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It is usually a combination of a Bode magnitude plot, expressing the magnitude (usually in decibels) of the frequency response, and a Bode phase plot, expressing the phase shift. As originally conceived by Hendrik Wade Bode in the 1930s, the plot is an asymptotic approximation of the frequency response, using straight line segments .
Magnitude transfer function of a bandpass filter with lower 3 dB cutoff frequency f 1 and upper 3 dB cutoff frequency f 2 Bode plot (a logarithmic frequency response plot) of any first-order low-pass filter with a normalized cutoff frequency at =1 and a unity gain (0 dB) passband.
Magnitude response of a low pass filter with 6 dB per octave or 20 dB per decade roll-off. Measuring the frequency response typically involves exciting the system with an input signal and measuring the resulting output signal, calculating the frequency spectra of the two signals (for example, using the fast Fourier transform for discrete signals), and comparing the spectra to isolate the ...
Bode plot A plot of the amplitude and phase frequency response of a system, where the actual response is approximated by straight line segments. Boolean algebra (logic) A type of algebra that deals with values that can only hold values "true" and "false", of great use in design and analysis of digital systems. boost converter
A Bode plot of displacements in the system with (red) and without (blue) the 10% tuned mass. The Bode plot is more complex, showing the phase and magnitude of the motion of each mass, for the two cases, relative to F 1. In the plots at right, the black line shows the baseline response (m 2 = 0).
Bode's sensitivity integral, discovered by Hendrik Wade Bode, is a formula that quantifies some of the limitations in feedback control of linear parameter invariant systems. Let L be the loop transfer function and S be the sensitivity function .
The coherence (sometimes called magnitude-squared coherence) between two signals x(t) and y(t) is a real-valued function that is defined as: [1] [2] = | | ()where G xy (f) is the Cross-spectral density between x and y, and G xx (f) and G yy (f) the auto spectral density of x and y respectively.
The internal state variables are the smallest possible subset of system variables that can represent the entire state of the system at any given time. [13] The minimum number of state variables required to represent a given system, , is usually equal to the order of the system's defining differential equation, but not necessarily.