12-06-2013
You have restated the method you have chosen to solve your goal. Not your goal.
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Hi
i have the following code:
if(($line!=1) and (@field!='\$')){
print ( "\nTRY TO CONNECT TO DATABASE................\n");
my $dbh = DBI->connect($dsn, $user, $pass);
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eval
... (1 Reply)
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Help !!
First, Thanks in Advance
Here is what I have
I have an environment Variable, let's call it v_VALUE.
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Hi Gurus,
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Hi all,
some small script with eval turned me to crazy.
my OS is linux
Linux s10-1310 2.6.16.53-0.8.PTF.434477.3.TDC.0-smp #1 SMP Fri Aug 31 06:07:27 PDT 2007 x86_64 x86_64 x86_64 GNU/Linux
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anyone has any info on why this is complaining???
vivek@vivek-c5e55ef2e ~/TAC
$ zoneCounter=1
vivek@vivek-c5e55ef2e ~/TAC
$ optUsage1=23%
vivek@vivek-c5e55ef2e ~/TAC
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-bash: syntax error... (1 Reply)
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10. Shell Programming and Scripting
anyone has any info on why this is complaining???
vivek@vivek-c5e55ef2e ~/TAC
$ zoneCounter=1
vivek@vivek-c5e55ef2e ~/TAC
$ optUsage1=23%
vivek@vivek-c5e55ef2e ~/TAC
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LEARN ABOUT SUNOS
mlib_signallpccovariance_f32
mlib_SignalLPCCovariance_F32(3MLIB) mediaLib Library Functions mlib_SignalLPCCovariance_F32(3MLIB)
NAME
mlib_SignalLPCCovariance_F32 - perform linear predictive coding with covariance method
SYNOPSIS
cc [ flag... ] file... -lmlib [ library... ]
#include <mlib.h>
mlib_status mlib_SignalLPCCovariance_F32(mlib_f32 *coeff, const mlib_f32 *signal, void *state);
DESCRIPTION
The mlib_SignalLPCCovariance_F32() function performs linear predictive coding with covariance method.
In linear predictive coding (LPC) model, each speech sample is represented as a linear combination of the past M samples.
M
s(n) = SUM a(i) * s(n-i) + G * u(n)
i=1
where s(*) is the speech signal, u(*) is the excitation signal, and G is the gain constants, M is the order of the linear prediction fil-
ter. Given s(*), the goal is to find a set of coefficient a(*) that minimizes the prediction error e(*).
M
e(n) = s(n) - SUM a(i) * s(n-i)
i=1
In covariance method, the coefficients can be obtained by solving following set of linear equations.
M
SUM a(i) * c(i,k) = c(0,k), k=1,...,M
i=1
where
N-k-1
c(i,k) = SUM s(j) * s(j+k-i)
j=0
are the covariance coefficients of s(*), N is the length of the input speech vector.
Note that the covariance matrix R is a symmetric matrix, and the equations can be solved efficiently with Cholesky decomposition method.
See Fundamentals of Speech Recognition by Lawrence Rabiner and Biing-Hwang Juang, Prentice Hall, 1993.
PARAMETERS
The function takes the following arguments:
coeff The linear prediction coefficients.
signal The input signal vector.
state Pointer to the internal state structure.
RETURN VALUES
The function returns MLIB_SUCCESS if successful. Otherwise it returns MLIB_FAILURE.
ATTRIBUTES
See attributes(5) for descriptions of the following attributes:
+-----------------------------+-----------------------------+
| ATTRIBUTE TYPE | ATTRIBUTE VALUE |
+-----------------------------+-----------------------------+
|Interface Stability |Evolving |
+-----------------------------+-----------------------------+
|MT-Level |MT-Safe |
+-----------------------------+-----------------------------+
SEE ALSO
mlib_SignalLPCCovarianceInit_F32(3MLIB), mlib_SignalLPCCovarianceFree_F32(3MLIB), attributes(5)
SunOS 5.10 10 Nov 2004 mlib_SignalLPCCovariance_F32(3MLIB)