Multimedia Systems WS 2010/2011 08.11.2010 M. Rahamatullah - PowerPoint PPT Presentation

Multimedia Systems WS 2010/2011 08.11.2010 M. Rahamatullah Khondoker (Room # 36/410 ) University of Kaiserslautern Department of Computer Science Integrated Communication Systems ICSY http://www.icsy.de

Outline  Data and Signals  Signal Basics  Digitization  Sampling  Quantization  Encoder  Decibels 2 M. Rahamatullah Khondoker, University of Kaiserslautern

Data and Signals  Analog data: continuous and takes continuous values  Examples: speech, analog clock, hands movement  Digital data: have discrete states and takes discrete values  Examples: digital clock  Analog signal: has infinite number of values in a range  Digital signal: have limited number of values 3 M. Rahamatullah Khondoker, University of Kaiserslautern

Signal Basics  Signals can be periodic or non-periodic  Period (T): time (in second) of one cycle  Frequency (f): number of periods in 1 second  Frequency (f) and periods (T) are inverse to each other  Peak Amplitude (A): absolute value of its highest intensity Fig. Example of periodic signals 4 M. Rahamatullah Khondoker, University of Kaiserslautern

Signal Basics  Phase: position of the signal relative to time 0 Fig. Examples of different phases of signal Fig. Examples amplitudes, frequencies and phase 5 M. Rahamatullah Khondoker, University of Kaiserslautern

Digitization

Digitization  Digitization is the process of creating digital data from analog signal  Steps  Sampling  Quantizing  Encoding  Examples encoder  Pulse Code Modulation (PCM)  Delta Modulation 7 M. Rahamatullah Khondoker, University of Kaiserslautern

Sampling  Capture continuous signal in a discrete interval  Nyquist – Shannon sampling theorem A signal with a maximum frequency (Nyquist-Frequency, Grenzfrequenz) f max has to be sampled with a minimal frequency of f a =2*f max to allow an accurate reconstruction of the original signal. 8 M. Rahamatullah Khondoker, University of Kaiserslautern

Sampling  signal with f s =200 Hz Amplitude Time 1 ------ s 100 9 M. Rahamatullah Khondoker, University of Kaiserslautern

Sampling  signal with f s =200 Hz  sampling rate of f a =300 Hz Amplitude Time 1 ------ s 100  Maximum frequency of chosen sampling rate is f g = f a /2 = 150 Hz 10 M. Rahamatullah Khondoker, University of Kaiserslautern

Sampling  signal with f s =200 Hz  sampling rate of f a =300 Hz Amplitude Time 1 ------ s 100  Maximum frequency of chosen sampling rate is f g = f a /2 = 150 Hz  Reconstruction results in a the signal with f r = 100 Hz 11 M. Rahamatullah Khondoker, University of Kaiserslautern

Sampling Amplitude Time Frequency (Hz) 1 ------ s 100 f r f g f s Time Domain Frequency Domain 12 M. Rahamatullah Khondoker, University of Kaiserslautern

Sampling  Oversampling  Theoretically no advantages  Usage scenario: Non-optimal filters • Ideal vs. real low-pass filter  Disadvantages • no quality gain • more storage space & higher data rates are required  Undersampling  Signal cannot be reconstructed 13 M. Rahamatullah Khondoker, University of Kaiserslautern

Quantization  Transform signal with continuous values into a signal with discrete values 14 M. Rahamatullah Khondoker, University of Kaiserslautern

Quantization Error  Occurs when the approximated value is not equal to the real value  Low quantization error  Low bit rate and low storage consumptions  High quality  High quantization error  High bit rate and high storage consumptions  Low quality 15 M. Rahamatullah Khondoker, University of Kaiserslautern

Pulse Code Modulation  PCM has  PAM Sampler  Quantizer  Encoder  PAM sampler makes PAM pulses  Quantizer constitutes PCM pulses  Encoder provides digital data 16 M. Rahamatullah Khondoker, University of Kaiserslautern

Decibel

Decibel  Signals lost or gained strength is measured by using decibel  Relative strength of two signals or one signal at different points  A specification in decibel is always related to a reference value!  Decibels can be added or subtracted when we are measuring several points instead of two 18 M. Rahamatullah Khondoker, University of Kaiserslautern

Decibel  dB(SPL)  often simplified: dB  sound pressure level • Measurement unit: pascal (Pa) • relative to 20 micropascals ( μ Pa) = 2×10 −5 Pa  dB(A), dB(B), dB(C), dB(D)  unit adapted to the sound level perception of human hearing  A-, B-, or C-Filter for weighting  dBm, dBmW  electrical power • Measurement unit: milliwatt • Relative to 1 milliwatt  dBi  Transmission power of antennas • Relative to hypothetical perfect isotropic antenna 19 M. Rahamatullah Khondoker, University of Kaiserslautern

Thanks for your attention Any questions, comments or concerns?

M. Rahamatullah Khondoker, M.Sc. Integrated Communication Systems ICSY University of Kaiserslautern Department of Computer Science P.O. Box 3049 D-67653 Kaiserslautern Phone: +49 (0)631 205-26 43 Fax: +49 (0)631 205-30 56 Email: khondoker@informatik.uni-kl.de Internet: http://www.icsy.de