### *** Outline ***

- Harmonic inversion
- Harmonic inversion in Ubuntu 9.04
- Harmonic inversion in Cygwin 1.5
- Effect of spin-spin relaxation time T2 in harminv
- Effect of frequency offset in harminv
- Dead time correction in harminv
- Harmonic inversion - reference
- Harmonic inversion - author
- Generalized eigenvalue problem
- Generalized eigenvalue problem - reference
- Generalized eigenvalue problem - book
- Linux OS
- Cygwin
- LPSVD

### Harmonic inversion

✱ Harminv: a free program (and accompanying C library) to solve the problem of harmonic inversion: decomposing a time-series into a sum of sinusoids, including exponentially decaying sinusoids

✱ Harminv
installation;

new installation procedure
in cygwin-1.7 (Setup.exe version 2.738):

1 download it in your cygwin home folder 2 gzip -d harminv-1.3.1.tar.gz 3 tar -xvf harminv-1.3.1.tar 4 cd harminv-1.3.1 5 ./configure --prefix=/usr/local F77="gfortran" 6 make 7 make install

✱ Harminv manual page

✱ Harminv example

✱ sourcearchive: harminv file list

✱ Steven G. Johnson (MIT Applied Mathematics) From electrons to photons (1300 Ko MS PPT file)

✱ W. Bermel (Bruker Biospin, 2008) Fast data acquisition methods (5600 Ko PDF file)

✱ Ubuntu: harminv (1.4.1-2) [universe]

✱ CommentCaMarche: Repartitionner, installer Linux (Ubuntu 8.04), conserver Windows

✱ Avram: a virtual machine code interpreter

### Harmonic inversion in Ubuntu 9.04

We provide OpenOffice3 spreadshead and MS Excel spreadshead which contain the real and imaginary parts of an FID associated with three Lorentzian lineshapes:

Frequency (MHz) T2 (microsecond) Amplitude Phase 0.024 4000 1 0 0.010 3000 0.5 0 -0.010 2000 0.3 0 The FID of a Lorentzian lineshape inharminvis defined by FID(t) = Amplitude*exp(-i*(2*π*Frequency*t - Phase))*exp(-t/T2) FID(t) = Amplitude*exp(-i*(2*π*Frequency*t - Phase))*exp(-t*Decay) In contrast,the FID of a Lorentzian lineshape inNMRis defined by FID(t) = Amplitude*exp(i*(2*π*Frequency*t + Phase))*exp(-t/T2) FID(t) = Amplitude*exp(i*(2*π*Frequency*t + Phase))*exp(-t*Decay) Decay (= 1/T2) and Frequency define the quality factor Q: Q = π*|Frequency|/Decay = π*|Frequency|*T2 10 is the value by default of Q.

This FID and the corresponding spectrum are represented in the following two figures:

We select the spreadsheet cells containing the real and imaginary parts of this FID, and then paste the data into a text file saved as mimi. In this file, the character i is appended to the imaginary part; the real and imaginary parts of an amplitude are joined.

Within a spectral width SW (= 1/DW) ranging from -SW/2 to SW/2, only spectrum lines located inside ]-SW/4, SW/4[ are identified by harminv, including folded spectrum lines.

In Ubuntu operating system, the results provided by harminv are:

### Harmonic inversion in Cygwin 1.5

In MS Windows, use Bloc-notes or WordPad for saving the text file mimi.

For the other data, see Harmonic inversion in Ubuntu

### Effect of spin-spin relaxation time T2 in harminv

#### Example 1

Consider another simulation with two Lorentzian lineshapes where both T2 = 400 seconds:

Frequency (Hz) T2 (second) Amplitude 1 400 1 1.1 400 2 The signal FID is generated with a step t = 0.1 second.

The two signals are detected by harminv.

#### Example 2

Consider the same simulation but both T2 = 4 seconds:

Frequency (Hz) T2 (second) Amplitude 1 4 1 1.1 4 2

This figure shows that within a spectral width SW = 10 Hz ranging from -5 Hz to +5 Hz, only spectrum lines located inside ]-2.5 Hz, 2.5 Hz[ are identified by harminv.

The two signals are detected by harminv.

#### Example 3

Consider the same simulation but T2 = 4 seconds for the low frequency Lorentzian lineshape and T2 = 2 seconds for the high frequency Lorentzian lineshape :

Frequency (Hz) T2 (second) Amplitude 1 4 1 1.1 2 2

Only the signal with T2 = 4 seconds is detected by harminv.

#### Example 4

Consider the same simulation but T2 = 2 seconds for the low frequency Lorentzian lineshape and T2 = 4 seconds for the high frequency Lorentzian lineshape :

Frequency (Hz) T2 (second) Amplitude 1 2 1 1.1 4 2

Only the signal with T2 = 4 seconds is detected by harminv.

#### Example 5

Consider the same simulation but both T2 = 2 seconds:

Frequency (Hz) T2 (second) Amplitude 1 2 1 1.1 2 2

The two signals are not detected by harminv.

Since the quality factor Q of a signal is proportional to T2, it decreases with T2. When Q is lower than its default value (= 10), this signal is not detected by harminv. Fortunately, we can decrease the default value of Q.

Once we define the default value of Q to 5, the two signals are detected by harminv.

### Effect of frequency offset in harminv

#### Example 1

Consider another simulation with three Lorentzian lineshapes where T2 = 8 seconds:

Frequency (Hz) T2 (second) Amplitude 0.5 8 1 1.0 8 1 1.5 8 1 The signal FID is generated with a step t = 0.1 second. The frequency axis in harminv increases from left to right direction.

The three signals located at 0.5 Hz, 1 Hz, and 1.5 Hz are detected by harminv. The Q value (= 12.5671) of the 0.5-Hz signal is close to the default value (= 10 ).

#### Example 2

Consider the same simulation with three Lorentzian lineshapes where T2 = 6 seconds:

Frequency (Hz) T2 (second) Amplitude 0.5 6 1 1.0 6 1 1.5 6 1

Only two signals (1 Hz and 1.5 Hz) are detected by harminv. That located at the lowest frequency (0.5 Hz) is missing due to T2 value. Its Q value is less than 10.

#### Example 3

Consider the same simulation with three Lorentzian lineshapes where T2 = 3 seconds:

Frequency (Hz) T2 (second) Amplitude 0.5 3 1 1.0 3 1 1.5 3 1

Only the signal located at the highest frequency (1.5 Hz) is detected by harminv. The other two located at lower frequencies (0.5 Hz and 1 Hz) are missing due to T2 value.

#### Example 4

Consider the same simulation with three Lorentzian lineshapes of different T2:

Frequency (Hz) T2 (second) Amplitude 0.5 9 1 1.0 6 1 1.5 3 1

Since the value of T2 increases when the frequency offset decreases, the Q values of the three signals remain larger than the default value (= 10). As a result, the three signals are detected by harminv.

### Dead time correction in harminv

#### FID simulation with SIMPSON

We provide OpenOffice3 spreadshead and MS Excel spreadshead which contain the real and imaginary parts of an FID simulated with SIMPSON. This FID is generated with a step t = 0.1 millisecond. The following figure is the absorption spectrum.

This FID is analyzed with harminv:

Among these results, we choose the nine most significant lineshapes:

pascal@pascalman ~/harminv-1.3.1 $ harminv -Q 0.1 -t 0.1 0-25 < mimi frequency, decay constant, Q, amplitude, phase, error -0.206699, 8.411231e-02, 7.72022, 1.55368, -0.676291, 6.592080e-05 -0.18529, 3.717283e-01, 1.56595, 1.62323, -0.362238, 2.716799e-03 -0.0973252, 9.353716e-01, 0.326882, 2.71895, -0.0858323, 1.759053e-02 0.0212417, 1.395977e-01, 0.478036, 0.0325433, 0.630549, 2.242755e-02 0.127801, 2.072755e-01, 1.93703, 0.0895102, 2.44031, 3.941283e-03 0.174193, 9.237603e-01, 0.59241, 2.07773, 0.306538, 2.054223e-02 0.23999, 2.132489e-01, 3.53555, 0.0751803, -1.5363, 2.368882e-03 0.381661, 5.100819e-01, 2.35065, 0.857901, 0.878896, 3.941438e-03 0.416107, 1.574062e-01, 8.30487, 0.237168, 1.50239, 5.907249e-04

The following figure is the corresponding spectrum simulated with these nine most significant lineshapes.

#### Dead time of an FID simulated with SIMPSON

We delete the first ten complex points of the previous FID simulated with SIMPSON. The following figure is the corresponding spectrum.

This truncated FID is analyzed with harminv:

Among these results, we choose the nine most significant lineshapes:

pascal@pascalman ~/harminv-1.3.1 $ harminv -Q 0.1 -t 0.1 0-25 < mimi frequency, decay constant, Q, amplitude, phase, error -0.282786, 5.812946e-01, 1.52831, 1.46747, 0.868016, 7.474566e-02 -0.224117, 1.555329e-01, 4.52692, 1.1898, -0.0357725, 3.827899e-02 -0.207581, 5.262681e-02, 12.3917, 0.756576, 0.256943, 8.726306e-03 0.11712, 9.059055e-02, 4.06161, 0.0138281, 0.934831, 6.742798e-03 0.201694, 1.190246e-01, 5.32361, 0.0142939, 0.421093, 7.885690e-03 0.417218, 6.430202e-01, 2.03839, 0.404517, -1.26507, 3.930932e-02 0.42231, 1.848341e-01, 7.17793, 0.281399, -0.57026, 1.193036e-03 0.48845, 4.668777e-01, 3.28675, 0.0876451, -0.816684, 3.282163e-02 0.635941, 4.221341e-01, 4.73278, 0.0133947, -1.46356, 1.337269e-02

The following figure is the corresponding spectrum simulated with these nine most significant lineshapes.

#### Correction of dead time of an FID simulated with SIMPSON

Thanks to these nine lineshapes, we simply simulate the ten missing complex points of the previous truncated FID simulated with SIMPSON. The following figure is the corresponding spectrum.

The recovered lineshape is not perfect but the effect of dead time has been attenuated.

### Harmonic inversion - reference

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### Harmonic inversion - author

✱ Howard S. Taylor, University of Southern California

✱ Vladimir A. Mandelshtam, University of California, Irvine

### Generalized eigenvalue problem

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### Linux OS

✱ Système d'exploitation basé sur Linux : Fedora

✱ Mauriat Miranda: Download Fedora Linux

✱ Softpedia: Installing Fedora 8 Werewolf

✱ InformIT: Installing Fedora

✱ UNIX tutorial for beginners

✱ PCWDLD: Linux commands cheat sheet as quick reference for both experienced and basic users.

✱ GNU Operating System

✱ GCC: the GNU Compiler Collection

✱ David Henry: Une introduction à GCC et MinGW

✱ ubuntu-fr.org: Comment utiliser MingW32 pour faire des exécutables Windows ?

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### Cygwin

✱ Wikipedia: Cygwin is free software that provides a Unix-like environment and command-line interface for Microsoft Windows

✱ George B. Moodya:
An introduction to Cygwin

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with a vast set of GNU and other free software applications organized into a large number
of optional packages

✱ Cygwin information and installation

✱ Cygwin installation on Windows XP

✱ InOnIt: Cygwin and Java

✱ Cygwin: Programmation

✱ Jacques Grelet: Cygwin

### LPSVD

✱ BRUKER BIOSPIN Newsletter (PDF): NMR processing technique “Linear Prediction”

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**LPSVD algorithm for parameter estimation of damped sinusoids**,
(PDF)

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**Magnetic resonance spectroscopy identifies neural progenitor cells in the live human brain**,

*Science* **318**, 980-985 (2007).

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**188**, 231-245 (2007).

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