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The '''method of reassignment''' is a technique for
{{New Testament manuscript infobox
sharpening a [[time-frequency representation]] by mapping
| form  = Papyrus
the data to time-frequency coordinates that are nearer to
| number = <math>\mathfrak{P}</math><sup>115</sup>
the true [[Support (mathematics)|region of support]] of the
| image  = 666.jpg
analyzed signal. The method has been independently
| isize  =
introduced by several parties under various names, including
| caption= Red arrow points to χιϛ (616), "number of the beast" in '''P'''<sup>115</sup>
''method of reassignment'', ''remapping'', ''time-frequency reassignment'',
| name  = [[Oxyrhynchus papyri|P. Oxy.]] 4499
and ''modified moving-window method''.<ref name="hainsworth">{{Cite thesis |type=PhD |chapter=Chapter 3: Reassignment methods |title=Techniques for the Automated Analysis of Musical Audio |url=http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.5.9579 |last=Hainsworth  |first=Stephen |year=2003 |publisher=University of Cambridge |accessdate= |docket= |oclc= }}</ref> In
| text  = [[Book of Revelation|Rev]] 2-3, 5-6, 8-15
the case of the [[spectrogram]] or the [[short-time Fourier transform]],
| date  = c. 275
the method of reassignment sharpens blurry
| found  = [[Oxyrhynchus]], [[Egypt]]
time-frequency data by relocating the data according to
| now at = [[Ashmolean Museum]]
local estimates of instantaneous frequency and group delay.
| cite  = Juan Chapa, ''Oxyrynchus Papyri'' 66:11-39. (#4499)
This mapping to reassigned time-frequency coordinates is
| size  = 26 fragments; 15.5 x 23.5 cm; 33-36 lines/page
very precise for signals that are separable in time and
| type  = [[Alexandrian text-type|Alexandrian]], close agreement with '''[[Codex Alexandrinus|A]]''' & '''[[Codex Ephraemi Rescriptus|C]]'''
frequency with respect to the analysis window.
| cat    = I
| hand  =  
| note  = Gives [[number of the beast]] as 6'''1'''6
}}
'''Papyrus 115''' (''P. Oxy.'' 4499, designated by <math>\mathfrak{P}</math><sup>115</sup> in the [[Biblical manuscript#Gregory-Aland|Gregory-Aland]] numbering) is a fragmented [[Biblical manuscript|manuscript]] of the [[New Testament]] written in [[Greek language|Greek]] on [[papyrus]]. It consists of 12 fragments of a [[codex]] containing parts of the [[Book of Revelation]]. It dates to the 3rd century, ca. 225-275 AD.<ref>Juan Chapa, ''Oxy. Pap.,'' 66:11-39, no. 4499</ref> [[Bernard Pyne Grenfell|Grenfell]] and [[Arthur Surridge Hunt|Hunt]] discovered the papyrus at [[Oxyrhynchus|Oxyrhynchus, Egypt]].


== Introduction ==
<math>\mathfrak{P}</math><sup>115</sup> was not deciphered and published until the end of the 20th century. It is currently housed at the [[Ashmolean Museum]].<ref name = INTF>{{Cite web|url=http://intf.uni-muenster.de/vmr/NTVMR/ListeHandschriften.php?ObjID=10115|title= Liste Handschriften|publisher=Institute for New Testament Textual Research|accessdate=27 August 2011|location=Münster}}</ref>


[[Image:Reassigned spectrogral surface of bass pluck.png|thumb|400px|
== Description ==
Reassigned spectral surface for the onset of an acoustic bass tone
The original codex had 33-36 lines per page of 15.5&nbsp;cm by 23.5&nbsp;cm. The surviving text includes 2:1-3, 13-15, 27-29; 3:10-12; 5:8-9; 6:5-6; 8:3-8, 11-13; 9:1-5, 7-16, 18-21; 10:1-4, 8-11; 11:1-5, 8-15, 18-19; 12:1-5, 8-10, 12-17; 13:1-3, 6-16, 18; 14:1-3, 5-7, 10-11, 14-15, 18-20; 15:1, 4-7.<ref>{{Cite book
having a sharp pluck and a fundamental frequency of approximately 73.4&nbsp;Hz.
| last = Comfort
Sharp spectral ridges representing the harmonics are evident, as is the
| first = Philip W.
abrupt onset of the tone.
| authorlink = Philip Comfort
The spectrogram was computed using a 65.7 ms Kaiser window with a shaping
| author2 = David P. Barrett
parameter of 12.]]
| title = The Text of the Earliest New Testament Greek Manuscripts
| publisher = Tyndale House Publishers
| year = 2001
| location = Wheaton, Illinois
| pages = 664–677
| url =
| isbn = 978-0-8423-5265-9}}</ref>


Many signals of interest have a distribution of energy that
The [[nomina sacra]] are written in an abbreviated way: <span style="text-decoration: overline">ΙΗΛ</span> <span style="text-decoration: overline">ΑΥΤΟΥ</span> <span style="text-decoration: overline">ΠΡΣ</span> <span style="text-decoration: overline">ΘΩ</span> <span style="text-decoration: overline">ΘΥ</span> <span style="text-decoration: overline">ΑΝΩΝ</span> <span style="text-decoration: overline">ΠΝΑ</span> <span style="text-decoration: overline">ΟΥΝΟΥ</span> <span style="text-decoration: overline">ΟΥΝΟΝ</span> <span style="text-decoration: overline">ΚΥ</span> <span style="text-decoration: overline">ΘΝ</span> <span style="text-decoration: overline">ΑΝΟΥ</span> <span style="text-decoration: overline">ΟΥΝΩ</span>.
varies in time and frequency. For example, any sound signal
having a beginning or an end has an energy distribution that
varies in time, and most sounds exhibit considerable
variation in both time and frequency over their duration.
Time-frequency representations  are commonly used to analyze
or characterize such signals. They map the one-dimensional
time-domain signal into a two-dimensional function of time
and frequency. A time-frequency representation describes the
variation of spectral energy distribution over time, much as
a musical score describes the variation of musical pitch
over time.


In audio signal analysis, the spectrogram is the most
The text-type is the [[Alexandrian text-type|Alexandrian]]. <math>\mathfrak{P}</math><sup>115</sup> follows the text of [[Codex Alexandrinus]] ('''A''') and [[Codex Ephraemi Rescriptus]] ('''C''').<ref name = Comfort>Philip W. Comfort, ''Encountering the Manuscripts. An Introduction to New Testament Paleography & Textual Criticism'', Nashville, Tennessee: Broadman & Holman Publishers, 2005, p. 77.</ref>
commonly used time-frequency representation, probably
because it is well-understood, and immune to so-called
"cross-terms" that sometimes make other time-frequency
representations difficult to interpret. But the windowing
operation required in spectrogram computation introduces an
unsavory tradeoff between time resolution and frequency
resolution, so spectrograms provide a time-frequency
representation that is blurred in time, in frequency, or in
both dimensions. The method of time-frequency reassignment
is a technique for refocussing time-frequency data in a
blurred representation like the spectrogram by mapping the
data to time-frequency coordinates that are nearer to the
true region of support of the analyzed signal.


== The spectrogram as a time-frequency representation ==
An interesting textual variant of '''P'''<sup>115</sup> is that it gives the [[number of the beast]] as 616 ([[Chi (letter)|chi]], [[Iota (letter)|iota]], [[Stigma (letter)|stigma]] (ΧΙϚ)), rather than the majority reading of [[666 (number)|666]] (chi, xi, stigma (ΧΞϚ)), as does [[Codex Ephraemi Rescriptus]].


One of the best-known time-frequency representations is the
== See also ==
spectrogram, defined as the squared magnitude of the
* [[List of New Testament papyri]]
short-time Fourier transform. Though the short-time phase
* [[Oxyrhynchus papyri]]
spectrum is known to contain important temporal information
* [[Stigma (letter)]]
about the signal, this information is difficult to
interpret, so typically, only the short-time magnitude
spectrum is considered in short-time spectral analysis.
 
As a time-frequency representation, the spectrogram has
relatively poor resolution. Time and frequency resolution
are governed by the choice of analysis window and greater
concentration in one domain is accompanied by greater
smearing in the other.
 
A time-frequency representation having improved resolution,
relative to the spectrogram, is the [[Wigner&ndash;Ville distribution]],
which may be interpreted as a short-time
Fourier transform with a window function that is perfectly
matched to the signal. The Wigner&ndash;Ville distribution is
highly concentrated in time and frequency, but it is also
highly nonlinear and non-local. Consequently, this
distribution is very sensitive to noise, and generates
cross-components that often mask the components of interest,
making it difficult to extract useful information concerning
the distribution of energy in multi-component signals.
 
[[Cohen's class distribution function|Cohen's class]] of
bilinear time-frequency representations is a class of
"smoothed" Wigner&ndash;Ville distributions, employing a smoothing
kernel that can reduce sensitivity of the distribution to
noise and suppresses cross-components, at the expense of
smearing the distribution in time and frequency. This
smearing causes the distribution to be non-zero in regions
where the true Wigner&ndash;Ville distribution shows no energy.
 
The spectrogram is a member of Cohen's class. It is a
smoothed Wigner&ndash;Ville distribution with the smoothing kernel
equal to the Wigner&ndash;Ville distribution of the analysis
window. The method of reassignment smoothes the Wigner&ndash;Ville
distribution, but then refocuses the distribution back to
the true regions of support of the signal components. The
method has been shown to reduce time and frequency smearing
of any member of Cohen's class
<ref name = "improving">
{{cite journal |author=F. Auger and P. Flandrin |date=May 1995 |title=Improving the readability of time-frequency and
time-scale representations by the reassignment method |journal=IEEE Transactions on Signal Processing |volume=43 |issue=5 |pages=1068–1089 |publisher= |doi=10.1109/78.382394 |url= |accessdate= }}
</ref>
.<ref>P. Flandrin, F. Auger, and E. Chassande-Mottin,
''Time-frequency reassignment: From principles to algorithms'',
in Applications in Time-Frequency Signal Processing
(A. Papandreou-Suppappola, ed.), ch. 5, pp. 179 – 203, CRC Press, 2003.</ref>
In the case of the reassigned
spectrogram, the short-time phase spectrum is used to
correct the nominal time and frequency coordinates of the
spectral data, and map it back nearer to the true regions of
support of the analyzed signal.
 
== The method of reassignment ==
 
Pioneering work on the method of reassignment was
published by Kodera, Gendrin, and de Villedary under the
name of ''Modified Moving Window Method''
<ref>
{{cite journal |author=K. Kodera, R. Gendrin, and C. de Villedary |date=Feb 1978 |title=Analysis of time-varying signals with small BT values |journal=IEEE Transactions on Acoustics, Speech and Signal Processing |volume=26 |issue=1 |pages=64–76  | publisher= |doi=10.1109/TASSP.1978.1163047 |url= |accessdate= }}
</ref>
Their technique enhances the resolution in time and
frequency of the classical Moving Window Method (equivalent
to the spectrogram) by assigning to each data point a new
time-frequency coordinate that better-reflects the
distribution of energy in the analyzed signal.
 
In the classical moving window method, a  time-domain
signal, <math>x(t)</math> is decomposed into a set of
coefficients, <math>\epsilon( t, \omega )</math>, based on a set of elementary signals, <math>h_{\omega}(t)</math>,
defined
 
<center><math>
h_{\omega}(t) = h(t) e^{j \omega t}
</math></center>
 
where <math>h(t)</math> is a (real-valued) lowpass kernel
function, like the window function in the short-time Fourier
transform. The coefficients in this decomposition are defined
 
<center><math>\begin{align}
\epsilon( t, \omega )
&= \int x(\tau) h( t - \tau ) e^{ -j \omega \left[ \tau - t \right]} d\tau \\
&= e^{ j \omega t}  \int x(\tau) h( t - \tau ) e^{ -j \omega \tau } d\tau \\
&= e^{ j \omega t} X(t, \omega) \\
&= X_{t}(\omega) = M_{t}(\omega) e^{j \phi_{\tau}(\omega)}
\end{align}</math></center>
 
where <math>M_{t}(\omega)</math> is the magnitude, and
<math>\phi_{\tau}(\omega)</math> the phase, of
<math>X_{t}(\omega)</math>, the Fourier transform of the
signal <math>x(t)</math> shifted in time by <math>t</math>
and windowed by <math>h(t)</math>.
 
<math>x(t)</math> can be reconstructed from the moving window coefficients by
 
<center><math>\begin{align}
x(t)  & = \iint X_{\tau}(\omega) h^{*}_{\omega}(\tau - t) d\omega d\tau \\
  & = \iint X_{\tau}(\omega) h( \tau - t ) e^{ -j \omega \left[ \tau - t \right]}  d\omega d\tau \\
&= \iint M_{\tau}(\omega) e^{j \phi_{\tau}(\omega)} h( \tau - t ) e^{ -j \omega \left[ \tau - t \right]}  d\omega d\tau \\
&= \iint M_{\tau}(\omega) h( \tau - t ) e^{ j \left[ \phi_{\tau}(\omega) - \omega \tau+ \omega t \right] } d\omega d\tau
\end{align}</math></center>
 
For signals having magnitude spectra,
<math>M(t,\omega)</math>, whose time variation is slow
relative to the phase variation, the maximum contribution to
the reconstruction integral comes from the vicinity of the
point <math>t,\omega</math> satisfying the phase
stationarity condition
 
<center><math>\begin{matrix}
\frac{\partial}{\partial \omega} \left[ \phi_{\tau}(\omega) - \omega \tau +  \omega t\right] & = 0 \\
\frac{\partial}{\partial \tau} \left[ \phi_{\tau}(\omega) - \omega \tau +  \omega t \right] & = 0
\end{matrix}</math></center>
 
or equivalently, around the point <math>\hat{t}, \hat{\omega}</math>  defined by
 
<center><math>\begin{align}
\hat{t}(\tau, \omega) & = \tau -  \frac{\partial \phi_{\tau}(\omega)}{\partial \omega} =
-  \frac{\partial \phi(\tau, \omega)}{\partial \omega} \\
\hat{\omega}(\tau, \omega) & = \frac{\partial \phi_{\tau}(\omega)}{\partial \tau} =
\omega + \frac{\partial \phi(\tau, \omega)}{\partial \tau} .
\end{align}</math></center>
 
This phenomenon is known in such fields as optics as the
[[stationary phase approximation|principle of stationary phase]],
which states that for periodic or quasi-periodic
signals, the variation of the Fourier phase spectrum not
attributable to periodic oscillation is slow with respect to
time in the vicinity of the frequency of oscillation, and in
surrounding regions the variation is relatively rapid.
Analogously, for impulsive signals, that are concentrated in
time, the variation of the phase spectrum is slow with
respect to frequency near the time of the impulse, and in
surrounding regions the variation is relatively rapid.
 
In reconstruction, positive and negative contributions to
the synthesized waveform cancel, due to destructive
interference, in frequency regions of rapid phase variation.
Only regions of slow phase variation (stationary phase) will
contribute significantly to the reconstruction, and the
maximum contribution (center of gravity) occurs at the point
where the phase is changing most slowly with respect to time
and frequency.
 
The time-frequency coordinates thus computed are equal to
the local group delay, <math>\hat{t}_{g}(t,\omega)</math>,
and local instantaneous frequency, <math>\hat{\omega}
_{i}(t,\omega)</math>, and are computed from the phase of
the short-time Fourier transform, which is normally ignored
when constructing the spectrogram. These quantities are
''local'' in the sense that they represent a windowed
and filtered signal that is localized in time and frequency,
and are not global properties of the signal under analysis.
 
The modified moving window method, or method of
reassignment, changes (reassigns) the point of attribution
of <math>\epsilon(t,\omega)</math> to this point of maximum
contribution <math>\hat{t}(t,\omega),
\hat{\omega}(t,\omega)</math>, rather than to the point
<math>t,\omega</math> at which it is computed. This point is
sometimes called the ''center of gravity'' of the
distribution, by way of analogy to a mass distribution. This
analogy is a useful reminder that the attribution of
spectral energy to the center of gravity of its distribution
only makes sense when there is energy to attribute, so the
method of reassignment has no meaning at points where the
spectrogram is zero-valued.
 
== Efficient computation of reassigned times and frequencies ==
 
In digital signal processing, it is most common to sample
the time and frequency domains. The discrete Fourier
transform is used to compute samples <math>X(k)</math> of
the Fourier transform from samples <math>x(n)</math> of a
time domain signal. The reassignment operations proposed by
Kodera ''et al.''  cannot be applied directly to the
discrete short-time Fourier transform data, because partial
derivatives cannot be computed directly on data that is
discrete in time and frequency, and it has been suggested
that this difficulty has been the primary barrier to wider
use of the method of reassignment.
 
It is possible to approximate the partial derivatives using
finite differences. For example, the phase spectrum can be
evaluated at two nearby times, and the partial derivative
with respect to time be approximated as the difference
between the two values divided by the time difference, as in
 
<center><math>\begin{matrix}
\frac{\partial \phi(t, \omega)}{\partial t} & \approx
\frac{1}{\Delta t}  \left[ \phi(t + \frac{\Delta t}{2}, \omega) - \phi(t - \frac{\Delta t}{2}, \omega) \right] \\
\frac{\partial \phi(t, \omega)}{\partial \omega} & \approx
\frac{1}{\Delta \omega}
  \left[ \phi(t, \omega+ \frac{\Delta \omega}{2}) - \phi(t, \omega-\frac{\Delta \omega}{2}) \right]
\end{matrix}</math></center>
 
For sufficiently small values of <math>\Delta t</math> and
<math>\Delta \omega</math>, and provided that the phase
difference is appropriately "unwrapped", this
finite-difference method yields good approximations to the
partial derivatives of phase, because in regions of the
spectrum in which the evolution of the phase is dominated by
rotation due to sinusoidal oscillation of a single, nearby
component, the phase is a linear function.
 
Independently of Kodera ''et al.'', Nelson arrived at a similar method for
improving the time-frequency precision of short-time
spectral data  from partial derivatives of the short-time phase
spectrum.
<ref name = "crossspectral">
{{cite journal |author=D. J. Nelson |date=Nov 2001 |title=Cross-spectral methods for processing speech |journal=Journal of the Acoustical Society of America |volume=110 |issue=5 |pages=2575–2592 |publisher= |doi=10.1121/1.1402616 |url= |accessdate= }}
</ref>
It is easily shown that Nelson's
''cross spectral surfaces'' compute an approximation of the derivatives that
is equivalent to the finite differences method.
 
Auger and Flandrin showed that the method of reassignment, proposed
in the context of the spectrogram by Kodera ''et al.'', could be extended to
any member of [[Cohen's class]] of time-frequency representations by generalizing the
reassignment operations to
 
<center><math>\begin{matrix}
\hat{t} (t,\omega) & = t -
\frac{\iint \tau \cdot W_{x}(t-\tau,\omega -\nu) \cdot \Phi(\tau,\nu) d\tau d\nu}
{\iint W_{x}(t-\tau,\omega -\nu) \cdot \Phi(\tau,\nu) d\tau d\nu } \\
\hat{\omega} (t,\omega) & = \omega -
\frac{\iint \nu \cdot W_{x}(t-\tau,\omega -\nu) \cdot \Phi(\tau,\nu) d\tau d\nu}
{\iint W_{x}(t-\tau,\omega -\nu) \cdot \Phi(\tau,\nu) d\tau d\nu}
\end{matrix}</math></center>
 
where <math>W_{x}(t,\omega)</math> is the Wigner&ndash;Ville
distribution of <math>x(t)</math>, and
<math>\Phi(t,\omega)</math> is the kernel function that
defines the distribution. They further described an
efficient method for computing the times and frequencies for
the reassigned spectrogram efficiently and accurately
without explicitly computing the partial derivatives of
phase.
<ref name = "improving" />
 
In the case of the spectrogram, the reassignment operations
can be computed by
 
<center><math>\begin{matrix}
\hat{t} (t,\omega) & = t - \Re \Bigg\{ \frac{ X_{\mathcal{T}h}(t,\omega) \cdot X^*(t,\omega) }
{ | X(t,\omega) |^2 } \Bigg\}  \\
\hat{\omega}(t,\omega) & = \omega + \Im \Bigg\{ \frac{ X_{\mathcal{D}h}(t,\omega) \cdot X^*(t,\omega) }
{ | X(t,\omega) |^2 } \Bigg\} 
\end{matrix}</math></center>
 
where <math>X(t,\omega)</math> is the short-time Fourier
transform computed using an analysis window
<math>h(t)</math>, <math>X_{\mathcal{T}h}(t,\omega)</math>
is the short-time Fourier transform computed using a
time-weighted anlaysis window <math>h_{\mathcal{T}}(t) = t
\cdot h(t)</math> and
<math>X_{\mathcal{D}h}(t,\omega)</math> is the short-time
Fourier transform computed using a time-derivative analysis
window <math>h_{\mathcal{D}}(t) = \frac{d}{dt}h(t)</math>.
 
Using the auxiliary window functions
<math>h_{\mathcal{T}}(t)</math> and
<math>h_{\mathcal{D}}(t)</math>, the reassignment operations
can be computed at any time-frequency coordinate
<math>t,\omega</math> from an algebraic combination of three
Fourier transforms evaluated at <math>t,\omega</math>. Since
these algorithms operate only on short-time spectral
data evaluated at a single time and frequency, and do not
explicitly compute any derivatives, this gives an efficient
method of computing the reassigned discrete short-time
Fourier transform.
 
One constraint in this method of computation is that the <math>| X(t,\omega) |^2</math> must be non-zero. This is not much of a restriction,
since the reassignment operation itself implies that there
is some energy to reassign, and has no meaning when the
distribution is zero-valued.
 
==Separability==
The short-time Fourier transform can often be used to
estimate the amplitudes and phases of the individual
components in a ''multi-component''  signal, such as a
quasi-harmonic musical instrument tone. Moreover, the time
and frequency reassignment operations can be used to sharpen
the representation by attributing the spectral energy
reported by the short-time Fourier transform to the point
that is the local center of gravity of the complex energy
distribution.
 
For a signal consisting of a single component, the
instantaneous frequency can be estimated from the partial
derivatives of phase of any short-time Fourier transform
channel that passes the component. If the signal is to be
decomposed into many components,
 
<center><math>
x(t) = \sum_{n} A_{n}(t) e^{j \theta_{n}(t)}
</math></center>
 
and the instantaneous frequency of each component
is defined as the derivative of its phase with respect to time,
that is,
 
<center><math>
\omega_{n}(t) = \frac{d \theta_{n}(t)}{d t},
</math></center>
 
then the instantaneous frequency of each individual component
can be computed from the phase of the response of a filter that passes
that component, provided that no more than
one component lies in the passband of the filter.
 
This is the property, in the frequency domain, that Nelson
called ''separability''
<ref name = "crossspectral" />
and is required of all signals so analyzed. If this property is not met, then
the desired multi-component decomposition cannot be achieved,
because the parameters of individual components cannot be
estimated from the short-time Fourier transform. In such
cases, a different analysis window must be chosen so that
the separability criterion is satisfied.
 
If the components of a signal are separable in frequency
with respect to a particular short-time spectral analysis
window, then the output of each short-time Fourier transform
filter is a filtered version of, at most, a single
dominant (having significant energy) component, and so the
derivative, with respect to time, of the phase of the
<math>X(t,\omega_{0})</math> is equal to the derivative with
respect to time, of the phase of the dominant component at
<math>\omega_{0}</math>. Therefore, if a component,
<math>x_{n}(t)</math>, having instantaneous frequency
<math>\omega_{n}(t)</math> is the dominant component in the
vicinity of <math>\omega_{0}</math>, then the instantaneous
frequency of that component can be computed from the phase
of the short-time Fourier transform evaluated at
<math>\omega_{0}</math>. That is,
 
<center><math>\begin{matrix}
\omega_{n}(t)
&= \frac{\partial}{\partial t}  \arg\{ x_{n}(t) \} \\
&= \frac{\partial }{\partial t} \arg\{ X(t,\omega_{0}) \}
\end{matrix}</math></center>
 
[[Image:Long-window reassigned spectrogram of speech.png|thumb|400px|
Long-window reassigned spectrogram of the word "open",
computed using a 54.4 ms Kaiser window with a shaping
parameter of 9, emphasizing harmonics.]]
 
[[Image:Short-window reassigned spectrogram of speech.png|thumb|400px|
Short-window reassigned spectrogram of the word "open",
computed using a 13.6 ms Kaiser window with a shaping
parameter of 9, emphasizing formants and glottal pulses.]]
 
Just as each bandpass filter in the short-time Fourier
transform filterbank may pass at most a single complex
exponential component, two temporal events must be
sufficiently separated in time that they do not lie in the
same windowed segment of the input signal. This is the
property of separability in the time domain, and is
equivalent to requiring that the time between two events be
greater than the length of the impulse response of the
short-time Fourier transform filters, the span of non-zero
samples in <math>h(t)</math>.
 
In general, there is an infinite number of equally valid
decompositions for a multi-component signal.
The separability property must be considered in the context of the
desired decomposition. For example, in the analysis of a speech signal,
an analysis window that is long relative to the time between glottal pulses
is sufficient to separate harmonics, but the individual
glottal pulses will be smeared, because
many pulses are covered by each window
(that is, the individual pulses are not separable, in time,
by the chosen analysis window).
An analysis window that is much shorter than the
time between glottal pulses may resolve the glottal pulses,
because no window spans
more than one pulse, but the harmonic frequencies
are smeared together, because the main lobe of the analysis window
spectrum is wider than the spacing between the harmonics
(that is, the harmonics are not separable, in frequency,
by the chosen analysis window).


== References ==
== References ==
 
{{reflist}}
<references/>


== Further reading ==
== Further reading ==
*S. A. Fulop and K. Fitz, ''A spectrogram for the twenty-first century'', Acoustics Today, vol. 2, no. 3, pp.&nbsp;26–33, 2006.
* Juan Chapa, ''Oxyrynchus Papyri'' 66:11-39. (no. 4499).
*S. A. Fulop and K. Fitz, ''Algorithms for computing the time-corrected instantaneous frequency (reassigned) spectrogram, with applications'', Journal of the Acoustical Society of America, vol. 119, pp.&nbsp;360 – 371, Jan 2006.
* Philip W. Comfort and David P. Barrett, ''The Text of the Earliest New Testament Greek Manuscripts'', (Wheaton, Illinois: [[Tyndale House|Tyndale House Publishers]], 2001), pp.&nbsp;664–677.
* [[David C. Parker]], [http://books.google.pl/books?id=C7ZLQns00MAC&pg=PA73&lpg=PA73&dq=%22Editio+Octava+Critica+Maior%22&source=bl&ots=d6JC8Rrqf1&sig=firgZQpFa4VuELKxaNZNY3c1tlY&hl=pl&ei=u_MyTpyJOoqd-wa3_t2jDQ&sa=X&oi=book_result&ct=result&resnum=7&ved=0CEAQ6AEwBjgo#v=onepage&q=%22Editio%20Octava%20Critica%20Maior%22&f=false ''A new Oxyrhynchus Papyrus of Revelation: P115 (P. Oxy. 4499)''], in: ''Manuscripts, Texts, Theology: Collected Papers, 1977-2007'', [[Walter de Gruyter]], Berlin, 2009, pp.&nbsp;73–92.


== External links ==
== External links ==
* [http://tftb.nongnu.org/ TFTB — Time-Frequency ToolBox]
* Oxford University [http://www.papyrology.ox.ac.uk/POxy/beast/beast616.html 'P. Oxy. LXVI 4499']
* [http://www.klingbeil.com/spear/ SPEAR - Sinusoidal Partial Editing Analysis and Resynthesis]
* Image of the fragments of [http://www.csad.ox.ac.uk/POxy/papyri/vol66/pages/4499.htm P. Oxy. LXVI 4499]
* [http://www.cerlsoundgroup.org/Loris/ Loris - Open-source software for sound modeling and morphing]
{{Grenfell and Hunt}}
* [http://musicalgorithms.ewu.edu/algorithms/roughness.html SRA - A web-based research tool for spectral and roughness analysis of sound signals] (supported by a Northwest Academic Computing Consortium grant to J. Middleton, Eastern Washington University)


[[Category:Time–frequency analysis]]
{{DEFAULTSORT:Papyrus 0115}}
[[Category:Transforms]]
[[Category:New Testament papyri]]
[[Category:Oxyrhynchus papyri]]
[[Category:3rd-century biblical manuscripts]]
[[Category:Egyptian papyri]]
[[Category:Early Greek manuscripts of the New Testament]]

Revision as of 01:48, 16 August 2014

Template:New Testament manuscript infobox Papyrus 115 (P. Oxy. 4499, designated by P115 in the Gregory-Aland numbering) is a fragmented manuscript of the New Testament written in Greek on papyrus. It consists of 12 fragments of a codex containing parts of the Book of Revelation. It dates to the 3rd century, ca. 225-275 AD.[1] Grenfell and Hunt discovered the papyrus at Oxyrhynchus, Egypt.

P115 was not deciphered and published until the end of the 20th century. It is currently housed at the Ashmolean Museum.[2]

Description

The original codex had 33-36 lines per page of 15.5 cm by 23.5 cm. The surviving text includes 2:1-3, 13-15, 27-29; 3:10-12; 5:8-9; 6:5-6; 8:3-8, 11-13; 9:1-5, 7-16, 18-21; 10:1-4, 8-11; 11:1-5, 8-15, 18-19; 12:1-5, 8-10, 12-17; 13:1-3, 6-16, 18; 14:1-3, 5-7, 10-11, 14-15, 18-20; 15:1, 4-7.[3]

The nomina sacra are written in an abbreviated way: ΙΗΛ ΑΥΤΟΥ ΠΡΣ ΘΩ ΘΥ ΑΝΩΝ ΠΝΑ ΟΥΝΟΥ ΟΥΝΟΝ ΚΥ ΘΝ ΑΝΟΥ ΟΥΝΩ.

The text-type is the Alexandrian. P115 follows the text of Codex Alexandrinus (A) and Codex Ephraemi Rescriptus (C).[4]

An interesting textual variant of P115 is that it gives the number of the beast as 616 (chi, iota, stigma (ΧΙϚ)), rather than the majority reading of 666 (chi, xi, stigma (ΧΞϚ)), as does Codex Ephraemi Rescriptus.

See also

References

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Further reading

External links

Template:Grenfell and Hunt

  1. Juan Chapa, Oxy. Pap., 66:11-39, no. 4499
  2. Template:Cite web
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  4. Philip W. Comfort, Encountering the Manuscripts. An Introduction to New Testament Paleography & Textual Criticism, Nashville, Tennessee: Broadman & Holman Publishers, 2005, p. 77.