Chapter 1. Electronics and Semiconductors
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1 Chapter 1. Electronics and Semiconductors Tong In Oh 1
2 Objective Understanding electrical signals Thevenin and Norton representations of signal sources Representation of a signal as the sum of sine waves Analog and digital representations of a signal Signal amplification (amplifier) 2
3 Introduction Microelectronics Based on the integrated-circuit (IC) technology Contain billions of components in a small piece of silicon Equal to a complete digital computer (microcomputer, microprocessor) Shall study Electronic devices in the discrete circuits / components of an integrated circuits Design and analysis of interconnections of these devices Available IC chips and their applications In this Chapter 1 Basic concepts and terminology Signal/signal-processing(signal amplification) Circuit representations or models for linear amplifiers Design and analysis of electronic circuits Properties and physics of semiconductors Monolithic circuit/crystal structure of semiconductors/electron/hole/doping/carrier drift/carrier diffusion/pn junction 3
4 1.1 Signals Contain information (patient monitor, voice of a radio announcer, etc) To extract required information from a set of signals Need to process the signals in predetermined manner Signal processing performed by electronic systems Transducer: convert the various forms of physical signals to electrical signals Two types of signal sources Thevenin form / Norton form v s t = R s i s (t) Figure 1.1 Two alternative representations of a signal source: (a) the Thévenin form; (b) the Norton form. 4
5 Time-varying quantity Represented by the changes in its magnitude as time progresses Difficult to characterize of describe succinctly for signal-processing 5
6 1.2 Frequency Spectrum of Signals Extremely useful characterization of a signal Obtained through the mathematical tools Fourier series/fourier transform: representing a voltage or current signal as the sum of sine-wave signals of different frequencies and amplitudes v a t = V a sin ωt + θ V a : peak value, amplitude ω: angular frequency (radians/second) ω = 2πf rad/s f: frequency in hertz f = 1/T Hz T: period in seconds θ: phase Sine-wave is characterized by its peak value(v a )/frequency(f)/phase(θ) Magnitude of signal: root-mean-square (rms) value (V a / 2) 6
7 Fourier series: Representation of signals as the sum of sinusoids In the special case for a periodic function of time Fourier transform: Obtain the frequency spectrum of a signal In general case for an arbitrary function of time Ex) expressed a given periodic function of time as the sum of an infinite number of harmonic sinusoids v t = 4V π (sin ω 0t sin 3ω 0t sin 5ω 0t + ) V: amplitude of the square wave ω 0 : fundamental frequency Figure 1.5 A symmetrical square-wave signal of amplitude V. 7 Figure 1.6 The frequency spectrum (also known as the line spectrum) of the periodic square wave of Fig. 1.5.
8 Matlab Code for Fourier Series 8
9 For a nonperiodic function of time, Frequency spectrum as a continuous function of frequency Signal representation Time-domain representation (v a t ): waveform varies with time Frequency-domain representation (V a ω ): frequency spectrum Figure 1.7 The frequency spectrum of an arbitrary waveform such as that in Fig
10 Matlab Code for Fourier Transform 10
11 Homework Example 1.1 Summary of Thevenin and Norton s theorem Summary of Fourier series/fourier transform Recommendation Running Matlab code 11
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