LazyBase: Trading freshness for performance at scale

 
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Old 06-23-2010
LazyBase: Trading freshness for performance at scale

HPL-2010-70 LazyBase: Trading freshness for performance at scale - Morrey III, Charles B.; Keeton, Kimberly; Soules, Craig A. N.; Veitch, Alistair
Keyword(s): distribute, database, scaling, pipelining, freshness, staleness, update/access tradeoff
Abstract: Increasingly, enterprise applications wish to perform data mining analyses on rapidly changing data sets. Many of these applications can perform correctly on varying degrees of stale data. However, traditional systems poorly support simultaneous updates and read queries at the performance desired by ...
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mlib_SignalMelCepstral_S16(3MLIB)			    mediaLib Library Functions				 mlib_SignalMelCepstral_S16(3MLIB)

NAME
mlib_SignalMelCepstral_S16 - perform cepstral analysis in mel frequency scale SYNOPSIS
cc [ flag... ] file... -lmlib [ library... ] #include <mlib.h> mlib_status mlib_SignalMelCepstral_S16(mlib_s16 *cepst, mlib_s32 cscale, const mlib_s16 *signal, void *state); DESCRIPTION
The mlib_SignalMelCepstral_S16() function performs cepstral analysis in mel frequency scale. The user supplied scaling factor will be used and the output will be saturated if necessary. The first two steps of mel scale cepstral analysis is the same as in general cepstral anaysis. After the logarithm of the spectrum magni- tude is obtained, it is converted into mel frequency scale before the inverse Fourier transform. +-----------+ +-----------+ | Linear | | Inverse | ... ------>| to |------->| Fourier |-----> X'(k) | Mel Scale | X''(m) | Transform | c(n) +-----------+ +-----------+ where X'(k) is defined in linear frequency scale and X''(m) is defined in mel frequency scale. The mel frequency scale is defined as following. freq_mel = melmul * LOG10(1 + freq_linear / meldiv) where freq_mel is the frequency in mel scale, freq_linear is the frequency in linear scale, melmul is the multiplying factor, muldiv is the dividing factor. Optionally, a bank of band pass filters in linear frequency scale can be used below the bank of band pass filters in mel frequency scale, as shown below in linear frequency scale. 0 f1 f2 f3 fp fp+1 fp+2 fp+3 fp+q |---|---|---| ... |---|----|-----| ... | ... -> freq where fp = melbgn, fp+q = melend, p = nlinear, q = nmel; the filters number 1 to p are defined in linear frequency scale which have equal bandwidth in linear frequency scale; the filters number p+1 to p+q are defined in mel frequency scale which have equal bandwidth in mel frequency scale and increasing bandwidth in linear frequency scale. See Digital Signal Processing by Alan V. Oppenheim and Ronald W. Schafer, Prentice Hall, 1974. See Fundamentals of Speech Recognition by Lawrence Rabiner and Biing-Hwang Juang, Prentice Hall, 1993. PARAMETERS
The function takes the following arguments: cepst The cepstral coefficients. cscale The scaling factor of cepstral coefficients, where actual_data = output_data * 2**(-scaling_factor). signal The input signal vector, the signal samples are in Q15 format. 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_SignalMelCepstralInit_S16(3MLIB), mlib_SignalMelCepstral_S16_Adp(3MLIB), mlib_SignalMelCepstralFree_S16(3MLIB), attributes(5) SunOS 5.10 10 Nov 2004 mlib_SignalMelCepstral_S16(3MLIB)