1mlib_SignalLPCAutoCorrel_F3m2e(d3iMaLLIiBb)Library Fmulnicbt_iSoingsnalLPCAutoCorrel_F32(3MLIB)
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NAME

6       mlib_SignalLPCAutoCorrel_F32  -  perform  linear predictive coding with
7       autocorrelation method
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SYNOPSIS

10       cc [ flag... ] file... -lmlib [ library... ]
11       #include <mlib.h>
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13       mlib_status mlib_SignalLPCAutoCorrel_F32(mlib_f32 *coeff,
14            const mlib_f32 *signal, void *state);
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DESCRIPTION

18       The mlib_SignalLPCAutoCorrel_F32() function performs linear  predictive
19       coding with autocorrelation method.
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22       In  linear  predictive coding (LPC) model, each speech sample is repre‐
23       sented as a linear combination of the past M samples.
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25                      M
26              s(n) = SUM a(i) * s(n-i) + G * u(n)
27                     i=1
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31       where s(*) is the speech signal, u(*) is the excitation signal,  and  G
32       is  the gain constants, M is the order of the linear prediction filter.
33       Given s(*), the goal is to find a set of coefficient  a(*)  that  mini‐
34       mizes the prediction error e(*).
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36                             M
37              e(n) = s(n) - SUM a(i) * s(n-i)
38                            i=1
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42       In  autocorrelation method, the coefficients can be obtained by solving
43       following set of linear equations.
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45               M
46              SUM a(i) * r(|i-k|) = r(k), k=1,...,M
47              i=1
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51       where
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53                    N-k-1
54              r(k) = SUM s(j) * s(j+k)
55                     j=0
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59       are the autocorrelation coefficients of s(*), N is the  length  of  the
60       input speech vector. r(0) is the energy of the speech signal.
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63       Note  that the autocorrelation matrix R is a Toeplitz matrix (symmetric
64       with all diagonal elements equal), and  the  equations  can  be  solved
65       efficiently with Levinson-Durbin algorithm.
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68       See  Fundamentals  of Speech Recognition by Lawrence Rabiner and Biing-
69       Hwang Juang, Prentice Hall, 1993.
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PARAMETERS

72       The function takes the following arguments:
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74       coeff     The linear prediction coefficients.
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77       signal    The input signal vector.
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80       state     Pointer to the internal state structure.
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RETURN VALUES

84       The function returns MLIB_SUCCESS if successful. Otherwise  it  returns
85       MLIB_FAILURE.
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ATTRIBUTES

88       See attributes(5) for descriptions of the following attributes:
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93       ┌─────────────────────────────┬─────────────────────────────┐
94       │      ATTRIBUTE TYPE         │      ATTRIBUTE VALUE        │
95       ├─────────────────────────────┼─────────────────────────────┤
96       │Interface Stability          │Committed                    │
97       ├─────────────────────────────┼─────────────────────────────┤
98       │MT-Level                     │MT-Safe                      │
99       └─────────────────────────────┴─────────────────────────────┘
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SEE ALSO

102       mlib_SignalLPCAutoCorrelInit_F32(3MLIB), mlib_SignalLPCAutoCorrelGetEn‐
103       ergy_F32(3MLIB),          mlib_SignalLPCAutoCorrelGetPARCOR_F32(3MLIB),
104       mlib_SignalLPCAutoCorrelFree_F32(3MLIB), attributes(5)
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108SunOS 5.11                        2 Mar 2007mlib_SignalLPCAutoCorrel_F32(3MLIB)
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