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Introduction

DIGITAL SIGNAL PROCESSING. Introduction. Course information. Course information(C0ntd..). Discrete Time signal. Sequence x[n] as opposed to continuous time signals x(t). Discrete in Nature. Population statistics Stock market indices. Sampled continuos time (analog) signals. Example

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Introduction

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  1. DIGITAL SIGNAL PROCESSING Introduction

  2. Course information

  3. Course information(C0ntd..)

  4. Discrete Time signal • Sequence x[n] as opposed to continuous time signals x(t)

  5. Discrete in Nature • Population statistics • Stock market indices

  6. Sampled continuos time (analog) signals • Example • Speech

  7. Applications

  8. Speech Processing Original speech High pass Down sample Up sample Low pass

  9. Image Processing

  10. Video Processing General Concept: Object 1 Motion Analysis Object 2 Video Synthesis Applications Analysis

  11. Discrete-Time System y(n)=T{x(n)}

  12. Why DTSP? • Discrete Time Signal Processing of Continuous Signals x (n) y (n) y(t) x (t)

  13. WhyDTSP? Digital Signal Processing (DSP) is derived from DTSP y(n) y(n) x(t) x(n)

  14. Discrete Time Signal

  15. Where Not?

  16. DSP COMPONENTS • Converting analog signal into digital sequence. • Performing all signal processing operations in digital in digital form. • If necessary converting the digital information back to analog signal. • A TYPICAL DSP SCHEME Analog Filter ADC DSP Processor DAC Analog Filter

  17. WHY DSP?

  18. Frequency Selective Filtering

  19. Echo Cancellation

  20. DSP SOLUTION TO EC

  21. Equalization

  22. Speech Transmission

  23. Image Processing

  24. Image Processing

  25. DSP in real time embedded systems

  26. Comparison of Chips POWE R CONSUMP T I ON FLEXIBILITY

  27. Comparison of Chips

  28. Course Outline

  29. Course Outline

  30. Course Outline • DSP: A/D,D/A • System Design and Implementation • Practical computation of F

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