You are here : matlab → Signal Processing → falltime
# falltime() - Signal Processing

### Syntax

### Example

### Output / Return Value

### Limitations

### Alternatives / See Also

### Reference

F = falltime(X) returns a vector, F, containing the time each transition of the bilevel waveform, X, takes to cross from the 90% to 10% reference levels. See Percent Reference Levels. To determine the transitions, falltime estimates the state levels of the input waveform by a histogram method. falltime identifies all regions, which cross the lower-state boundary of the high state and the upper-state boundary of the low state. The low-state and high-state boundaries are expressed as the state level plus or minus a multiple of the difference between the state levels. See State-Level Tolerances. Because falltime uses interpolation, F may contain values that do not correspond to sampling instants of the bilevel waveform, X.F = falltime(X,FS) specifies the sampling frequency in hertz. The sampling frequency determines the sample instants corresponding to the elements in X. The first sample instant in X corresponds to t=0. Because falltime uses interpolation, F may contain values that do not correspond to sampling instants of the bilevel waveform, X.F = falltime(X,T) specifies the sample instants, T, as a vector with the same number of elements as X.[F,LT,UT] = falltime(...) returns vectors, LT and UT, whose elements correspond to the time instants where X crosses the lower and upper percent reference levels.[F,LT,UT,LL,UL] = falltime(...) returns the levels, LL and UL, corresponding to the lower- and upper-percent reference levels.[...] = falltime(...,Name,Value) returns the fall times with additional options specified by one or more Name,Value pair arguments. falltime(...) plots the signal and darkens the regions of each transition where fall time is computed. The plot marks the lower and upper crossings and the associated reference levels. The state levels and the associated lower- and upper-state boundaries are also displayed.

F = falltime(X)F = falltime(X,FS)F = falltime(X,T)[F,LT,UT] = falltime(...)[F,LT,UT,LL,UL] = falltime(...)[...] = falltime(...,Name,Value) falltime(...)

Fall Time of Bilevel WaveformOpen This Example Determine the fall time in samples for a 2.3 V clock waveform. Load the 2.3 V clock data. Determine the fall time in samples. Use the default 10% and 90% percent reference levels. Plot the waveform and annotate the fall time.load('negtransitionex.mat','x') falltime(x) ans = 0.7200 Fall Time with 20% and 80% Reference LevelsOpen This Example Determine the fall time in a 2.3 V clock waveform sampled at 4 MHz. Compute the fall time using the 20% and 80% reference levels. Load the 2.3 V clock data with sampling instants. Determine the fall time using 20% and 80% reference levels. Plot the waveform and annotate the fall time.load('negtransitionex.mat','x','t') falltime(x,'PercentReferenceLevels',[20 80]) ans = 0.5400 Falltime, Reference-Level Instants, and Reference LevelsOpen This Example Determine the fall time, reference-level instants, and reference levels in a 2.3 V clock waveform sampled at 4 MHz. Load the 2.3 V clock waveform along with the sampling instants.load('negtransitionex.mat','x','t') Determine the fall time, reference-level instants, and reference levels.[f,lt,ut,ll,ul] = falltime(x,t); Plot the waveform with the upper and lower reference levels and reference level instants. Show that the fall time is the difference between the lower- and upper-reference level instants.plot(t,x) xlabel('seconds') ylabel('Volts') hold on plot([lt ut],[ll ul],'ro') hold off fprintf('Rise time is %g seconds.',lt-ut) Rise time is 1.8e-07 seconds.