1 / 24

מכללת BITLEE

מכללת BITLEE. קורס DSP יישומי לתעשיה. DSP- D igital S ignal P rocessing. FROM ANALOG TO DIGITAL DOMAIN. 25 March 2004. TOPICS. Analog vs. digital: why, what & how What is DSP? What is DSP used for? Speech & Audio processing Image & Video processing Adaptive filtering

luana
Download Presentation

מכללת BITLEE

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. מכללת BITLEE קורס DSP יישומי לתעשיה

  2. DSP- Digital Signal Processing

  3. FROM ANALOG TO DIGITAL DOMAIN 25 March 2004

  4. TOPICS • Analog vs. digital: why, what & how • What is DSP? • What is DSP used for? • Speech & Audio processing • Image & Video processing • Adaptive filtering • Digital system example • Sampling & aliasing • Frequency analysis: why? & applications • DSP Devices and Architectures

  5. Analog Digital Discrete function Vk of discrete sampling variable tk, with k = integer: Vk = V(tk). Continuous function V of continuous variable t (time, space etc) : V(t). Uniform (periodic) sampling. Sampling frequency fS = 1/ tS Analog & digital signals

  6. Limitations Advantages • A/D & signal processors speed: wide-band signals still difficult to treat (real-time systems). • Finite word-length effect. • Obsolescence (analog electronics has it, too!). • More flexible. • Often easier system upgrade. • Data easily stored. • Better control over accuracy requirements. • Noise reduction. Digital vs analog proc’ing Digital Signal Processing (DSPing)

  7. Predicting a system’s output. • Implementing a certain processing task. • Studying a certain signal. Applications • General purpose processors (GPP), -controllers. • Digital Signal Processors (DSP). • Programmable logic ( PLD, FPGA ). Hardware Fast Faster real-time DSPing • Programming languages: Pascal, C / C++ ... • “High level” languages: Matlab, Mathcad, Mathematica… • Dedicated tools (ex: filter design s/w packages). Software DSPing: aim & tools

  8. What is DSP? Digital Signal Processing – the processing or manipulation of signals using digital techniques Digital Signal Processor Input Signal Output Signal ADC DAC Analogue to Digital Converter Digital to Analogue Converter

  9. What is DSP? • Feed in analog signal • Convert from analog to Digital • Process mathematical representation of signal • Convert from digital back to analog • Output analog signal • Real Time Processing of the mathematical representations of signals

  10. What is DSP Used For? …And much more!

  11. DATA VIDEO AUDIO DSP Technology & Markets VOICE

  12. General scheme ANALOG DOMAIN FilterAntialiasing FilterAntialiasing Sometimes steps missing - Filter + A/D - D/A + filter A/D A/D DIGITAL DOMAIN Digital Processing Digital Processing D/A ANALOG DOMAIN Topics of this lecture. FilterReconstruction Digital system example

  13. ANALOG INPUT Antialiasing Filter 1 2 3 A/D Digital Processing • Digital format. What to use for processing? See slide “DSPing aim & tools” DIGITAL OUTPUT Digital system implementation KEY DECISION POINTS: Analysis bandwidth, Dynamic range •Sampling rate. • Pass / stop bands. • No. of bits. Parameters.

  14. 1 * Ex: train wheels in a movie. 25 frames (=samples) per second. Train starts wheels ‘go’ clockwise. Train accelerates wheels ‘go’ counter-clockwise. *Sampling: independent variable (ex: time) continuous  discrete. Quantisation: dependent variable (ex: voltage) continuous  discrete. Here we’ll talk about uniform sampling. Sampling How fast must we sample a continuous signal to preserve its info content? Why? Frequency misidentification due to low sampling frequency.

  15. Lowpass Spectrum f -fmax fmax Bandpass Spectrum f –f1 f2 –f2 f1 Generalized Sampling Theorem • Sampling rate must be greater than twice the analog signal’s bandwidth • Bandwidth is defined asnon-zero extent of spectrumof the continuous-time signalin positive frequencies • Lowpass spectrum on right:bandwidth is fmax • Bandpass spectrum on right:bandwidth is f2 – f1

  16. 1 __ s(t) = sin(2f0t) s(t) @ fS f0 = 1 Hz, fS = 3 Hz __ s1(t) = sin(8f0t) __ s2(t) = sin(14f0t) s(t) @ fS represents exactly all sine-waves sk(t) defined by: sk (t) = sin( 2 (f0 + k fS) t ) , k  Sampling - 2

  17. 1 Example Condition on fS? F1 F2 F3 fS > 300 Hz F1=25 Hz, F2 = 150 Hz, F3 = 50 Hz fMAX The sampling theorem A signal s(t) with maximum frequency fMAX can be recovered if sampled at frequency fS > 2 fMAX . Theo* *Multiple proposers: Whittaker(s), Nyquist, Shannon, Kotel’nikov. Naming gets confusing ! Nyquist frequency (rate) fN = 2 fMAXor fMAXor fS,MINor fS,MIN/2

  18. 1 (a)Band-limited signal: frequencies in [-B, B] (fMAX = B). (a) (b) (b)Time sampling frequency repetition. fS > 2 B no aliasing. (c) (c)fS 2 B aliasing ! Aliasing: signal ambiguity in frequency domain Sampling low-pass signals

  19. 1 (a) (a),(b)Out-of-band noise can aliase into band of interest. Filter it before! (c)Antialiasing filter (b) • Passband: depends on bandwidth of interest. • Attenuation AMIN : depends on • ADC resolution ( number of bits N). • AMIN, dB ~ 6.02 N + 1.76 • Out-of-band noise magnitude. (c) Antialiasing filter

  20. 2 Different applications have different needs. • Number of bits N (~resolution) • Data throughput (~speed) • Signal-to-noise ratio (SNR) • Signal-to-noise-&-distortion rate (SINAD) • Effective Number of Bits (ENOB) • Spurious-free dynamic range (SFDR) • Integral non-linearity (INL) • Differential non-linearity (DNL) • … Radar systems Static distortion Communication Dynamic distortion Imaging / video NB: Definitions may be slightly manufacturer-dependent! (Some) ADC parameters

  21. 2 Continuous input signal digitized into 2N levels. Uniform, bipolar transfer function (N=3) Quantisation step q = V FSR 2N Ex: VFSR = 1V , N = 12 q = 244.1 V Voltage ( = q) Scale factor (= 1 / 2N ) Percentage (= 100 / 2N ) LSB Quantisation error ADC - Number of bits N

  22. Digital Telephony PCM (Pulse Code Modulation) • Standard telephone signal: _ Telephone speech bandwidth 300hz-3.4khz • Sampling Rate: 8 kHz • 8-bit samples • Data transfer rate = 88= 64kbits/s (64kbps) • ATU-TI G711

  23. Digital Audio • Standard music CD: _Sound is audible in 20 Hz to 20 kHz range: • Sampling Rate: 44.1 kHz • 16-bit samples • 2-channel stereo • Data transfer rate = 21644,100 = 1.4 Mbits/s • 1 hour of music = 1.43,600 = 635 MB

  24. 1 Example Ear + brain act as frequency analyser: audio spectrum split into many narrow bands low-power sounds detected out of loud background. • Bandwidth: indicates rate of change of a signal. High bandwidth signal changes fast. Frequency domain (hints) • Time & frequency: two complementary signal descriptions. Signals seen as “projected’ onto time or frequency domains.

More Related