Linux and UNIX Man Pages

Test Your Knowledge in Computers #233
Difficulty: Easy
The goal of ARPANET, the precursor to the global Internet, was to exploit new computer technologies to meet the needs of military command and control against nuclear threats, achieve survivable control of US nuclear forces, and improve military tactical and management decision making.
True or False?
Linux & Unix Commands - Search Man Pages

mlib_signallpcautocorrelgetenergy_s16(3mlib) [opensolaris man page]

mlib_SignalLPCAutoCorrelGetEnergy_S16(3MLIB)		    mediaLib Library Functions		      mlib_SignalLPCAutoCorrelGetEnergy_S16(3MLIB)

mlib_SignalLPCAutoCorrelGetEnergy_S16, mlib_SignalLPCAutoCorrelGetEnergy_S16_Adp - return the energy of the input signal SYNOPSIS
cc [ flag... ] file... -lmlib [ library... ] #include <mlib.h> mlib_status mlib_SignalLPCAutoCorrelGetEnergy_S16( mlib_s16 *engery, mlib_s32 escale, void *state); mlib_status mlib_SignalLPCAutoCorrelGetEnergy_S16_Adp( mlib_s16 *engery, mlib_s32 *escale, void *state); DESCRIPTION
Each of the functions returns the energy of the input signal. 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 autocorrelation method, the coefficients can be obtained by solving following set of linear equations. M SUM a(i) * r(|i-k|) = r(k), k=1,...,M i=1 where N-k-1 r(k) = SUM s(j) * s(j+k) j=0 are the autocorrelation coefficients of s(*), N is the length of the input speech vector. r(0) is the energy of the speech signal. Note that the autocorrelation matrix R is a Toeplitz matrix (symmetric with all diagonal elements equal), and the equations can be solved efficiently with Levinson-Durbin algorithm. See Fundamentals of Speech Recognition by Lawrence Rabiner and Biing-Hwang Juang, Prentice Hall, 1993. Note for functions with adaptive scaling (with _Adp postfix), the scaling factor of the output data will be calculated based on the actual data; for functions with non-adaptive scaling (without _Adp postfix), the user supplied scaling factor will be used and the output will be saturated if necessary. PARAMETERS
Each function takes the following arguments: energy The energy of the input signal. escale The scaling factor of the energy, where actual_data = output_data * 2**(-scaling_factor). state Pointer to the internal state structure. RETURN VALUES
Each 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 |Committed | +-----------------------------+-----------------------------+ |MT-Level |MT-Safe | +-----------------------------+-----------------------------+ SEE ALSO
mlib_SignalLPCAutoCorrelInit_S16(3MLIB), mlib_SignalLPCAutoCorrel_S16(3MLIB), mlib_SignalLPCAutoCorrelGetPARCOR_S16(3MLIB), mlib_SignalLP- CAutoCorrelFree_S16(3MLIB), attributes(5) SunOS 5.11 2 Mar 2007 mlib_SignalLPCAutoCorrelGetEnergy_S16(3MLIB)

Featured Tech Videos