domain:DSP group chap1-ed121 Example of FilteringInput signal Output signal of a lowpass filter P6DSP group chap1-ed1221.2.3 Multiplexing & Demultiplexing For an efficient utilization of a wideband transmission Channel, Many narrow-bandwidth low-frequency signals are

15、 combined to form a composite wideband signal that is transmitted as a single signal. The process of combining these signals is called multiplexing . Multiplexing is implemented to ensure that a replica of the original narrow-bandwidth low-frequency signals can be recovered at the receiving end. Dem

16、ultiplexing is the recovery process in the receiving end.DSP group chap1-ed123 Example of Multiplexing FDM is a widely used method.QAMP11DSP group chap1-ed1241.2.4 Signal generation Simple signal generation: Oscillator sinusoidal signal Generation of complex signals: Hibert filter analytic signalDSP

17、 group chap1-ed1251.2.4 Signal generationDSP group chap1-ed126 1.3 Examples of Typical Signals ECG signalP13RQSTP Time seriesDSP group chap1-ed127 Musical Sound Signals Speech & music signals represent air pressure as a function of time at a point in space. Waveform of the speech signal I like digit

18、al signal processing28 Musical Sound Signals DSP group chap1-ed129 Image Signals static black-and-white image signalsDSP group chap1-ed130 1.3 Examples of Typical Signals Video signalsvideo Seismic signalsDSP group chap1-ed131 1.4 Typical Signal Processing Applications Digital sound synthesisTTS; Sp

19、eech recognition; Signal coding and compression; Radar Cellular phone; Discrete multitone transmission (DMT); Digital camera; Signal enhancementDSP group chap1-ed133 ApplicationMTKDSP group chap1-ed134 ApplicationADSL (Asymmetric Digital Subscriber Line) DSP group chap1-ed135 ApplicationADSL DSP gro

20、up chap1-ed136 ApplicationDigital Camrer CMOS image sensor Image processing algorithms Bad pixed detection and masking; Color interpolation Color balancing Contrast enhancement False color detection and masking Image and video compressionDSP group chap1-ed137 Applicationimage enhancementOriginalEnha

21、ncedDSP group chap1-ed138 ApplicationSummarySpeech Signal ProcessingImage Signal ProcessingCommunication Signal ProcessingRadar Signal ProcessingBiomedical Signal ProcessingSeismic explorationDSP group chap1-ed139 1.5 Why Digital Signal Processing Digital processing of an analog signalDigital-to-ana

22、log converterDigital processorSample-and-holdAnalog-to-digital converterAnalog lowpass filterFig. 1.27 Scheme for the digital processing of an analog signal A/D converterD/A converterAnalog processorAnalog Input xc(t)Analog output yr(t)DSP group chap1-ed140 Advantages of DSP Stability = Absence of d

23、rift in the filter characteristics Processing characteristics are fixed, e.g. by binary coefficients stored in memories; They are independent of the external environment and of parameters such as temperature; Aging has no effectDSP group chap1-ed141 Advantages of DSP Precision = Improved quality lev

24、el Quality of processing limited only by economic considerations; Arbitrarily low degradations achieved with desired quality by increasing the number of bits in data/ coefficient representation; An increase of 1 bit in the representation results in a 6dB improvement in the SNR.DSP group chap1-ed142

25、Component tolerances do not affect system performance with correct operation; No adjustments necessary during fabrication(裝配); No realignment needed over lifetime of equipment. Advantages of DSP Programmability = Reproducibility Easy to develop and implement adaptive filters, programmable filters and complementary filters; Illustrates flexibility of digital techniques. Ease of new function developmentDSP group chap1-ed143 Advantages of DSP Same equipment can be shared between several signals, with obvious financial advantages for each function Multiplexing Uses standard digital circui