1. EEE 420 Digital Signal Processing Instructor : Erhan A. Ince E-mail: erhan.ince@emu.edu.trerhan.ince@emu.edu.tr Web page address: http://faraday.ee.emu.edu.tr/http://faraday.ee.emu.edu.tr/eeng420

2. Digital Signal Processing And Its Benefits By a signal we mean any variable that carries or contains some kind of information that can be conveyed, displayed or manipulated. Examples of signals of particular interest are: -speech, is encountered in telephony, radio, and everyday life - biomedical signals, (heart signals, brain signals) -Sound and music, as reproduced by the compact disc player -Video and image, -Radar signals, which are used to determine the range and bearing of distant targets

3. Attraction of DSP comes from key advantages such as : * Guaranteed accuracy: (accuracy is only determined by the number of bits used) * Perfect Reproducibility: Identical performance from unit to unit ie. A digital recording can be copied or reproduced several times with no loss in signal quality * No drift in performance with temperature and age * Uses advances in semiconductor technology to achieve: (i) smaller size (ii) lower cost (iii) low power consumption (iv) higher operating speed * Greater flexibility: Reprogrammable, no need to modify the hardware * Superior performance ie.linear phase response can be achieved complex adaptive filtering becomes possible

4. Disadvantages of DSP * Speed and Cost DSP designs can be expensive, especially when large bandwidth signals are involved. ADC or DACs are either to expensive or do not have sufficient resolution for wide bandwidth applications. * DSP designs can be time consuming plus need the necessary resources (software etc) * Finite word-length problems If only a limited number of bits is used due to economic considerations serious degradation in system performance may result.

5. Application Areas Image Processing Instrumentation/ControlSpeech/Audio Military Pattern recognition spectrum analysis speech recognition secure communications Robotic vision noise reduction speech synthesis radar processing Image enhancement data compression text to speech sonar processing Facsimile position and ratedigital audio missile guidance animation controlequalization TelecommunicationsBiomedicalConsumer applications Echo cancellationpatient monitoringcellular mobile phones Adaptive equalizationscannersUMTS ADPCM trans-codersEEG brain mappersdigital television Spread spectrumECG Analysisdigital cameras Video conferencingX-Ray storage/enhancement internet phone etc.

6. Key DSP Operations 1.Convolution 2.Correlation 3.Digital Filtering 4.Discrete Transformation 5.Modulation

7. Convolution Convolution is one of the most frequently used operations in DSP. Specially in digital filtering applications where two finite and causal sequences x[n] and h[n] of lengths N 1 and N 2 are convolved where, n = 0,1,…….,(M-1) and M = N 1 + N 2 -1 This is a multiply and accumulate operation and DSP device manufacturers have developed signal processors that perform this action.

8. Correlation There are two forms of correlation : 1. Auto-correlation 2. Cross-correlation 1.The cross-correlation function (CCF) is a measure of the similarities or shared properties between two signals. Applications are cross-spectral analysis, detection/recovery of signals buried in noise, pattern matching etc. Given two length-N sequences x[k] and y[k] with zero means, an estimate of their cross-correlation is given by: Where, r xy (n) is an estimate of the cross covarience

9. The cross-covarience is defined as

10. 2.An estimate of the auto-correlation of an length-N sequence x[k] with zero mean is given by

11. Digital Filtering The equation for finite impulse response (FIR) filtering is Where, x[k] and y[k] are the input and output of the filter respectively and h[k] for k = 0,1,2,………,N-1 are the filter coefficients

12. Filter structure A common filtering objective is to remove or reduce noise from a wanted signal.

13. (a) (b) (c) (d) (e) (f) Figure : Reconstructed bi-level text images for degradation caused by h 1 and AWGN. (a) Original, (b) 2D Inverse, (c) 2D Wiener, (d)PIDD, (e) 2D VA-DF, (f) PEB-FCNRT

14. Discrete Transformation Discrete transforms allow the representation of discrete-time signals in the frequency domain or the conversion between time and frequency domain representations. Many discrete transformations exists but the discrete Fourier transform (DFT) is the most widely used one. DFT is defined as: IDFT is defined as:

15. MATLAB function for DFT function [Xk] = dft(xn) N=length(xn); n = 0:1:N-1; % row vector for n k = 0:1:N-1; % row vecor for k WN = exp(-1j*2*pi/N); % Twiddle factor (w) nk = n'*k; % creates a N by N matrix of nk values WNnk = WN.^ nk; % DFT matrix Xk = (WNnk*xn' );

16. Matlab Function for IDFT function [xn] = idft(Xk) % Computes Inverse Discrete Transform % ----------------------------------- % [xn] = idft(Xk) % xn = N-point sequence over 0 <= n <= N-1 % Xk = DFT coeff. array over 0 <= k <= N-1 % N = length of DFT % N = length(Xk); n = [0:1:N-1]; % row vector for n k = [0:1:N-1]; % row vecor for k WN = exp(-j*2*pi/N); % Wn factor nk = n'*k; % N by N matrix of nk values WNnk = WN.^ (-nk); % IDFT matrix xn = (Xk' * WNnk)/N; % row vector for IDFT values

17. Example Let x[n] be a 4-point sequence >>x=[1, 1, 1, 1]; >>N = 4; >>X = dft(x,N); >>magX = abs(X) ; >>phaX = angle(X) * 180/pi; magX= 4.0000 0.0000 0.0000 0.0000 phaX= 0-134.981-90.00-44.997

18. Modulation Discrete signals are rarely transmitted over long distances or stored in large quantities in their raw form. Signals are normally modulated to match their frequency characteristic to those of the transmission and/or storage media to minimize signal distortion, to utilize the available bandwidth efficiently, or to ensure that the signal have some desirable properties. Two application areas where the idea of modulation is extensively used are: 1. telecommunications 2. digital audio engineering High frequency signal is the carrier The signal we wish to transmit is the modulating signal

19. Three most commonly used digital modulation schemes for transmitting Digital data over bandpass channels are: Amplitude shift keying (ASK) Phase shift keying (PSK) Frequency shift keying (FSK) When digital data is transmitted over an all digital network a scheme known As pulse code modulation (PCM) is used.