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Mr. Thilak de Silva. BSc. Eng., MSc, CEng, FIE(SL), FIET(UK), CITP(UK), MBCS(UK), MIEEE (USA) M.Sc. in IT - Year 1 Semester II - 2012
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Analog and Digital Signals. Periodic and Non-periodic signals. Time domain and Frequency domain representation. Fourier Analysis Nyquest theorem. M.Sc. in IT - Year 1 Semester II - 2012
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At the end of this session you will have a broad understanding of Analog and Digital signals, Fourier Analysis and Nyquest theorem. M.Sc. in IT - Year 1 Semester II - 2012
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Data is in memory. It is converted in to Signals When transmitting Need a transmission media to transmit signals. Signals can be divided as, ▪ Analog Signals, Digital Signals ▪ Periodic Signals, Non Periodic Signals M.Sc. in IT - Year 1 Semester II - 2012
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Analog signals are continuous and has infinitely many levels of intensity over a period of time. Digital signals are discrete and has limited number of levels of intensity over a period of time. M.Sc. in IT - Year 1 Semester II - 2012
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Can be analog or digital. Periodic signals – has a pattern which repeats over identical periods. (Cycle) Practically we do not have periodic signals. Non periodic signals – changes without exhibiting a pattern or cycle that repeats over time. M.Sc. in IT - Year 1 Semester II - 2012 Periodic analog signal Non Periodic analog signal
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Has 3 parameters, Amplitude Frequency Phase
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Time Domain Representation shows changes in signal amplitude with respect to time Frequency domain representation show the relationship between amplitude and frequency M.Sc. in IT - Year 1 Semester II - 2012
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A composite signal is made of many sine waves. Fourier showed that any composite signal is actually a combination of simple sine waves with different frequencies, amplitudes and phases. These are known as harmonics M.Sc. in IT - Year 1 Semester II - 2012
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A composite periodic Signal Source - http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image01617.jpghttp://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image01617.jpg M.Sc. in IT - Year 1 Semester II - 2012
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Use to transform a time domain signal in to frequency components. Only applicable for periodic signals. According to Fourier analysis any signal is composed with several frequencies called harmonics. M.Sc. in IT - Year 1 Semester II - 2012
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Fundamental frequency – f (first harmonic) Third harmonic – 3f Fifth harmonic – 5f … Source - http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image01814.jpghttp://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image01814.jpg M.Sc. in IT - Year 1 Semester II - 2012
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Range of frequencies / Difference between the highest and lowest frequencies Source - http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image02014.jpghttp://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image02014.jpg M.Sc. in IT - Year 1 Semester II - 2012
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When adding two signals the strength of the resulting signal depends on the phase differences, amplitudes, frequencies etc. Eg:- In phase (add voltages)Out phase (deduct voltages) M.Sc. in IT - Year 1 Semester II - 2012
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A digital signal has infinite number of frequency components. (Bit rate)Speed = 1kb per second 2 ms F=1/T F=1/2*10 F=5ooHz F=0.5Khz -3 Required Bandwidth (Fundamental frequency) = ½*Bit Rate T Bit Pattern = 101010 M.Sc. in IT - Year 1 Semester II - 2012
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Bit rate = 1kb per second Bit Pattern = 11001100 F=1/T F=1/4*10 F=25oHz F=0.25Khz -3 Required Bandwidth = 0.25Khz M.Sc. in IT - Year 1 Semester II - 2012 T 4 ms
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At the receiving end the signal is regenerated by looking at the amplitude, IF amplitude is high 1 is generated IF amplitude is low 0 is generated Therefore we must at least send the fundamental frequency. That’s why we say that the bandwidth should be at least half of the bit rate. M.Sc. in IT - Year 1 Semester II - 2012
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When frequency getting high the amplitude gets low. Sending more and more harmonics makes the signal regeneration easy. But this is expensive due to high bandwidth. Deciding the number of harmonics we send should be done based on the characteristics of the media. M.Sc. in IT - Year 1 Semester II - 2012
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Periodic Signal Fourier Analysis Non Periodic Signal Fourier Transform A Discrete Frequency Spectrum A Continuous Frequency Spectrum M.Sc. in IT - Year 1 Semester II - 2012
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Can have two or more discrete level. Bit Rate – number of bits sent per second. Baud rate – signal changing rate per second Required bandwidth depends on the baud rate. M.Sc. in IT - Year 1 Semester II - 2012
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Two Levels One signal element represents one bit Therefore bit rate= baud rate Four Levels One signal representation has two bits Therefore bit rate= baud rate M.Sc. in IT - Year 1 Semester II - 2012 Source : http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image02214.jpg http://train-srv.manipalu.com/wpress/wp-content/uploads/2010/01/clip-image02214.jpg
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We can increase the Bit Rate without increasing the Bandwidth. But, The error probability is high, Circuit component cost is high, Effect of transmission impairments is high, There for we do not use 4 levels practically. M.Sc. in IT - Year 1 Semester II - 2012
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Atténuation Delay Noise Jitter M.Sc. in IT - Year 1 Semester II - 2012
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BitRate = 2 x bandwidth x log 2 L Assumptions One signal element carry only one bit No noise, attanuation etc in the transmission media If there are noise and attanuation (Shannon Capacity) Capacity = bandwidth x log 2 (1 + SNR) M.Sc. in IT - Year 1 Semester II - 2012
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If Capacity = 20 Kbp/s & Bit Rate = 3 Kbp/s Can represent maximum 6 bits per element. 2 = 64 combinations of amplitude or phase differences. (64 QAM) M.Sc. in IT - Year 1 Semester II - 2012 2 bits per element6 Kbp/s 3 bits per element9 Kbp/s 4 bits per element12 Kbp/s 5 bits per element15 Kbp/s 6 bits per element18 Kbp/s 7 bits per element21 Kbp/s 6
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Data Communications and Networking, Forouzan, Chapter 03, 4 th Edition M.Sc. in IT - Year 1 Semester II - 2012
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