Papers by DheeraJ Krishna Govada
Overview 1. Classification of waveform shapes: we can broadly divide waveforms into the classes p... more Overview 1. Classification of waveform shapes: we can broadly divide waveforms into the classes periodic (repeat in time) and aperiodic (don't repeat in time). The first class seem to have some kind of "pitch" associated with them and can be subdivided into simple (sinusoidal) and complex (non-sinusoidal) waveforms. The aperiodic class can be subdivided into impulsive (occur once) and noise (continuous but random) waveforms. 2. Periodic waveforms: Simple periodic waveforms (sinewaves) arise from perfect (undamped) simple resonating systems. They can be characterised by their period (or their frequency), amplitude and phase. Complex periodic waveforms (periodic but not sinusoidal in shape) arise from all other repetitively vibrating systems. We can readily characterise the amplitude of complex periodic waveforms and their repetition frequency, but it is hard to see how we might characterise their shape. 3. Measurement of Waveform Shape: to measure the shape of a waveform we use the method of Fourier analysis. Fourier showed that it is possible to build any waveform shape by adding together simple periodic waveforms of the appropriate frequency, amplitude and phase (see figure 1-4.1). Thus we can quantify the shape of a waveform by listing the component sinewaves needed to make it. For complex periodic waveforms, Fourier analysis gives particularly simple results. In this case we find that the only component sinewaves needed occur at frequencies that are whole number multiples of the repetition frequency of the complex. This is because each component sinewave must complete a whole number of cycles per period T of the complex (otherwise the sum would not be periodic in T). Since such component sinewaves have such a special role in the analysis of complex periodic waveforms, they are given the special name of harmonics. Harmonics are the sinusoidal components of a complex periodic waveform which occur at frequencies that are whole number multiples of the repetition frequency. Because of its special role in defining harmonics, the repetition frequency is also known as the fundamental frequency. 4. Amplitude Spectrum: Fourier analysis is the process of finding which sinewaves need to be added together to make a particular waveform shape. Although we could write down the results of Fourier analysis as a formula, it is often more convenient to plot the results of Fourier analysis on a graph called a spectrum (see figure 1-4.2) The horizontal axis of a spectrum tells you the frequency of the component sinusoids of a signal, while the vertical axis tells you how much of that frequency is present. Typically the phase of the components is not plotted. On a spectrum, individual harmonics are seen as vertical lines at the corresponding frequency. Fourier analysis can also be applied to aperiodic signals, and is then often just called spectral analysis: i.e. analysis that calculates a spectrum. Our sensation of timbre seems to be closely related to the spectral content of the sound signal.
Prof. Dr. Chitralekha MahantaIndian Institute of Technology, Guwahati
BJT Small Signal Analysis
In the last classes we have seen how biasing of the transistor is done ... more BJT Small Signal Analysis
In the last classes we have seen how biasing of the transistor is done and we were considering different biasing schemes. All these biasing schemes are basically for using the transistor as an amplifier for faithful amplification of an input signal. Today we will discuss about the transistor being used as an amplifier and to understand the operation of the transistor as an amplifier we have to first understand the analysis of the BJT when a small signal is applied. So small signal analysis of a BJT will be discussed today. The small signal means the magnitude of the AC signal which is applied should be small enough to keep the transistor still in the active region of operation because we want the transistor to operate in the active region. Only then the transistor will be able to faithfully amplify an AC input signal. If that signal amplitude is very high then it is seen that the transistor will be driven into either saturation or cut off region because when you have very large signal at the input then the base current signal will be having a high magnitude. Peak to peak value of the base current will be high.
IEEE SOLID STATE FOR VLSI
Advanced Reliable Systems (ARES) Laboratory
Department of Electrical Engineering
generation and recombination of excess
carriers in a semiconductor
the structure of two MOS Field-Effect-Transistors
(FETs) that are building blocks for all digital... more the structure of two MOS Field-Effect-Transistors
(FETs) that are building blocks for all digital devices.
The nMOS transistor shown in Figure 2.1 (n-type, n-channel,
enhancement mode field-effect transistor) is built on the p-type
semiconductor substrate, which is usually acceptor-doped silicon
Subsystem Design and Layout For Mtech in VLSI TECHNOLOGY & PROCESS MODELLING.
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Papers by DheeraJ Krishna Govada
In the last classes we have seen how biasing of the transistor is done and we were considering different biasing schemes. All these biasing schemes are basically for using the transistor as an amplifier for faithful amplification of an input signal. Today we will discuss about the transistor being used as an amplifier and to understand the operation of the transistor as an amplifier we have to first understand the analysis of the BJT when a small signal is applied. So small signal analysis of a BJT will be discussed today. The small signal means the magnitude of the AC signal which is applied should be small enough to keep the transistor still in the active region of operation because we want the transistor to operate in the active region. Only then the transistor will be able to faithfully amplify an AC input signal. If that signal amplitude is very high then it is seen that the transistor will be driven into either saturation or cut off region because when you have very large signal at the input then the base current signal will be having a high magnitude. Peak to peak value of the base current will be high.
(FETs) that are building blocks for all digital devices.
The nMOS transistor shown in Figure 2.1 (n-type, n-channel,
enhancement mode field-effect transistor) is built on the p-type
semiconductor substrate, which is usually acceptor-doped silicon