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Discrimination of Metal Differences Using Electromagnetic
Discrimination of Metal Differences Using Electromagnetic

... A frequent misconception is that when a comparator is set up to sort for a particular difference, that difference is all that is sorted. In actuality, the comparator is set up on a particular piece with specific characteristics and any deviation from those characteristics will be detected. For examp ...
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... using the phasor calculations as in Serway’s Chapter 33. The expression ωL and 1/ωC are known as the inductive reactance and capacitive reactance, respectively; using dimensional analysis, you should be able to show that each has units of Ohms. At the frequency where the inductive and capacitive rea ...
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... • The default symbol for √-1 is i. However, MatLAB does recognize that j is equivalent to i. – The coefficient of the imaginary number must be placed before the ‘i’ or ‘j’. • If you typed c = 2-3j, MatLAB interprets it as ...
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... For example, if we choose C = 1·5nF and R2 = 10k this gives R1 = (about) 5k for a frequency of 40kHz. We should therefore use a 10k variable resistor for R1. This will allow us to set the frequency to exactly 40kHz. For stability of frequency, a voltage regulator is recommended (the vero diagram bel ...
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AN1882 The NE568A as a wideband FM modulator

... A linearizing DC bias current is fed into Pin 17 through an RF choke and series resistor RIN as shown in Figure 4. This reduces the harmonic content of the output signal while also increasing its amplitude. The AC modulator output signal appears on Pins 19 and 20 superimposed on a DC common mode vol ...
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Description of a Function Generator Instrument A function generator

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Edelstein, Hutchison et al (1980)

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Key_P1 - Weber State University

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Lesson 6 – Applications

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Chirp spectrum



The spectrum of a chirp pulse describes its characteristics in terms of its frequency components. This frequency-domain representation is an alternative to the more familiar time-domain waveform, and the two versions are mathematically related by the Fourier transform. The spectrum is of particular interest when pulses are subject to signal processing. For example, when a chirp pulse is compressed by its matched filter, the resulting waveform contains not only a main narrow pulse but, also, a variety of unwanted artifacts many of which are directly attributable to features in the chirp's spectral characteristics. The simplest way to derive the spectrum of a chirp, now computers are widely available, is to sample the time-domain waveform at a frequency well above the Nyquist limit and call up an FFT algorithm to obtain the desired result. As this approach was not an option for the early designers, they resorted to analytic analysis, where possible, or to graphical or approximation methods, otherwise. These early methods still remain helpful, however, as they give additional insight into the behavior and properties of chirps.
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