Edit distance on real signals

returns
the Edit Distance on Real Signals between sequences `dist`

= edr(`x`

,`y`

,`tol`

)`x`

and `y`

. `edr`

returns
the minimum number of elements that must be removed from `x`

, `y`

,
or both `x`

and `y`

, so that
the sum of Euclidean distances between the remaining signal elements
lies within the specified tolerance, `tol`

.

`[___] = edr(___,`

specifies
the distance metric to use in addition to any of the input arguments
in previous syntaxes. `metric`

)`metric`

can be one of `'euclidean'`

, `'absolute'`

, `'squared'`

,
or `'symmkl'`

.

`edr(___)`

without output arguments
plots the original and aligned signals.

If the signals are real vectors, the function displays the two original signals on a subplot and the aligned signals in a subplot below the first one.

If the signals are complex vectors, the function displays the original and aligned signals in three-dimensional plots.

If the signals are real matrices, the function uses

`imagesc`

to display the original and aligned signals.If the signals are complex matrices, the function plots their real and imaginary parts in the top and bottom half of each image.

[1] Chen, Lei, M. Tamer Özsu, and Vincent Oria. “Robust
and Fast Similarity Search for Moving Object Trajectories.” *Proceedings
of 24th ACM International Conference on Management of Data (SIGMOD
‘05)*. 2005, pp. 491–502.

[2] Sakoe, Hiroaki, and Seibi Chiba. “Dynamic Programming
Algorithm Optimization for Spoken Word Recognition.” *IEEE ^{®} Transactions
on Acoustics, Speech, and Signal Processing*. Vol. ASSP-26,
No. 1, 1978, pp. 43–49.

[3] Paliwal, K. K., Anant Agarwal, and Sarvajit
S. Sinha. “A Modification over Sakoe and Chiba’s Dynamic
Time Warping Algorithm for Isolated Word Recognition.” *Signal
Processing*. Vol. 4, 1982, pp. 329–333.

`alignsignals`

| `dtw`

| `finddelay`

| `findsignal`

| `xcorr`