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CALVIN ENGR 311 - Chapter 1

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PowerPoint PresentationSlide 2Slide 3Slide 4Slide 5Slide 6Slide 7Slide 8Slide 9Slide 10Slide 11Slide 12Slide 13Slide 14Slide 15Slide 16Slide 17Slide 18Slide 19Slide 20Slide 21Slide 22Slide 23Slide 24Slide 25Slide 26Slide 27Slide 28Slide 29Slide 30Slide 31Slide 32Slide 33Slide 34Slide 35Slide 36Slide 37Slide 38Slide 39Chapter 1 - Introduction to ElectronicsIntroductionMicroelectronicsIntegrated Circuits (IC) TechnologySilicon ChipMicrocomputer / MicroprocessorDiscrete CircuitsSignalsSignal processinghttp://www.eas.asu.edu/~midle/jdsp/jdsp.htmlSignalsVoltage SourcesCurrent SourcesThevenin & Norton http://www.clarkson.edu/%7Esvoboda/eta/ClickDevice/refdir.htmlhttp://www.clarkson.edu/%7Esvoboda/eta/Circuit_Design_Lab/circuit_design_lab.htmlhttp://www.clarkson.edu/%7Esvoboda/eta/CircuitElements/vcvs.htmlSignalsVoltage SourcesCurrent Sourceshttp://www.clarkson.edu/~svoboda/eta/ClickDevice/super.htmlhttp://javalab.uoregon.edu/dcaley/circuit/Circuit_plugin.htmlSignalsVoltage SourcesCurrent SourcesFrequency Spectrum of SignalsFourier SeriesFourier TransformFundamental and Harmonicshttp://www.educatorscorner.com/experiments/spectral/SpecAn3.shtmlxfrequencytimeDefining the Signal or Function to be Analyzed:f t( ) sin 0t  t( ) .2 cos 7 0 t 0 1 2 3 4 5 6202f t( )tFrequency Spectrum of SignalsFourier Serieshttp://www.jhu.edu/%7Esignals/fourier2/index.htmlFrequency Spectrum of SignalsFourier SeriesFourier Series (Trigonometric form) of f(t):a01T0Ttf t( )d a00average valuean2T0Ttf t( ) cos n 0 t dcosine coefficientsn varying from 1 to N10 20 30 40 50 6000.1an0nFrequency Spectrum of SignalsFourier Seriesbn2T0Ttf t( ) sin n 0 t dsine coefficients10 20 30 40 50 6000.51bn0nFrequency Spectrum of SignalsFourier SeriesRearranging total expression to include a0 in the complete spectruma1nan b1nbnc1n12a1n 2b1n 2 c0a00 10 20 30 40 50 6000.20.4c1n0nFrequency Spectrum of SignalsFourier SeriesReconstruction of time-domain function from trig. Fourier series:f2 t( )n1an1cos n1 0 t  bn1sin n1 0 t  �a00 1 2 3 4 5 6202f2 t( )f t( )tFrequency Spectrum of SignalsFourier SeriesFourier Series (Complex Form) of f(t):wn12N  nCn1T0tf t( ) ei wn 0 td0 10 20 30 40 50 6000.020.04Cn0nFourier Transform of f(t) gives:12N 12N  .2512NF  0tf t( ) ei  td30 20 10 0 10 20 3000.10.20.3F ( )0The magnitude of F() yields the continuous frequency spectrum, and it is obviously of the form of the sampling function. The value of F(0) is A. A plot of |F()| as a function of  does not indicate the magnitude of the voltage present at any given frequency. What is it, then? Examination of F   shows that, if f(t) is a voltage waveform, then F   is dimensionally "volts per unit frequency," a concept that may be strange to most of us.Frequency Spectrum of Signalshttp://www.jhu.edu/%7Esignals/fourier2/index.htmlFrequency Spectrum of Signalshttp://www.jhu.edu/%7Esignals/listen/music1.htmlhttp://www.jhu.edu/%7Esignals/phasorlecture2/indexphasorlect2.htmAnalog and Digital SignalsSampling Rate http://www.jhu.edu/%7Esignals/sampling/index.htmlBinary number systemhttp://scholar.hw.ac.uk/site/computing/activity11.aspAnalog-to-Digital Converterhttp://www.astro-med.com/knowledge/adc.htmlhttp://www.maxim-ic.com/design_guides/English/AD_CONVERTERS_21.pdfDigital-to-Analog Converterhttp://www.maxim-ic.com/ADCDACRef.cfmAmplifiersSignal AmplificationDistortionNon-Linear DistortionSymbolsGains – Voltage, Power, CurrentDecibelsAmplifier Power SuppliesEfficiencyVoltage_Gain Av voviPower_Gain Ap load_power PL input_power PI voiovIiICurrent_Gain Ai ioiIApAvAiVoltage_gain_in_decibels 20 log Av  dBColtage_gain_in_decibels 20 log Ai  dBPower_gain_in_decibels 10 log Ap  dBAmplifiersExample 1.1PL40.5 mWPIVirmsIirms PI0.05 mWApPLPI Ap810WWAp10 log 810  Ap29.085 dBPdc10 9.5 10 9.5 Pdc190 mWPdissipatedPdcPI PLPdissipated149.55 mWPLPdc100  21.316 %Av91 Av9 Ii0.0001Av20 log 9  Av19.085 dBIo91000Io9 103 A AiIoIi Ai90AAAi20 log Ai  Ai39.085 dB Vorms92 Iorms92PLVormsIorms Virms12 Iirms0.12An amplifier transfer characteristic that is linear except for output saturation.AmplifiersSaturationAn amplifier transfer characteristic that shows considerable nonlinearity. (b) To obtain linear operation the amplifier is biased as shown, and the signal amplitude is kept small.AmplifiersNon-Linear Transfer Characteristics and BiasingAmplifiersExample 1.2vI0.6 0.61 0.69vovI 10 1011e40 vI0.58 0.6 0.62 0.64 0.66 0.68 0.70510vovI vIvI0.673vIFind vI vo10 1011e40 vIgivenvo5vI0Lplus 10Lplus vo0( )vovI 10 1011e40 vIvI0vI0.69vIFind vI vo10 1011e40 vIgiveninital valuevI0vo0.3Lminus 0.3AmplifiersExample 1.2AmplifiersExample 1.2highlight equation use symbolicsthen differentiate10 1011e40 vI12500000000exp 40 vI 12500000000exp 40 0.673( ) 196.457Circuit Models For AmplifiersVoltage AmplifiersCircuit Models For AmplifiersExample 1.3Circuit Models For AmplifiersExercise 1.8Circuit Models For AmplifiersOther AmplifiersCurrentTransconductanceTransresistanceCircuit Models For AmplifiersExample 1.4Frequency Response of AmplifiersBandwidthSingle-Time Constant Networkshttp://www.clarkson.edu/%7Esvoboda/eta/plots/FOC.htmlhttp://www.clarkson.edu/%7Esvoboda/eta/acWorkout/Switched_RCandRL.htmlFrequency Response of AmplifiersBandwidth(a) Magnitude and (b) phase response of STC networks of the low-pass type.Frequency Response of AmplifiersBandwidthFrequency Response of AmplifiersFrequency Response of AmplifiersBandwidth(a) Magnitude and (b) phase response of STC networks of the high-pass type.Frequency Response of AmplifiersFrequency Response of AmplifiersExample 1.5Frequency


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