Hi everybody, I'll show you what I've done and what results I got. Aim Exploiting ADAU1701 to correct a loud speaker frequency response (from 40Hz to 1000Hz) in order to make it as flat as possible in the low band. Procedure Get loudspeaker impulse response and frequency response measurements. Use of the inverse measured frequency response in order to compute FIR coefficients of an equalizing filter that eqaualizes my loudspeaker. The filter design has been done using a simple windowing method. Many filters have been designed of many different order, I choose for this example a 600th-order FIR. Simulation in Matlab of the filter designed (see Results point 1.) Exporting of filter coefficients in text-file in order to feed the "FIR" block of sigmastudio. Build a patch in SigmaStudio composed of just a FIR filter block, a probe/stimulus components and input/output associations. Instructions memory consumption of about 610 instruction memory locations. The FIR block has been updated with the coefficients file ( I've attached it below). Measure the loudspeaker frequency response using the processing corretion built-up by the 600th-order FIR (see Results point 2.) Results Matlab simulation of equalization procedure Real equalization process using the ADAU1701 computation procedure to correct the original loudspeaker frequency response FIR filter frequency response into Matlab domain FIR filter frequency response into ADAU1701 domain (exploiting stimulus/probe blocks) Questions As you can see the simulated equalization process and the real one are very different. Also the frequency response of FIR in matlab and in sigmastudio are different expecially on the tail at high frequencies. I think that this mismatch is due to the arithmetic used by ADAU1701 and a PC. In my opinion ADAU1701 is a fixed-point DSP with double precision, isn't it? How FIR computation into DSP works? What's the correct format of the coefficients in order to achieve a working FIR filtering? I attached the coefficients file as you can see if the decimal format is useful or not (to visualize it better use matlab or notepad++, because windows textfile reader doesn't read newline commands). What's the wordlength of a fixed-point coefficient admitted by the chip? How can I convert matlab coefficients in a fixed-point version suitable for sigmaDSP ADAU1701? I hope you can help me because I'm completely frozen on ths. I made many many tests and measurements without any successful results. Regards, Leo.

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Hi Leon: The difference in your results is due to quantization of your coefficients. The 1701 has a 5.23 fixed point format. To complicate things further the stimluy and probe provide a first approximation view of the transfer function and, although they do take into account the coefficient quantization and correct fixed point number, they do not do so for the actual signal and therefore you might also encounter differences in an actual measurement. The FIR block doesn't use the double precision arithmetic because it would make it very wastefull (double all the operations), for FIR filtering you most likey do not this double precison arithmetic. To simulate fixed point in Matlab, Mathworks has a fixed point library that you could use. You can also simply quantize your calculated coefficients to a 5.23 number by finding the fractional value that is best represented with a 2^-23 precision. Hope this helps. Miguel

FIR and general filtering on ADAU1701. Hints about fixed point arithmetic!

leonxp

on Aug 2, 2013

Hi everybody, I'll show you what I've done and what results I got.

Aim

Exploiting ADAU1701 to correct a loud speaker frequency response (from 40Hz to 1000Hz) in order to make it as flat as possible in the low band.

Procedure

Get loudspeaker impulse response and frequency response measurements.
Use of the inverse measured frequency response in order to compute FIR coefficients of an equalizing filter that eqaualizes my loudspeaker. The filter design has been done using a simple windowing method. Many filters have been designed of many different order, I choose for this example a 600th-order FIR.
Simulation in Matlab of the filter designed (see Results point 1.)
Exporting of filter coefficients in text-file in order to feed the "FIR" block of sigmastudio.
Build a patch in SigmaStudio composed of just a FIR filter block, a probe/stimulus components and input/output associations. Instructions memory consumption of about 610 instruction memory locations.
The FIR block has been updated with the coefficients file ( I've attached it below).
Measure the loudspeaker frequency response using the processing corretion built-up by the 600th-order FIR (see Results point 2.)

Results

Matlab simulation of equalization procedure
Real equalization process using the ADAU1701 computation procedure to correct the original loudspeaker frequency response
FIR filter frequency response into Matlab domain
FIR filter frequency response into ADAU1701 domain (exploiting stimulus/probe blocks)

Questions

As you can see the simulated equalization process and the real one are very different. Also the frequency response of FIR in matlab and in sigmastudio are different expecially on the tail at high frequencies. I think that this mismatch is due to the arithmetic used by ADAU1701 and a PC. In my opinion ADAU1701 is a fixed-point DSP with double precision, isn't it?
How FIR computation into DSP works? What's the correct format of the coefficients in order to achieve a working FIR filtering? I attached the coefficients file as you can see if the decimal format is useful or not (to visualize it better use matlab or notepad++, because windows textfile reader doesn't read newline commands).
What's the wordlength of a fixed-point coefficient admitted by the chip?
How can I convert matlab coefficients in a fixed-point version suitable for sigmaDSP ADAU1701?

I hope you can help me because I'm completely frozen on ths. I made many many tests and measurements without any successful results.
Regards,
Leo.

attachment.zip

Tags: Audio Signal Processors filter sigmastudio SigmaDSP Audio Processors frequency audio adau1701 Show More

0 gr4eme
on Aug 2, 2013 7:52 AM
Hi LeonXP

As a High End loudspeaker designer for 17 years can i ask why you require a flat line response?

Im not sure exactly what your aim is but if it was me i would take the response in a known environment and have the EQ correct any in room response to the known response

Graeme
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0 gr4eme
on Aug 2, 2013 8:14 AM
Loudspeakers are very rarely flat in my experience, mainly because a flat loudspeaker would sound terrible so any one designing would probably never need the ability to do what your asking, just my 2¢
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0 leonxp
on Aug 2, 2013 1:07 PM
I need to flat as best as possible loudspeaker modules (also composite systems) in order to show correction power of ADAU1701 mounted on board of amplifiers I'm working on.
Hi-fi means less "frequency color" as possible right? I know that customers choose louspeakers not only for their power but also for their "color". But this is not my business, I need hi-fi test results.

Regards.

P.s. My measurements are performed in an anechoic room with measurements systems which negelet any reflected sound contribuition.
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0 ADIApproved

on Aug 2, 2013 1:13 PM
Hi Leon:

The difference in your results is due to quantization of your coefficients. The 1701 has a 5.23 fixed point format. To complicate things further the stimluy and probe provide a first approximation view of the transfer function and, although they do take into account the coefficient quantization and correct fixed point number, they do not do so for the actual signal and therefore you might also encounter differences in an actual measurement. The FIR block doesn't use the double precision arithmetic because it would make it very wastefull (double all the operations), for FIR filtering you most likey do not this double precison arithmetic.

To simulate fixed point in Matlab, Mathworks has a fixed point library that you could use. You can also simply quantize your calculated coefficients to a 5.23 number by finding the fractional value that is best represented with a 2^-23 precision.

Hope this helps.

Miguel
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0 ADIApproved

on Aug 2, 2013 1:16 PM
HI again:

By the way, if you try using our Automatic Filter Designer (built into sigmaStudio) you can do the approximaition of speakers to different targets (if you want it flat, you can leave it flat) by approximating biquads instead of FIR. this process will lessen the DSP burden from using many coefficients (typical from FIR filters).

As greme mentions, not sure if flat response should be the target but the tool lets you specify whatever target you want.

Cheers

Miguel
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0 leonxp
on Aug 2, 2013 1:28 PM
Sorry, I respect your job (and I like it very much) and if you want to show me your products I'd glad to see your web site and know more about that.
But think about a composite module of 4 or 6 trasducers into the same loudspeaker. It's quite impossible to produce 6 different trasducers which match exactely the frequency response band you desire. In this circumstance you have to cut overlapping bands and try to flat all of them or some of them. Think to composite modules mounted on loudspeaker of strange shapes don't to common loudspeakers.
I know that loudspeakers, amplification set for live music and so on are cool if they sound in a particular way but this is not my business.

Regards,

Leo.
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0 leonxp
on Aug 2, 2013 4:05 PM
Matlab tools about it I found are related to well-known filters as pass-band, low-pass, etc...
I found something about quantization but I cannot understand how to use the fractional value and exactly what it is. Do you know something about that?

By the way, the procedure I've to test is:

0. B are FIR coefficients vector computed in a common way with matlab

normalize B coefficients with the norm_factor = 2^(ceil(log2(max(abs(B))))), this is the maximum value of B coefficients aprroximated to the nearest power of two of its value, for istance b_max = -5 => norm_factor = 8
So:
norm_factor = 2^(ceil(log2(max(abs(B)))))
B_norm = B/norm_factor

compute the wordlength of quantizer. It's:
wordlength = 2^(DSP_resolution_bit - 1) (in ADAU1701 case what is this resolution 23 or 28???)
For a 16 bit DSP resolution the: wordlength = 2^15 = 32768

compute B_quantized as:
B_quantized = [round(B_norm*wordlength) / wordlength] * norm_fact

My questions are:

what the resolution of ADAU1701 to achieve the optimal wordlength?

how can I use the fractional value, and what is it exactely?

My reference:
http://cnx.org/content/m10813/latest/

Thanks, regards

Leo.
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0 ADIApproved

on Aug 2, 2013 5:49 PM
Hi Leo:

I now recall that regardless of the value you enter in the FIR filter, you can get the quantized value in the output window. So simply copy the output of the capture window of SigmaStudio into Matlab and plot your transfer function again.

Let us know your results.

Regards

Miguel
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0 leonxp

on Aug 2, 2013 7:32 PM

I got the data from the capture (note in my capture window and in the file exportation I read 5.32 data ??? whiat does it mean). Nevertheless data I load into DSP and data I got reading them are a bit different. I post these them.

Original DATA (no quantization)	Captured DATA
0.000185 0.000193 0.000199 0.000205 0.000209 0.000212 0.000213 0.000213 0.000212 0.000210 0.000206 0.000201 0.000195 0.000189 0.000182 0.000175 0.000168 0.000161 0.000155 0.000149 0.000145 0.000142 0.000140 0.000141 0.000143 0.000147 0.000153 0.000161 0.000172 0.000184 0.000199 0.000216 0.000234 0.000254 0.000275 0.000297 0.000319 0.000342 0.000364 0.000386 0.000407 0.000426 0.000444 0.000460 0.000474 0.000485 0.000494 0.000500 0.000504 0.000505 0.000504 0.000501 0.000495 0.000489 0.000481 0.000473 0.000466 0.000458 0.000453 0.000449 0.000447 0.000449 0.000454 0.000463 0.000476 0.000494 0.000516 0.000543 0.000575 0.000611 0.000650 0.000694 0.000739 0.000787 0.000836 0.000885 0.000933 0.000979 0.001021 0.001059 0.001092 0.001118 0.001137 0.001147 0.001148 0.001139 0.001120 0.001091 0.001052 0.001003 0.000945 0.000878 0.000803 0.000722 0.000635 0.000545 0.000452 0.000359 0.000268 0.000180 0.000097 0.000020 -0.000048 -0.000106 -0.000153 -0.000188 -0.000209 -0.000218 -0.000212 -0.000194 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0.004275 0.003434 0.002565 0.001683 0.000802 -0.000063 -0.000899 -0.001694 -0.002436 -0.003117 -0.003729 -0.004267 -0.004729 -0.005114 -0.005425 -0.005667 -0.005847 -0.005974 -0.006062 -0.006122 -0.006171 -0.006224 -0.006299 -0.006414 -0.006584 -0.006827 -0.007158 -0.007590 -0.008135 -0.008800 -0.009591 -0.010510 -0.011555 -0.012720 -0.013994 -0.015363 -0.016807 -0.018304 -0.019826 -0.021342 -0.022818 -0.024216 -0.025496 -0.026618 -0.027538 -0.028214 -0.028604 -0.028666 -0.028362 -0.027657 -0.026516 -0.024914 -0.022827 -0.020240 -0.017140 -0.013526 -0.009402 -0.004778 0.000327 0.005884 0.011861 0.018214 0.024897 0.031854 0.039023 0.046340 0.053734 0.061132 0.068458 0.075636 0.082588 0.089238 0.095512 0.101340 0.106654 0.111394 0.115503 0.118934 0.121646 0.123607 0.124793 0.125189 0.124793 0.123607 0.121646 0.118934 0.115503 0.111394 0.106654 0.101340 0.095512 0.089238 0.082588 0.075636 0.068458 0.061132 0.053734 0.046340 0.039023 0.031854 0.024897 0.018214 0.011861 0.005884 0.000327 -0.004778 -0.009402 -0.013526 -0.017140 -0.020240 -0.022827 -0.024914 -0.026516 -0.027657 -0.028362 -0.028666 -0.028604 -0.028214 -0.027538 -0.026618 -0.025496 -0.024216 -0.022818 -0.021342 -0.019826 -0.018304 -0.016807 -0.015363 -0.013994 -0.012720 -0.011555 -0.010510 -0.009591 -0.008800 -0.008135 -0.007590 -0.007158 -0.006827 -0.006584 -0.006414 -0.006299 -0.006224 -0.006171 -0.006122 -0.006062 -0.005974 -0.005847 -0.005667 -0.005425 -0.005114 -0.004729 -0.004267 -0.003729 -0.003117 -0.002436 -0.001694 -0.000899 -0.000063 0.000802 0.001683 0.002565 0.003434 0.004275 0.005075 0.005818 0.006494 0.007090 0.007597 0.008007 0.008313 0.008511 0.008600 0.008579 0.008450 0.008219 0.007891 0.007474 0.006977 0.006413 0.005792 0.005128 0.004434 0.003724 0.003012 0.002311 0.001635 0.000994 0.000401 -0.000135 -0.000605 -0.001002 -0.001322 -0.001561 -0.001717 -0.001790 -0.001781 -0.001694 -0.001533 -0.001305 -0.001017 -0.000676 -0.000292 0.000126 0.000568 0.001024 0.001485 0.001940 0.002380 0.002798 0.003185 0.003534 0.003841 0.004101 0.004309 0.004465 0.004566 0.004613 0.004608 0.004553 0.004450 0.004305 0.004121 0.003905 0.003661 0.003397 0.003117 0.002829 0.002537 0.002249 0.001969 0.001701 0.001451 0.001221 0.001015 0.000835 0.000682 0.000556 0.000458 0.000388 0.000342 0.000321 0.000321 0.000340 0.000374 0.000421 0.000477 0.000539 0.000602 0.000666 0.000725 0.000778 0.000822 0.000856 0.000877 0.000886 0.000881 0.000862 0.000830 0.000785 0.000729 0.000662 0.000587 0.000506 0.000420 0.000333 0.000245 0.000160 0.000079 0.000005 -0.000061 -0.000117 -0.000161 -0.000194 -0.000212 -0.000218 -0.000209 -0.000188 -0.000153 -0.000106 -0.000048 0.000020 0.000097 0.000180 0.000268 0.000359 0.000452 0.000545 0.000635 0.000722 0.000803 0.000878 0.000945 0.001003 0.001052 0.001091 0.001120 0.001139 0.001148 0.001147 0.001137 0.001118 0.001092 0.001059 0.001021 0.000979 0.000933 0.000885 0.000836 0.000787 0.000739 0.000694 0.000650 0.000611 0.000575 0.000543 0.000516 0.000494 0.000476 0.000463 0.000454 0.000449 0.000447 0.000449 0.000453 0.000458 0.000466 0.000473 0.000481 0.000489 0.000495 0.000501 0.000504 0.000505 0.000504 0.000500 0.000494 0.000485 0.000474 0.000460 0.000444 0.000426 0.000407 0.000386 0.000364 0.000342 0.000319 0.000297 0.000275 0.000254 0.000234 0.000216 0.000199 0.000184 0.000172 0.000161 0.000153 0.000147 0.000143 0.000141 0.000140 0.000142 0.000145 0.000149 0.000155 0.000161 0.000168 0.000175 0.000182 0.000189 0.000195 0.000201 0.000206 0.000210 0.000212 0.000213 0.000213 0.000212 0.000209 0.000205 0.000199 0.000193 0.000185	0,000185012800000000 0,000192999800000000 0,000198960300000000 0,000205040000000000 0,000208973900000000 0,000211954100000000 0,000213027000000000 0,000213027000000000 0,000211954100000000 0,000210046800000000 0,000205993700000000 0,000200986900000000 0,000195026400000000 0,000188946700000000 0,000182032600000000 0,000174999200000000 0,000167965900000000 0,000161051800000000 0,000154972100000000 0,000149011600000000 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These are Images of processing data with the coefficients written as DSP do:

Filter:

Equalization:

0 leonxp

on Aug 2, 2013 7:39 PM

I tried a quantization of coefficients, using 16 bits as length of word these are results (only in Matlab I cannot test the loudspeaker before monday):

Filter Coefficients:

Original Coefficients	Quantized Coefficients
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0.003395 0.003662 0.003906 0.004120 0.004303 0.004448 0.004555 0.004608 0.004616 0.004562 0.004463 0.004311 0.004097 0.003838 0.003532 0.003181 0.002800 0.002380 0.001938 0.001488 0.001022 0.000565 0.000130 -0.000290 -0.000679 -0.001015 -0.001305 -0.001534 -0.001694 -0.001778 -0.001793 -0.001717 -0.001564 -0.001320 -0.000999 -0.000603 -0.000137 0.000404 0.000992 0.001633 0.002312 0.003014 0.003723 0.004433 0.005127 0.005791 0.006416 0.006981 0.007477 0.007889 0.008217 0.008453 0.008575 0.008598 0.008514 0.008316 0.008003 0.007599 0.007088 0.006493 0.005821 0.005074 0.004272 0.003433 0.002563 0.001686 0.000801 -0.000061 -0.000900 -0.001694 -0.002434 -0.003113 -0.003731 -0.004265 -0.004730 -0.005112 -0.005424 -0.005669 -0.005844 -0.005974 -0.006058 -0.006119 -0.006172 -0.006226 -0.006302 -0.006416 -0.006584 -0.006828 -0.007156 -0.007591 -0.008133 -0.008797 -0.009590 -0.010513 -0.011559 -0.012718 -0.013992 -0.015366 -0.016808 -0.018303 -0.019829 -0.021339 -0.022820 -0.024216 -0.025497 -0.026619 -0.027534 -0.028214 -0.028603 -0.028664 -0.028366 -0.027657 -0.026520 -0.024918 -0.022827 -0.020241 -0.017143 -0.013527 -0.009399 -0.004776 0.000328 0.005882 0.011864 0.018211 0.024895 0.031853 0.039024 0.046341 0.053734 0.061134 0.068459 0.075638 0.082588 0.089241 0.095512 0.101341 0.106651 0.111397 0.115501 0.118935 0.121643 0.123604 0.124794 0.125191 0.124794 0.123604 0.121643 0.118935 0.115501 0.111397 0.106651 0.101341 0.095512 0.089241 0.082588 0.075638 0.068459 0.061134 0.053734 0.046341 0.039024 0.031853 0.024895 0.018211 0.011864 0.005882 0.000328 -0.004776 -0.009399 -0.013527 -0.017143 -0.020241 -0.022827 -0.024918 -0.026520 -0.027657 -0.028366 -0.028664 -0.028603 -0.028214 -0.027534 -0.026619 -0.025497 -0.024216 -0.022820 -0.021339 -0.019829 -0.018303 -0.016808 -0.015366 -0.013992 -0.012718 -0.011559 -0.010513 -0.009590 -0.008797 -0.008133 -0.007591 -0.007156 -0.006828 -0.006584 -0.006416 -0.006302 -0.006226 -0.006172 -0.006119 -0.006058 -0.005974 -0.005844 -0.005669 -0.005424 -0.005112 -0.004730 -0.004265 -0.003731 -0.003113 -0.002434 -0.001694 -0.000900 -0.000061 0.000801 0.001686 0.002563 0.003433 0.004272 0.005074 0.005821 0.006493 0.007088 0.007599 0.008003 0.008316 0.008514 0.008598 0.008575 0.008453 0.008217 0.007889 0.007477 0.006981 0.006416 0.005791 0.005127 0.004433 0.003723 0.003014 0.002312 0.001633 0.000992 0.000404 -0.000137 -0.000603 -0.000999 -0.001320 -0.001564 -0.001717 -0.001793 -0.001778 -0.001694 -0.001534 -0.001305 -0.001015 -0.000679 -0.000290 0.000130 0.000565 0.001022 0.001488 0.001938 0.002380 0.002800 0.003181 0.003532 0.003838 0.004097 0.004311 0.004463 0.004562 0.004616 0.004608 0.004555 0.004448 0.004303 0.004120 0.003906 0.003662 0.003395 0.003120 0.002831 0.002541 0.002251 0.001968 0.001701 0.001450 0.001221 0.001015 0.000832 0.000679 0.000557 0.000458 0.000389 0.000343 0.000320 0.000320 0.000343 0.000374 0.000420 0.000481 0.000542 0.000603 0.000664 0.000725 0.000778 0.000824 0.000854 0.000877 0.000885 0.000877 0.000862 0.000832 0.000786 0.000732 0.000664 0.000587 0.000504 0.000420 0.000336 0.000244 0.000160 0.000076 0.000008 -0.000061 -0.000114 -0.000160 -0.000191 -0.000214 -0.000221 -0.000206 -0.000191 -0.000153 -0.000107 -0.000046 0.000023 0.000099 0.000183 0.000267 0.000359 0.000450 0.000542 0.000633 0.000725 0.000801 0.000877 0.000946 0.000999 0.001053 0.001091 0.001122 0.001137 0.001144 0.001144 0.001137 0.001122 0.001091 0.001060 0.001022 0.000977 0.000931 0.000885 0.000839 0.000786 0.000740 0.000694 0.000648 0.000610 0.000572 0.000542 0.000519 0.000496 0.000473 0.000465 0.000450 0.000450 0.000450 0.000450 0.000450 0.000458 0.000465 0.000473 0.000481 0.000488 0.000496 0.000504 0.000504 0.000504 0.000504 0.000504 0.000496 0.000488 0.000473 0.000458 0.000443 0.000427 0.000404 0.000389 0.000366 0.000343 0.000320 0.000298 0.000275 0.000252 0.000237 0.000214 0.000198 0.000183 0.000175 0.000160 0.000153 0.000145 0.000145 0.000137 0.000137 0.000145 0.000145 0.000153 0.000153 0.000160 0.000168 0.000175 0.000183 0.000191 0.000198 0.000198 0.000206 0.000206 0.000214 0.000214 0.000214 0.000214 0.000206 0.000206 0.000198 0.000191 0.000183

Original Coefficients

Quantized Coefficients

0.000185

0.000193

0.000199

0.000205

0.000209

0.000212

0.000213

0.000212

0.000210

0.000206

0.000201

0.000195

0.000189

0.000182

0.000175

0.000168

0.000161

0.000155

0.000149

0.000145

0.000142

0.000140

0.000141

0.000143

0.000147

0.000153

0.000161

0.000172

0.000184

0.000199

0.000216

0.000234

0.000254

0.000275

0.000297

0.000319

0.000342

0.000364

0.000386

0.000407

0.000426

0.000444

0.000460

0.000474

0.000485

0.000494

0.000500

0.000504

0.000505

0.000504

0.000501

0.000495

0.000489

0.000481

0.000473

0.000466

0.000458

0.000453

0.000449

0.000447

0.000449

0.000454

0.000463

0.000476

0.000494

0.000516

0.000543

0.000575

0.000611

0.000650

0.000694

0.000739

0.000787

0.000836

0.000885

0.000933

0.000979

0.001021

0.001059

0.001092

0.001118

0.001137

0.001147

0.001148

0.001139

0.001120

0.001091

0.001052

0.001003

0.000945

0.000878

0.000803

0.000722

0.000635

0.000545

0.000452

0.000359

0.000268

0.000180

0.000097

0.000020

-0.000048

-0.000106

-0.000153

-0.000188

-0.000209

-0.000218

-0.000212

-0.000194

-0.000161

-0.000117

-0.000061

0.000005

0.000079

0.000160

0.000245

0.000333

0.000420

0.000506

0.000587

0.000662

0.000729

0.000785

0.000830

0.000862

0.000881

0.000886

0.000877

0.000856

0.000822

0.000778

0.000725

0.000666

0.000602

0.000539

0.000477

0.000421

0.000374

0.000340

0.000321

0.000342

0.000388

0.000458

0.000556

0.000682

0.000835

0.001015

0.001221

0.001451

0.001701

0.001969

0.002249

0.002537

0.002829

0.003117

0.003397

0.003661

0.003905

0.004121

0.004305

0.004450

0.004553

0.004608

0.004613

0.004566

0.004465

0.004309

0.004101

0.003841

0.003534

0.003185

0.002798

0.002380

0.001940

0.001485

0.001024

0.000568

0.000126

-0.000292

-0.000676

-0.001017

-0.001305

-0.001533

-0.001694

-0.001781

-0.001790

-0.001717

-0.001561

-0.001322

-0.001002

-0.000605

-0.000135

0.000401

0.000994

0.001635

0.002311

0.003012

0.003724

0.004434

0.005128

0.005792

0.006413

0.006977

0.007474

0.007891

0.008219

0.008450

0.008579

0.008600

0.008511

0.008313

0.008007

0.007597

0.007090

0.006494

0.005818

0.005075

0.004275

0.003434

0.002565

0.001683

0.000802

-0.000063

-0.000899

-0.001694

-0.002436

-0.003117

-0.003729

-0.004267

-0.004729

-0.005114

-0.005425

-0.005667

-0.005847

-0.005974

-0.006062

-0.006122

-0.006171

-0.006224

-0.006299

-0.006414

-0.006584

-0.006827

-0.007158

-0.007590

-0.008135

-0.008800

-0.009591

-0.010510

-0.011555

-0.012720

-0.013994

-0.015363

-0.016807

-0.018304

-0.019826

-0.021342

-0.022818

-0.024216

-0.025496

-0.026618

-0.027538

-0.028214

-0.028604

-0.028666

-0.028362

-0.027657

-0.026516

-0.024914

-0.022827

-0.020240

-0.017140

-0.013526

-0.009402

-0.004778

0.000327

0.005884

0.011861

0.018214

0.024897

0.031854

0.039023

0.046340

0.053734

0.061132

0.068458

0.075636

0.082588

0.089238

0.095512

0.101340

0.106654

0.111394

0.115503

0.118934

0.121646

0.123607

0.124793

0.125189

0.124793

0.123607

0.121646

0.118934

0.115503

0.111394

0.106654

0.101340

0.095512

0.089238

0.082588

0.075636

0.068458

0.061132

0.053734

0.046340

0.039023

0.031854

0.024897

0.018214

0.011861

0.005884

0.000327

-0.004778

-0.009402

-0.013526

-0.017140

-0.020240

-0.022827

-0.024914

-0.026516

-0.027657

-0.028362

-0.028666

-0.028604

-0.028214

-0.027538

-0.026618

-0.025496

-0.024216

-0.022818

-0.021342

-0.019826

-0.018304

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-0.012720

-0.011555

-0.010510

-0.009591

-0.008800

-0.008135

-0.007590

-0.007158

-0.006827

-0.006584

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-0.006299

-0.006224

-0.006171

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-0.006062

-0.005974

-0.005847

-0.005667

-0.005425

-0.005114

-0.004729

-0.004267

-0.003729

-0.003117

-0.002436

-0.001694

-0.000899

-0.000063

0.000802

0.001683

0.002565

0.003434

0.004275

0.005075

0.005818

0.006494

0.007090

0.007597

0.008007

0.008313

0.008511

0.008600

0.008579

0.008450

0.008219

0.007891

0.007474

0.006977

0.006413

0.005792

0.005128

0.004434

0.003724

0.003012

0.002311

0.001635

0.000994

0.000401

-0.000135

-0.000605

-0.001002

-0.001322

-0.001561

-0.001717

-0.001790

-0.001781

-0.001694

-0.001533

-0.001305

-0.001017

-0.000676

-0.000292

0.000126

0.000568

0.001024

0.001485

0.001940

0.002380

0.002798

0.003185

0.003534

0.003841

0.004101

0.004309

0.004465

0.004566

0.004613

0.004608

0.004553

0.004450

0.004305

0.004121

0.003905

0.003661

0.003397

0.003117

0.002829

0.002537

0.002249

0.001969

0.001701

0.001451

0.001221

0.001015

0.000835

0.000682

0.000556

0.000458

0.000388

0.000342

0.000321

0.000340

0.000374

0.000421

0.000477

0.000539

0.000602

0.000666

0.000725

0.000778

0.000822

0.000856

0.000877

0.000886

0.000881

0.000862

0.000830

0.000785

0.000729

0.000662

0.000587

0.000506

0.000420

0.000333

0.000245

0.000160

0.000079

0.000005

-0.000061

-0.000117

-0.000161

-0.000194

-0.000212

-0.000218

-0.000209

-0.000188

-0.000153

-0.000106

-0.000048

0.000020

0.000097

0.000180

0.000268

0.000359

0.000452

0.000545

0.000635

0.000722

0.000803

0.000878

0.000945

0.001003

0.001052

0.001091

0.001120

0.001139

0.001148

0.001147

0.001137

0.001118

0.001092

0.001059

0.001021

0.000979

0.000933

0.000885

0.000836

0.000787

0.000739

0.000694

0.000650

0.000611

0.000575

0.000543

0.000516

0.000494

0.000476

0.000463

0.000454

0.000449

0.000447

0.000449

0.000453

0.000458

0.000466

0.000473

0.000481

0.000489

0.000495

0.000501

0.000504

0.000505

0.000504

0.000500

0.000494

0.000485

0.000474

0.000460

0.000444

0.000426

0.000407

0.000386

0.000364

0.000342

0.000319

0.000297

0.000275

0.000254

0.000234

0.000216

0.000199

0.000184

0.000172

0.000161

0.000153

0.000147

0.000143

0.000141

0.000140

0.000142

0.000145

0.000149

0.000155

0.000161

0.000168

0.000175

0.000182

0.000189

0.000195

0.000201

0.000206

0.000210

0.000212

0.000213

0.000212

0.000209

0.000205

0.000199

0.000193

0.000185

0.000183

0.000191

0.000198

0.000206

0.000214

0.000206

0.000198

0.000191

0.000183

0.000175

0.000168

0.000160

0.000153

0.000145

0.000137

0.000145

0.000153

0.000160

0.000175

0.000183

0.000198

0.000214

0.000237

0.000252

0.000275

0.000298

0.000320

0.000343

0.000366

0.000389

0.000404

0.000427

0.000443

0.000458

0.000473

0.000488

0.000496

0.000504

0.000496

0.000488

0.000481

0.000473

0.000465

0.000458

0.000450

0.000465

0.000473

0.000496

0.000519

0.000542

0.000572

0.000610

0.000648

0.000694

0.000740

0.000786

0.000839

0.000885

0.000931

0.000977

0.001022

0.001060

0.001091

0.001122

0.001137

0.001144

0.001137

0.001122

0.001091

0.001053

0.000999

0.000946

0.000877

0.000801

0.000725

0.000633

0.000542

0.000450

0.000359

0.000267

0.000183

0.000099

0.000023

-0.000046

-0.000107

-0.000153

-0.000191

-0.000206

-0.000221

-0.000214

-0.000191

-0.000160

-0.000114

-0.000061

0.000008

0.000076

0.000160

0.000244

0.000336

0.000420

0.000504

0.000587

0.000664

0.000732

0.000786

0.000832

0.000862

0.000877

0.000885

0.000877

0.000854

0.000824

0.000778

0.000725

0.000664

0.000603

0.000542

0.000481

0.000420

0.000374

0.000343

0.000320

0.000343

0.000389

0.000458

0.000557

0.000679

0.000832

0.001015

0.001221

0.001450

0.001701

0.001968

0.002251

0.002541

0.002831

0.003120

0.003395

0.003662

0.003906

0.004120

0.004303

0.004448

0.004555

0.004608

0.004616

0.004562

0.004463

0.004311

0.004097

0.003838

0.003532

0.003181

0.002800

0.002380

0.001938

0.001488

0.001022

0.000565

0.000130

-0.000290

-0.000679

-0.001015

-0.001305

-0.001534

-0.001694

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-0.001320

-0.000999

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-0.000137

0.000404

0.000992

0.001633

0.002312

0.003014

0.003723

0.004433

0.005127

0.005791

0.006416

0.006981

0.007477

0.007889

0.008217

0.008453

0.008575

0.008598

0.008514

0.008316

0.008003

0.007599

0.007088

0.006493

0.005821

0.005074

0.004272

0.003433

0.002563

0.001686

0.000801

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0.000328

0.005882

0.011864

0.018211

0.024895

0.031853

0.039024

0.046341

0.053734

0.061134

0.068459

0.075638

0.082588

0.089241

0.095512

0.101341

0.106651

0.111397

0.115501

0.118935

0.121643

0.123604

0.124794

0.125191

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0.123604

0.121643

0.118935

0.115501

0.111397

0.106651

0.101341

0.095512

0.089241

0.082588

0.075638

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0.061134

0.053734

0.046341

0.039024

0.031853

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0.018211

0.011864

0.005882

0.000328

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-0.003113

-0.002434

-0.001694

-0.000900

-0.000061

0.000801

0.001686

0.002563

0.003433

0.004272

0.005074

0.005821

0.006493

0.007088

0.007599

0.008003

0.008316

0.008514

0.008598

0.008575

0.008453

0.008217

0.007889

0.007477

0.006981

0.006416

0.005791

0.005127

0.004433

0.003723

0.003014

0.002312

0.001633

0.000992

0.000404

-0.000137

-0.000603

-0.000999

-0.001320

-0.001564

-0.001717

-0.001793

-0.001778

-0.001694

-0.001534

-0.001305

-0.001015

-0.000679

-0.000290

0.000130

0.000565

0.001022

0.001488

0.001938

0.002380

0.002800

0.003181

0.003532

0.003838

0.004097

0.004311

0.004463

0.004562

0.004616

0.004608

0.004555

0.004448

0.004303

0.004120

0.003906

0.003662

0.003395

0.003120

0.002831

0.002541

0.002251

0.001968

0.001701

0.001450

0.001221

0.001015

0.000832

0.000679

0.000557

0.000458

0.000389

0.000343

0.000320

0.000343

0.000374

0.000420

0.000481

0.000542

0.000603

0.000664

0.000725

0.000778

0.000824

0.000854

0.000877

0.000885

0.000877

0.000862

0.000832

0.000786

0.000732

0.000664

0.000587

0.000504

0.000420

0.000336

0.000244

0.000160

0.000076

0.000008

-0.000061

-0.000114

-0.000160

-0.000191

-0.000214

-0.000221

-0.000206

-0.000191

-0.000153

-0.000107

-0.000046

0.000023

0.000099

0.000183

0.000267

0.000359

0.000450

0.000542

0.000633

0.000725

0.000801

0.000877

0.000946

0.000999

0.001053

0.001091

0.001122

0.001137

0.001144

0.001137

0.001122

0.001091

0.001060

0.001022

0.000977

0.000931

0.000885

0.000839

0.000786

0.000740

0.000694

0.000648

0.000610

0.000572

0.000542

0.000519

0.000496

0.000473

0.000465

0.000450

0.000458

0.000465

0.000473

0.000481

0.000488

0.000496

0.000504

0.000496

0.000488

0.000473

0.000458

0.000443

0.000427

0.000404

0.000389

0.000366

0.000343

0.000320

0.000298

0.000275

0.000252

0.000237

0.000214

0.000198

0.000183

0.000175

0.000160

0.000153

0.000145

0.000137

0.000145

0.000153

0.000160

0.000168

0.000175

0.000183

0.000191

0.000198

0.000206

0.000214

0.000206

0.000198

0.000191

0.000183

Filter:

Equalization:

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Products Mentioned

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FIR and general filtering on ADAU1701. Hints about fixed point arithmetic!

Aim

Procedure

Results

Questions