1. Digital Signal Processing (7KS01)
UNIT 1
Discrete-time signals and systems By
Prof S.G.Pundkar

2. Analog Signal Processing
An analog signal is a continuous wave denoted by a sine wave and may vary in signal strength (amplitude) or frequency (time).
There are many examples of analog signals around us. The sound from a human voice is analog, because sound waves are continuous, as is our own vision.

3. Digital Signal Processing
If input to the system is analog and output is discrete in nature, then it is referred to as a discrete time system.
This analog to digital conversion is performed by an electronic device called sampler which convert analog signal to its discrete equivalent.
Sampled version is given to quantizes where amplitude of each sample gets round-off to a nearest integer value.
Finally the quantized signal is encoded by binary encoder to get digital equivalent of the analog signal.

5. Advantages Of Digital Signal Processing Over Analog Signal Processing
Digital signal processing operations can be changed by changing the program in digital programmable system, i.e., it is flexible systems.
Better control of accuracy in digital systems compared to analog systems.
Digital signals are easily stored on magnetic media such as magnetic tape without loss of quality of reproduction of signal. 
Digital signals can be processed off line, i.e., these are easily transported.
Sophisticated signal processing algorithms can be implemented by DSP method.
Digital circuits are less sensitive to tolerances of component values.
Digital circuits can be reproduced easily in large quantities at comparatively lower cost.
Digital system can be cascaded without any loading problems.
Digital Signals can be easily compressed as compared to ASP.
Digital Signals can be easily encrypted and decrypted.

6. Limitation of DSP
Processing of signals involves more power consumption
Processing of signals beyond higher frequencies (beyond GHz) and below lower frequencies (a few Hz) involves limitations
Information is lost because we only take samples of the signal at intervals.

7. Application of DSP
Telecommunication :Echo cancellation in telephone, video conferencing, cellular phone, Fax.
Consumer Electronics :Digital audio, electronic music , FM stereo application
Image Processing :Image compression, image enhancement, image analysis.
Medical Field :Medical diagnostic instrumentation such as CT-Scan, MRI etc.
Military
Speech Processing

11. Basic Block diagram of DSP
Q.1. Explain the block diagram of DSP? Give the applications of DSP (S-15 For 6 marks)
Basic Block diagram of DSP
Detail Block diagram of DSP

12. Q. 2. Explain with a neat diagram the analog to digital conversion
Q.2. Explain with a neat diagram the analog to digital conversion? (S-14, W-14 For 6 Mks)

14. Sampling of Analog Signal
Sampling Theorem :
This is the conversion of continuous time signal into discrete time signal obtain by taking “sample” of the continuous-time signal at discrete time instance.
Thus, if Xa(t) is the input to the sample, the output is Xa(nT)= X(n), where T is called Sampling Interval.
A continuous time signal x(t) can be completely represented in its sampled form and recover back from the sample form if the sampling frequency Fs>=2w
Where
w=Max. frequency of continuous time signal x(t) .
t=sampling duration
Fs= 1/T is a sampling rate

15. According to Nyquist, Sampling rate should be greater than equal to twice of maximum frequency component available in signal Fs>= 2Fmax. This is called as Nyquist rate.

16. Important Formulae
Xa(t) = ws (2∏Ft)
To find x(n), Replace t by n/Fs where fs= Sampling Frequency.
Nyquist Rate = 2 Fmax , where Fmax = Max Freq.
Samples/sec = (bit rate)/(bit/sample)
Folding Frequency = (Sample/sec) / 2
Resolution (∆) = Xmax – Xmin / L-1

17. Problems