Hi !

I'm looking for an efficient way to calc the RMS of a series of n-samples(24bit) with my BF537.

if have troubles to calc the sum of x^2 and store it because i need at least 64bit-and more if i have an large buffer of samples.

Is there any efficient method known?

is it better to do it by Xrms^2=mean(x)^2+stdDeviation^2 - cost me to loops?

regards chris

in addition

i have observed that define a var as unsigned long long (for u64) dont produce the wanted code to multiply two 32bit vars

or is the u64-value in debug window(locals) not correctly displayed ??

unsigned long long measureCH2=0;

int currInSample[4];

measureCH2 += currInSample[1]*currInSample[1]; /* get the square value */

produces:

[FFA01504] R2 *= R2 ;

[FFA01506] R5 = R2 >>> 31 ;

[FFA0150A] R3 = [ FP + -140 ] ;

[FFA0150E] R6 = [ FP + -136 ] ;

[FFA01512] R2 = R2 + R3 ( NS ) ;

[FFA01516] CC = AC0 ;

[FFA01518] R3 = CC ;

[FFA0151A] R6 = R5 + R6 ( NS ) ;

[FFA0151E] R3 = R6 + R3 ( NS ) ;

[FFA01522] [ FP + -140 ] = R2 ;

[FFA01526] [ FP + -136 ] = R3 ;

If your 24-bit data are fixed point values in 1.23 format, you could implement a rms function as follows (please note the use of explicit fixed point operators as opposed to using integer arithmetic):

#include <fract_math.h>

#include <fract2float_conv.h>

#include <math.h>

int currInSample[sample_length];

fract32 sample;

unsigned long long sum;

float rms;

int k;

for( k = 0; k < sample_length; k++ )

{

/* Convert from 1.23 fractional to 1.31 (aligning decimal points) */

sample = shl_fr1x32( (fract32) currInSample[k], 8 );

/* Compute MAC,

using fixed point mulitplication with rounding and saturation

*/

sum += (unsigned long long) multr_fr1x32x32( sample, sample );

}

/* Compute sum of squares / sample length => will return 32-bit result */

sum = sum / (unsigned long long) sample_length;

/* Compute sqrt( sum of squares / sample length ), with 24-bit precision */

rms[k] = sqrtf( fr32_to_float( (fract32) sum ));

Using integer arithmetic means you will be accumulating 48-bit data (24.0 * 24.0 Integers) as opposed to 32-bit data (1.31 * 1.31 = 2.62, rounded to 1.31) for the fractional example. Thus your 64-bit sum will fill up faster.

To perform a 24.0 * 24.0 => 64.0 MAC, you should modify your expression to:

measureCH2 += (unsigned long long) currInSample[1] * (unsigned long long) currInSample[1];

This way, the product will be computed using 64-bit arithmetic (which is necessary to fully capture a 24.0 * 24.0 product). Using a 32-bit multiplication is not recommened since the resulting product is likely to exceed the 32-bit return value.