search for: oversampl

...m = MULT16_32_Q15(interp[0],SHR32(accum[0], 1)) + MULT16_32_Q15(interp[1],SHR32(accum[1], 1)) + MULT16_32_Q15(interp[2],SHR32(accum[2], 1)) + MULT16_32_Q15(interp[3],SHR32(accum[3], 1)); #else cubic_coef(frac, interp); - sum = interpolate_product_single(iptr, st->sinc_table + st->oversample + 4 - offset - 2, N, st->oversample, interp); + interpolate_product_single(&sum, iptr, st->sinc_table + st->oversample + 4 - offset - 2, N, st->oversample, interp); #endif out[out_stride * out_sample++] = SATURATE32(PSHR32(sum, 14), 32767); @@ -534,7 +534,7 @@...

...mm_movehl_ps(sum, sum)); + sum = _mm_add_ss(sum, _mm_shuffle_ps(sum, sum, 0x55)); + _mm_store_ss(&ret, sum); + return ret; +} + +#define OVERRIDE_INTERPOLATE_PRODUCT_SINGLE +static inline float interpolate_product_single(const float *a, const float *b, unsigned int len, const spx_uint32_t oversample, float *frac) { + int i; + float ret; + __m128 sum = _mm_setzero_ps(); + __m128 f = _mm_loadu_ps(frac); + for(i=0;i<len;i+=2) + { + sum = _mm_add_ps(sum, _mm_mul_ps(_mm_load1_ps(a+i), _mm_loadu_ps(b+i*oversample))); + sum = _mm_add_ps(sum, _mm_mul_ps(_mm_load1_ps(a+i+1), _mm_loadu_p...

...mm_movehl_ps(sum, sum)); + sum = _mm_add_ss(sum, _mm_shuffle_ps(sum, sum, 0x55)); + _mm_store_ss(&ret, sum); + return ret; +} + +#define OVERRIDE_INTERPOLATE_PRODUCT_SINGLE +static inline float interpolate_product_single(const float *a, const float *b, unsigned int len, const spx_uint32_t oversample, float *frac) { + int i; + float ret; + __m128 sum = _mm_setzero_ps(); + __m128 f = _mm_loadu_ps(frac); + for(i=0;i<len;i+=2) + { + sum = _mm_add_ps(sum, _mm_mul_ps(_mm_load1_ps(a+i), _mm_loadu_ps(b+i*oversample))); + sum = _mm_add_ps(sum, _mm_mul_ps(_mm_load1_ps(a+i+1), _mm_loadu_p...

some times ago i was playing with coding, shannon theoremes and other stuff, i have tried without success to compress audio wave, and i have notice that simply oversampling audio material enacnhe a lot compression ratio i only take awav file, oversampled it by 20 tiimes and then compressi it using pkzip or rar. i don0't remember if i also do a CONSTANT PREDICTION, iony know that pkzip and rar nicely work when they have to compress a file that has few symbols...

...ed looking at the sample function and prob option but all examples i > seen do not use an imbalanced class problem as the one shown above > > > Thank you in advance > > > Thank you in advance > -- View this message in context: http://r.789695.n4.nabble.com/Subsampling-oversampling-from-a-data-frame-tp3965771p3965827.html Sent from the R help mailing list archive at Nabble.com.

Hi all, I am trying to predict a target variable that takes values 0 or 1 using the rpart command. In my initial dataset I have few positive observations of the target variable; therefore I have oversampled the rare event by a multiple of 6 (i.e. from 762 to 4572). However, in my results, I end up with a number of positives in one of the terminal nodes that is not divisible by 6. As I have the same observation repeated 6 times, shouldn't all of them follow the same branch of the tree and go to...

--- Hod McWuff <hod@wuff.dhs.org> wrote: > On Fri, 2002-10-04 at 10:26, Marco "elcabesa" Belli wrote: > > oversampling.. i maean digitally change the wave file rate form > 44khz to 440 > > khz > > > > it make next sample easyer predictable > > OK, IANASPE (signal processing engineer) but it seems to me that if a > simple shift like that can improve the compression ratio, then &gt...

Hi I have an umbalanced data set where I want to predict a binary variable Y. I want to do an under sampling by keeping all the 1 and taking just some of the 0 such as I'll have 90% of 0 and 10% of 1. Can u help me do that Thank u [[alternative HTML version deleted]]

constant prediction see this page http://flac.sourceforge.net/format.html oversampling.. i maean digitally change the wave file rate form 44khz to 440 khz it make next sample easyer predictable if i'll found my old work i'll tell you how much compression i could achieve

I have a question about data mining. I have a dataset of 70 instances with 14 features that belong to 4 classes. As the number of each class is not enough to obtain a good accuracy using some classifiers( svm, rna, knn) I need to "oversampling" the number of instances of each class. I have heard that there is a method to do this. It consists in generating these new instances as follows: new_instance <---- original_instance + u(epsilon) U(epsilon) is a uniform number in the range [-epsilon,epsilon] and this number is applie...

some times ago i was playing with coding, shannon theoremes and other stuff, i have tried without success to compress audio wave, and i have notice that simply oversampling audio material enacnhe a lot compression ratio i only take awav file, oversampled it by 20 tiimes and then compressi it using pkzip or rar. i don0't remember if i also do a CONSTANT PREDICTION, iony know that pkzip and rar nicely work when they have to compress a file that has few symbol...

Agreed that the oversampling isn't useful in the long term. I'm not sure what you mean by 'dictioniary overhead'. I'd like to see an easy-to-invoke set of parameters that will spare no cpu expense and produce the tightest theoretically possible output. I'm guessing the best of Marco's idea can...

Hola Comunidad, Feliz Año 2017: Tengo un problemilla con una regresión logística desbalanceada, tengo demasiados TRUE (93%). ¿Sabría alguién alguna forma de corregir el problema con R? Un slaudo, Milagros Camacho --- El software de antivirus Avast ha analizado este correo electrónico en busca de virus. https://www.avast.com/antivirus

On Fri, Oct 04, 2002 at 01:57:03PM -0400, Hod McWuff wrote: > Agreed that the oversampling isn't useful in the long term. I'm not sure > what you mean by 'dictioniary overhead'. > > I'd like to see an easy-to-invoke set of parameters that will spare no > cpu expense and produce the tightest theoretically possible output. > > I'm guessing the...

...question I have is fairly simple (I hope). The data were collected in two stages: a 15,000-subject randomly-sampled telephone interview (the SCREEN), with 2,517 subjects selected for in-home interviews. The 2,517-subject survey constitutes the actual dataset we're using. But those data include oversamples for activists and african-americans, plus a case weighting variable. According to the survey's documentation, using the weight allows the oversampled study data to be representative of the 15,000-person random sample. All this is fine, and I've been able to run linear models on the data...

...the 655k current limit. Please note this is not for using ridiculously high sample rate sourced audio for some imaginary audible benefit. I've been involved in some experimentation with offline upsampling in software prior to delivery to an external DAC as a way to bypass the DAC's internal oversampling and found that wavpak is the only compressed container format that supports the 705/768 sample rates but it is very poorly supported and extremely slow during decompression, and fully uncompressed WAV data is extremely cumbersome. Most DACs do appear to turn off their anti-aliasing filters at sa...

On Tue, Apr 05, 2005 at 08:26:45AM -0700, Ralph Giles wrote: > AM radio is lower quality (mono) but I don't know > what the digital equivalent would be. Just a minor nit-pick: AM radio can be stereo. However its use is almost nonexistent. See <http://users.hfx.eastlink.ca/~amstereo/amstereo.htm> for more information. > Telephone is nominally 8 kHz mono > (i.e. really bad)

On Sat, Oct 05, 2002 at 12:26:12PM -0400, Hod McWuff wrote: > On Sat, 2002-10-05 at 03:19, Miroslav Lichvar wrote: > > On Fri, Oct 04, 2002 at 01:57:03PM -0400, Hod McWuff wrote: > > > Agreed that the oversampling isn't useful in the long term. I'm not sure > > > what you mean by 'dictioniary overhead'. > > > > > > I'd like to see an easy-to-invoke set of parameters that will spare no > > > cpu expense and produce the tightest theoretically possible...

And it runs linux. http://www.zip4x4.com/ZIP4x4.htm Anyone seen one? bkw

...)) + MULT16_32_Q15(interp[1],SHR32(accum[1], 1)) + MULT16_32_Q15(interp[2],SHR32(accum[2], 1)) + MULT16_32_Q15(interp[3],SHR32(accum[3], 1)); + sum = SATURATE32PSHR(sum, 15, 32767); #else cubic_coef(frac, interp); sum = interpolate_product_single(iptr, st->sinc_table + st->oversample + 4 - offset - 2, N, st->oversample, interp); #endif - out[out_stride * out_sample++] = SATURATE32(PSHR32(sum, 14), 32767); + out[out_stride * out_sample++] = sum; last_sample += int_advance; samp_frac_num += frac_advance; if (samp_frac_num >= den_rate...