How to perform fft
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I have 1000 samples from an experiment with frequency Fs=67890 Hz. How can I perform fft on them? I followed the guide here https://uk.mathworks.com/help/matlab/ref/fft.html but it seems that the dominant frequency is zero which has no physical meaning.
These are my data
x =
0.3551
0.2308
0.3209
0.4527
0.4606
0.4511
0.4925
0.4769
0.5424
0.4698
0.4246
0.4502
0.5823
0.5451
0.4235
0.4062
0.3832
0.2749
0.1591
0.1889
0.4155
0.3840
0.3582
0.1852
0.2677
0.2454
0.2458
0.2100
0.1469
0.1186
0
0.4154
0.4807
0.4320
0.4072
0.3352
0.3357
0.2770
0.2801
0.3578
0.2703
0.3626
0.0998
0.3656
0.2590
0.4388
0.4144
0.2631
0
0.1076
0
0.4535
0.4626
0.4159
0.3686
0.4763
0.2582
0.2961
0.3691
0.3860
0.3875
0.4018
0.4292
0.3921
0.3128
0.4884
0.3153
0.2672
0.3448
0.3787
0.4799
0.3870
0.3534
0.3968
0.3006
0.3119
0.3585
0.1352
0.4154
0.3323
0.3733
0.3232
0.4116
0.3276
0.4852
0.3715
0.3991
0.3766
0.4866
0.3483
0.2736
0.3153
0.4049
0.3774
0.3071
0.3831
0.3992
0.3661
0.3337
0.1616
0.3305
0.4556
0.5053
0.4209
0.2868
0.2666
0.3057
0.4016
0.2579
0.4286
0.1672
0.4614
0.3814
0.4272
0.3374
0.4215
0.4788
0.3943
0.4097
0.3937
0.4230
0.4981
0.4821
0.1748
0.4015
0.5066
0.4959
0.4267
0.4692
0.3354
0.2919
0.5676
0.4875
0.4957
0.4122
0.5627
0.4573
0.3724
0.4320
0.4127
0.3655
0.3132
0.1982
0.2905
0.3757
0.5282
0.4584
0.4669
0.4059
0.3229
0.4696
0.3960
0.5024
0.4505
0.4084
0.4720
0.4251
0.3683
0.3791
0.3650
0.2426
0.3169
0.4405
0.4129
0.4839
0.3578
0.3550
0.4090
0.4063
0.4497
0.5195
0.4645
0.4514
0.4375
0.3405
0.5263
0.4195
0.3746
0.2887
0.4121
0.3987
0.4428
0.4065
0.3340
0.3511
0.3328
0.3698
0.4988
0.3478
0.2817
0.2795
0.4926
0.3976
0.3728
0.4816
0.4690
0.4328
0.6150
0.1455
0.3981
0.3184
0.4321
0.3678
0.3407
0.2930
0.3325
0.5747
0.5205
0.4418
0.4604
0.3597
0.3404
0.3153
0.5779
0.3666
0.3215
0.2842
0.2314
0.2940
0.3745
0.3215
0.2711
0.3004
0.3946
0.3942
0.3256
0.2587
0.3177
0.2474
0.2057
0.4025
0.4435
0.4262
0.3123
0.3033
0.3595
0.3224
0.5162
0.5210
0.5185
0.5082
0.5174
0.4634
0.4224
0.5525
0.4637
0.5132
0.5806
0.3519
0.5952
0.5103
0.4021
0.3890
0.3671
0.5863
0.3946
0.3198
0.1014
0.4934
0.4089
0.5890
0.4601
0.5628
0.5392
0.4553
0.4755
0.5468
0.4478
0.4900
0.3323
0.2200
0.4340
0.4119
0.4075
0.3577
0.5101
0.3585
0.3939
0.4366
0.3738
0.3934
0.4416
0.4464
0.3510
0.3791
0.4289
0.3966
0.3113
0.2998
0.4251
0.4033
0.3393
0.3843
0.4246
0.4224
0.4072
0.2900
0.4400
0.5314
0.4580
0.4382
0.4118
0.4298
0.5275
0.4492
0.4100
0.4098
0.4530
0.4531
0.4177
0.5175
0.2001
0.5330
0.4534
0.4613
0.0637
0.4619
0.5318
0.4129
0.3292
0.3293
0.4428
0.3560
0.4558
0.3736
0.2481
0.3881
0.3586
0.3284
0.0465
0.3070
0.4227
0.3891
0.3911
0.5650
0.3529
0.3481
0.3482
0.3682
0.5319
0.5387
0.1824
0.3062
0.4315
0.4625
0.3685
0.5253
0.4801
0.5584
0.4634
0.5326
0.4494
0.4534
0.4064
0.3226
0.1444
0.4603
0.4277
0
0.3656
0.4511
0.5926
0.4544
0.4301
0.3542
0.3607
0.3684
0.4694
0.5180
0.3940
0.4657
0.3901
0.4060
0.3740
0.3351
0.3571
0.3845
0.3225
0.4296
0.3675
0.4469
0.3926
0.3571
0.3877
0.2835
0.4564
0.4695
0.3038
0.4322
0.3454
0.4157
0.4131
0.3656
0.3244
0.3835
0.3835
0.3669
0.3769
0.3392
0.4072
0.4156
0.4026
0.4092
0.3624
0.4615
0.3921
0.4848
0.4077
0.2904
0.3404
0.3485
0.4472
0.4097
0.3488
0.3555
0.2958
0.1905
0.2594
0.5082
0.3526
0.5096
0.2486
0.3777
0.3662
0.4036
0.4170
0.4132
0.4760
0.4813
0.2767
0.4714
0.3762
0.3883
0.2067
0.1974
0.3166
0.3852
0.2576
0.3949
0.2443
0.3779
0.4300
0.3881
0.3786
0.3516
0.4147
0.3850
0.4277
0.4620
0.4737
0.4113
0.3448
0.3532
0.3431
0.2336
0.4660
0.4304
0.4478
0.2664
0.3472
0.3404
0.3530
0.5004
0.4685
0.4902
0.5056
0.4876
0.3388
0.3673
0.4873
0.3627
0.3553
0.3385
0.3725
0.5111
0.4345
0.3356
0.3316
0.3864
0.3736
0.3033
0.4409
0.4224
0.3873
0.3507
0.3317
0.3222
0.2853
0.3617
0.4143
0.4293
0.3870
0.3259
0.4120
0.3762
0.3981
0.4022
0.3711
0.3616
0.4801
0.3860
0.2593
0.5820
0.4110
0.4032
0.4109
0.3933
0.4776
0.2430
0.4151
0.4863
0.3633
0.1881
0.1723
0.4596
0.3971
0.3804
0.4301
0.2390
0.4319
0.3753
0.4073
0.4224
0.4255
0.4830
0.3504
0.3461
0.1993
0.4117
0.4678
0.4710
0.3577
0.3979
0.3993
0.3446
0.3214
0.3113
0.3695
0.3847
0.4664
0.4420
0.3579
0.5084
0.4741
0.4416
0.4036
0.3741
0.4747
0.5657
0.4787
0.4972
0.3841
0.2781
0.4447
0.5256
0.4557
0.4701
0.4399
0.3622
0.3493
0.3782
0.3784
0.6737
0.5224
0.4507
0.2935
0.4661
0.3368
0.3713
0.4094
0.3704
0.4510
0.3874
0.4808
0.3836
0.4163
0.2954
0.4038
0.3723
0.3454
0.3572
0.2956
0.3123
0.3045
0.3775
0.3586
0.3899
0.3283
0.2579
0.3975
0.3386
0.3333
0.3667
0.2439
0.3291
0.4948
0.4187
0.4469
0.3125
0.2881
0.1765
0.3667
0.4266
0.4227
0.4985
0.3694
0.3063
0.3647
0.3031
0.4227
0.4508
0.3426
0.2608
0.3380
0.4410
0.2822
0.3007
0.2079
0.3175
0.2548
0.2257
0.2664
0.2629
0.3153
0.2829
0.1878
0.2932
0.4240
0.3506
0.3450
0.3436
0.3147
0.4307
0.3297
0.3263
0.2626
0.3670
0.3903
0.3504
0.3635
0.3506
0.3645
0.3349
0.3742
0.4376
0.3087
0.1669
0.5031
0.4398
0.3169
0.1251
0.3737
0.4122
0.3529
0.3419
0.3728
0.3230
0.3516
0.3272
0.4056
0.4307
0.4187
0.3042
0.3735
0.3499
0.4240
0.1846
0.2853
0.2608
0.3536
0.3915
0.4461
0.4830
0.4267
0.2480
0.4508
0.1829
0.2214
0.3592
0.4563
0.2695
0.3125
0.2981
0.4959
0.3519
0.1361
0.3236
0.3682
0.3274
0.4352
0.3589
0.3794
0.3441
0.4345
0.3739
0.3811
0.3532
0.3125
0.4182
0.2854
0.3541
0.3988
0.4035
0.3540
0.3104
0.4531
0.5163
0.5809
0.3362
0.4588
0.4724
0.4871
0.4134
0.4033
0.3325
0.4309
0.3734
0.3137
0.3562
0.4370
0.2704
0.3935
0.3315
0.3020
0.3531
0.2427
0.3931
0.3654
0.3365
0.5205
0.3245
0.6086
0.4521
0.3837
0.4901
0.3527
0.4278
0.2909
0.3649
0.3479
0.2947
0.5558
0.4566
0.5902
0.4304
0.5311
0.5395
0.3745
0.5311
0.3001
0.4030
0.4117
0.3925
0.4652
0.3820
0.2739
0.4634
0.3541
0.3096
0.3282
0.3180
0.2612
0.2147
0.4373
0.4462
0.4324
0.4857
0.2976
0.3247
0.3276
0.3106
0.5885
0.5510
0.3492
0.3284
0.4325
0.4530
0.5664
0.5522
0.4787
0.4568
0.4210
0.5093
0.4775
0.4069
0.4151
0.4295
0.4312
0.3926
0.3863
0.3583
0.4121
0.3848
0.3773
0.3826
0.3374
0.3023
0.3368
0.4261
0.2167
0.4879
0.3032
0.2540
0.5302
0.4484
0.4872
0.3173
0.3800
0.4337
0.3698
0.3272
0.2498
0.3854
0.4042
0.4299
0.4018
0.3248
0.3756
0.3824
0.4029
0.4295
0.3573
0.3036
0.0557
0.4097
0.5186
0.4060
0.3733
0.2700
0.4013
0.2437
0.4369
0.3374
0.3853
0.4096
0.3145
0.3664
0.4738
0.2346
0.3548
0.2804
0.4698
0.4039
0.4628
0.4387
0.3089
0.3981
0.4727
0.4335
0.3591
0.4623
0.3922
0.4100
0.3585
0.4101
0.3834
0.2742
0.2886
0.4118
0.4812
0.4434
0.4607
0.3134
0.0859
0.1066
0.3441
0.2788
0.3310
0.4330
0.3551
0.4324
0.4427
0.3585
0.4497
0.1920
0.3622
0.4184
0.4762
0.4427
0.4545
0.4054
0.4440
0.3977
0.5034
0.5101
0.3951
0.5061
0.4242
0.4591
0.5080
0.4194
0.6229
0.3667
0.4874
0.4718
0.4996
0.2885
0.4989
0.5071
0.4529
0.5001
0.4165
0.4620
0.4430
0.3566
0.3709
0.4315
0.4694
0.3501
0.3343
0.4227
0.3484
0.3737
0.1854
0.4691
0.4328
0.4059
0.4462
0.4397
0.3578
0.3274
0.4586
0.4864
0.5225
0.3509
0.4212
0.4003
0.4854
0.1942
0.4785
0.4362
0.4213
0.4979
0.4989
0.3758
0.4904
0.6655
0.4860
0.4498
0.4712
0.3502
0.3666
0.3871
0.5061
0.3993
0.2872
0.3147
0.3531
0.4126
0.4546
0.4136
0.4674
0.4634
0.4877
0.4136
0.3401
0.4442
0.3997
0.3753
0.4675
0.3769
0.3556
0.3799
0.5048
0.3805
0.4656
0.4621
0.3986
0.2977
0.3280
0.4630
0.4375
0.3109
0.3265
0.4582
0.4432
0.3801
0.4558
0.4408
0.4279
0.3974
0.3856
0.4107
0.4463
0.4646
0.3674
0.4938
0.3389
0.4625
0.3187
0.3233
0.4389
0.3224
0.3140
0.4371
0.3664
0.4664
0.4350
0.4211
0.3415
and here is the code I have used for the fft
fs=67890;
T = 1/fs; % Sampling period
L = 1000; % Length of signal
t = (0:L-1)*T; % Time vector
y = fft(x);
P2 = abs(y/L);
P1 = P2(1:L/2+1);
P1(2:end-1) = 2*P1(2:end-1);
f = fs*(0:(L/2))/L;
subplot(2,1,1), plot(t,x),title('original data'),ylabel('x'),xlabel('t')
subplot(2,1,2), plot(f,P1),title('fft'),ylabel('magnitude'),xlabel('frequency')
This gives me this image
Hope it's clear
5 Comments
Rik
on 23 Feb 2017
To get rid of the 0Hz component, you can subtract the mean from your data, maybe that helps.
How does the result you are getting not work? Differently put: you ask how to perform fft, why is the answer 'with the function fft' incorrect?
Adam
on 23 Feb 2017
The 0-frequency component is simply a measure of the average of your data and suggests it is not very 0-centred. If you have perfectly 0-centred data then the 0-frequency component will also be 0.
You haven't shown any example of what you have done though or what your data looks like so there's not much else to say since you have clearly looked at the fft documentation already and followed an example there.
Efstathios Kontolatis
on 23 Feb 2017
Adam
on 23 Feb 2017
So just do what Rik Wisselink suggests to zero-centre your data or simply remove the 0-frequency component from the final result and plot it without if you just want to look at the frequency spectrum.
Efstathios Kontolatis
on 23 Feb 2017
Accepted Answer
Rik
on 23 Feb 2017
0 votes
[moved from comments]
To remove the 0Hz-component from the analysis, use y=fft(x-mean(x));
More Answers (1)
Pooja Patel
on 23 Feb 2017
0 votes
- amp1 = abs(fft(x1)); %Retain Magnitude
- % amp11 = amp1(1:Nsamps1/2); %Discard Half of Points
- % f11 = Fs*(0:Nsamps1/2-1)/Nsamps1; %Prepare freq data for plot
- f11 = 0:(fs1/Nsamps1):1000; %Prepare freq data for plot
- amp11 = amp1(1:length(f11)); % keep data till 1kHz
- plot(f11,amp11);
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