Subtracting two vectors of different length

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KDRA
KDRA 2019-1-29
评论： KDRA 2019-2-1
Hello,
I am trying to compare two vectors of very different length by using interpolation (R1 - F1). These are values related to the frequency bins described as f_aff and f vectors (respectively). My current code works but it does not seem to do the right thing. See my script below.
I am not sure if I am correct but I think the error maybe be because the frequency vector is non-linear so I am not sure if the linspace here works...
When I plot these two vectors separately without interpolation, the difference is pretty small but then after interpolation it goes up to 20 dB.
I would appreciate your help!
f_aff = [125 129 172 215 258 301 344 387 430 473 516 559 602 645 688 731 774 817 860 903 946 989 1032 1075 1118 1161 1204 1247 1290 1333 1376 1419 1462 1505 1548 1591 1634 1677 1720 1763 1806 1849 1892 1935 1978 2021 2064 2107 2150 2193 2236 2279 2322 2365 2408 2451 2497 2537 2580 2623 2666 2709 2752 2795 2838 2881 2924 2967 3010 3053 3096 3139 3182 3225 3268 3311 3354 3397 3440 3483 3526 3569 3612 3655 3698 3741 3784 3827 3870 3913 3956 3999 4042 4085 4128 4171 4214 4257 4300 4343 4386 4429 4472 4515 4558 4601 4644 4687 4730 4773 4816 4859 4902 4945 4988 5031 5074 5117 5160 5203 5246 5289 5332 5375 5418 5461 5504 5547 5590 5633 5676 5719 5762 5805 5848 5891 5934 5977 6020 6063 6106 6149 6192 6235 6278 6321 6364 6407 6450 6493 6536 6579 6622 6665 6708 6751 6794 6837 6880 6923 6966 7009 7052 7095 7138 7181 7224 7267 7310 7353 7396 7439 7482 7525 7568 7611 7654 7697 7740 7783 7826 7869 7912 7955 8000];
f = [125, 160, 200, 250, 315, 400, 500, 630, 800, 1000, 1250, 1600, 2000, 2500, 3150, 4000, 5000, 6300, 8000, 10000];
F1_m = [35.4 50 57.8 57.1 57.2 64.3 65.1 65.2 66.4 65.0 64.6 68.4 72 73.8 72.4 70.3 66.3 65.1 63.7 65];
R1_m = [46.9495525566315 48.0385256275429 56.7394910936395 59.0526580982104 57.8898823427092 56.5598810922227 58.2073459581807 59.3866454154771 58.3950368323739 58.8199162224362 61.9296747113695 63.0969864811895 60.7879172041026 57.3170848211968 60.7188155387509 62.0582099275805 60.1723427899083 56.9803700421588 55.6347526633159 56.3474293999317 57.4697167980110 59.1332558500579 60.1472787808621 60.0700214652395 58.1676314128097 56.4107148752243 58.4685305240429 60.8140271008369 61.5126142738754 60.4956251086211 59.6556204846324 58.4236301798295 57.9374910794919 60.5622411865936 63.1375533480448 64.9511183524034 64.8476467038119 64.9025455169853 63.4472618963326 61.0155598172182 61.4237963394965 63.6638870733989 64.9954449383057 65.6656491635678 66.5262451579203 66.9105699595665 66.7287029388819 66.2255597367988 65.4700233075733 65.4855983849100 67.2464501321911 69.9080552671495 71.9552205168995 71.8986939021709 71.2182752711739 71.7953224013434 72.0485719479038 71.6554581661854 70.6533058677423 70.7459826221040 72.5498793344994 74.2827882995270 75.1329565759775 75.7420636821961 75.6914519367813 75.2796338178501 74.4716993754235 73.2781974313175 72.3862361067673 73.1483619180440 73.0750739043636 72.7099302183872 72.0222399591912 71.9027602718696 70.8335543208131 70.4076791756693 69.8605791056181 69.6092517365672 68.7526959862595 67.7324282910174 67.7991858416926 68.4551178973679 69.8746112187334 70.9466366085484 70.0428364881271 68.7269740993748 68.4971983333549 67.8397098760714 68.0440389888663 67.8073626318051 67.2347068241060 66.9425225562858 65.8236572406199 64.7565656795052 64.5942847791963 64.4232361865823 65.1980549942284 65.4479025455588 65.0671287009502 64.5758128537930 63.7949152533354 63.0458796308529 62.7355424443258 62.4360128568897 61.4913612591605 60.3833723058361 60.4330285882857 60.9186529157498 61.3391017974483 62.1022050022118 62.5338066666576 62.5875493933869 61.5056000644960 60.1370032732948 59.7234100407571 60.4256524582559 60.7183699531295 59.3473586169763 58.8191038661669 59.4782003376343 60.3960244231483 60.9971961250525 60.8662182325371 60.6295066579305 60.9115791987718 60.5834947987681 59.8773567280509 58.8190898299718 58.3662174037829 57.8211830875231 55.9721517225508 55.4655187820830 55.1357713572842 55.5987703734668 55.4501886343092 55.5926044746766 56.2628681171663 56.2422405693999 56.0066763588240 57.0821192658925 58.4264865255485 58.6712881614999 58.4456620086571 57.9624866349172 58.1616957091606 58.3558387131633 57.7337606307656 57.5354877251610 57.8315275221234 58.0559771099481 57.7420874610169 56.4452817336371 56.6065146047738 57.2900951682665 57.5010422723460 58.0814352999206 58.3130680512442 58.6314234228966 58.4888129562938 58.3346209135367 57.3122257895209 56.4843907798461 56.2327147066294 56.0637890640808 55.3209902146068 55.5382575383832 55.4977169373532 54.7479846374780 55.1323914183025 55.4564144147509 55.0461578255621 54.2568171478017 53.9245645352059 54.5689992544002 54.8731771104946 54.3875880321623 53.2008885786154 52.8017592144459 51.9694080931309 51.6435567214985 51.1985111648497 50.4133912244660 50.0592902032103 50.2735671563406 50.4594062567421];
F1_m = F1_m([1:19]); %cutting the last value for 10kHz
xo2 = 1:numel(F1_m);
xi2 = linspace(1, numel(F1_m), length(R1_m));
F1_int = interp1(xo2, F1_m, xi2);
semilogx(f_aff, R1_m-F1_int)

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回答（2 个）

KSSV
KSSV 2019-1-29
Use interp1 and get them to same dimensions.
KDRA
KDRA 2019-1-30
Any other ideas?
  4 个评论
显示 2更早的评论
KDRA
KDRA 2019-1-30
I also tried resample but it works in a similar way. I am pretty sure this is due to the frequency vector f_aff and its frequencies distribution... Still, not sure what the solution would be.
One of the idea was to create a new frequency vector with the linspace distribution and 185 values and the dame range, however, this will change the shape of everything and I need to keep that.
KDRA
KDRA 2019-2-1
for the future generations, I managed to compare these two curves with the code below:
F1_m = F1_m([1:19]); %cutting the last value for 10kHz
F1_int = interp1(f, F1_m, f_aff)
F1_diff = R1_m - F1_int;
semilogx(f_aff, R1_m-F1_int)

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