Matlab - ESCOGER LA MENOR VECTOR DE VARIOS VECTORES

 
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ESCOGER LA MENOR VECTOR DE VARIOS VECTORES

Publicado por Fausto (4 intervenciones) el 13/10/2019 03:02:51
Un cordial saludo tengo varios datos de vectores que contienen cada uno 9 elementos y necesito extraer el menor vector de 9 elementos.

Columns 1 through 11

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
1.0140 1.0160 1.0177 1.0194 1.0208 1.0220 1.0230 1.0238 1.0244 1.0248 1.0250
1.0227 1.0236 1.0243 1.0248 1.0250 1.0250 1.0247 1.0241 1.0234 1.0224 1.0211
0.9240 0.9285 0.9326 0.9362 0.9394 0.9423 0.9448 0.9471 0.9490 0.9507 0.9521
0.9097 0.9103 0.9104 0.9099 0.9089 0.9074 0.9056 0.9033 0.9005 0.8974 0.8939
0.7289 0.7440 0.7579 0.7708 0.7828 0.7939 0.8043 0.8141 0.8232 0.8317 0.8396
0.9923 0.9931 0.9935 0.9935 0.9931 0.9924 0.9913 0.9898 0.9880 0.9859 0.9833
0.9686 0.9702 0.9713 0.9720 0.9724 0.9723 0.9720 0.9712 0.9701 0.9687 0.9669
0.9676 0.9700 0.9718 0.9732 0.9740 0.9744 0.9744 0.9740 0.9732 0.9719 0.9703

Columns 12 through 22

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
1.0250 1.0247 1.0242 1.0236 1.0226 1.0215 1.0201 1.0185 1.0167 1.0146 1.0123
1.0196 1.0178 1.0158 1.0135 1.0110 1.0082 1.0051 1.0018 0.9983 0.9944 0.9903
0.9533 0.9542 0.9549 0.9554 0.9556 0.9556 0.9554 0.9549 0.9543 0.9534 0.9523
0.8900 0.8858 0.8811 0.8761 0.8708 0.8650 0.8589 0.8525 0.8456 0.8384 0.8309
0.8470 0.8539 0.8604 0.8663 0.8719 0.8769 0.8816 0.8858 0.8896 0.8930 0.8959
0.9805 0.9772 0.9737 0.9698 0.9655 0.9609 0.9560 0.9507 0.9450 0.9390 0.9327
0.9648 0.9624 0.9596 0.9566 0.9531 0.9494 0.9453 0.9410 0.9362 0.9312 0.9258
0.9682 0.9658 0.9631 0.9599 0.9564 0.9525 0.9483 0.9436 0.9387 0.9334 0.9277

Columns 23 through 33

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
1.0097 1.0069 1.0038 1.0004 0.9968 0.9929 0.9887 0.9842 0.9794 0.9743 0.9689
0.9860 0.9813 0.9764 0.9712 0.9657 0.9600 0.9539 0.9476 0.9410 0.9340 0.9268
0.9510 0.9495 0.9477 0.9458 0.9436 0.9412 0.9386 0.9358 0.9327 0.9294 0.9259
0.8230 0.8147 0.8060 0.7970 0.7876 0.7779 0.7678 0.7573 0.7464 0.7351 0.7235
0.8985 0.9007 0.9025 0.9039 0.9049 0.9055 0.9057 0.9055 0.9049 0.9039 0.9025
0.9260 0.9190 0.9116 0.9038 0.8957 0.8873 0.8784 0.8693 0.8597 0.8498 0.8396
0.9201 0.9141 0.9077 0.9010 0.8939 0.8865 0.8788 0.8707 0.8623 0.8535 0.8444
0.9217 0.9153 0.9085 0.9015 0.8940 0.8863 0.8781 0.8697 0.8608 0.8517 0.8422

Columns 34 through 44

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.9632 0.9572 0.9509 0.9442 0.9371 0.9297 0.9220 0.9139 0.9054 0.8966 0.8874
0.9193 0.9115 0.9033 0.8949 0.8862 0.8771 0.8678 0.8581 0.8482 0.8379 0.8274
0.9222 0.9183 0.9141 0.9096 0.9050 0.9001 0.8950 0.8896 0.8840 0.8781 0.8720
0.7115 0.6991 0.6863 0.6731 0.6596 0.6456 0.6313 0.6166 0.6015 0.5860 0.5702
0.9007 0.8985 0.8959 0.8928 0.8893 0.8854 0.8811 0.8763 0.8711 0.8655 0.8594
0.8290 0.8180 0.8067 0.7950 0.7829 0.7705 0.7578 0.7447 0.7313 0.7176 0.7035
0.8349 0.8251 0.8149 0.8044 0.7935 0.7822 0.7706 0.7587 0.7464 0.7338 0.7208
0.8323 0.8222 0.8117 0.8008 0.7897 0.7782 0.7665 0.7544 0.7421 0.7295 0.7166

Columns 45 through 55

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.8778 0.8678 0.8575 0.8468 0.8358 0.8244 0.8128 0.8008 0.7886 0.7762 0.7636
0.8166 0.8055 0.7941 0.7826 0.7708 0.7589 0.7468 0.7346 0.7223 0.7101 0.6979
0.8657 0.8591 0.8523 0.8452 0.8379 0.8304 0.8227 0.8147 0.8065 0.7982 0.7896
0.5540 0.5374 0.5205 0.5032 0.4857 0.4678 0.4497 0.4313 0.4127 0.3939 0.3750
0.8528 0.8458 0.8383 0.8304 0.8220 0.8131 0.8038 0.7940 0.7838 0.7731 0.7620
0.6892 0.6746 0.6597 0.6446 0.6293 0.6138 0.5982 0.5825 0.5668 0.5511 0.5355
0.7076 0.6940 0.6801 0.6660 0.6516 0.6370 0.6223 0.6073 0.5923 0.5773 0.5622
0.7035 0.6902 0.6767 0.6630 0.6492 0.6353 0.6214 0.6074 0.5935 0.5798 0.5662

Columns 56 through 66

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.7509 0.7383 0.7257 0.7134 0.7015 0.6900 0.6794 0.6696 0.6611 0.6539 0.6484
0.6859 0.6741 0.6626 0.6516 0.6413 0.6316 0.6230 0.6154 0.6092 0.6044 0.6012
0.7809 0.7720 0.7630 0.7539 0.7447 0.7355 0.7264 0.7173 0.7083 0.6996 0.6911
0.3559 0.3369 0.3178 0.2989 0.2802 0.2617 0.2437 0.2262 0.2094 0.1935 0.1785
0.7505 0.7385 0.7262 0.7135 0.7004 0.6871 0.6735 0.6597 0.6459 0.6320 0.6181
0.5201 0.5050 0.4903 0.4761 0.4626 0.4500 0.4383 0.4279 0.4188 0.4114 0.4057
0.5473 0.5325 0.5180 0.5040 0.4904 0.4776 0.4656 0.4547 0.4450 0.4367 0.4299
0.5529 0.5399 0.5275 0.5156 0.5045 0.4942 0.4850 0.4769 0.4703 0.4651 0.4615

Columns 67 through 77

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.6446 0.6425 0.6423 0.6437 0.6467 0.6509 0.6562 0.6622 0.6688 0.6754 0.6816
0.5997 0.5999 0.6016 0.6047 0.6090 0.6143 0.6204 0.6268 0.6334 0.6396 0.6449
0.6829 0.6752 0.6679 0.6609 0.6544 0.6481 0.6421 0.6362 0.6304 0.6244 0.6180
0.1647 0.1520 0.1405 0.1303 0.1212 0.1131 0.1059 0.0995 0.0939 0.0887 0.0841
0.6045 0.5910 0.5778 0.5648 0.5520 0.5392 0.5263 0.5130 0.4991 0.4839 0.4669
0.4018 0.3998 0.3996 0.4010 0.4038 0.4079 0.4130 0.4188 0.4251 0.4315 0.4375
0.4248 0.4214 0.4196 0.4193 0.4202 0.4223 0.4253 0.4288 0.4326 0.4362 0.4392
0.4595 0.4592 0.4603 0.4627 0.4663 0.4707 0.4757 0.4811 0.4864 0.4913 0.4950

Columns 78 through 88

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.6862 0.6865 0.6794 0.6677 0.6542 0.6399 0.6252 0.6102 0.5951 0.5799 0.5648
0.6478 0.6453 0.6341 0.6182 0.6006 0.5822 0.5632 0.5438 0.5239 0.5036 0.4830
0.6107 0.6023 0.5937 0.5870 0.5817 0.5773 0.5734 0.5699 0.5667 0.5638 0.5612
0.0798 0.0759 0.0732 0.0719 0.0713 0.0713 0.0717 0.0724 0.0736 0.0751 0.0771
0.4465 0.4210 0.3936 0.3711 0.3526 0.3365 0.3219 0.3084 0.2957 0.2834 0.2713
0.4421 0.4429 0.4372 0.4272 0.4158 0.4036 0.3911 0.3784 0.3656 0.3528 0.3401
0.4402 0.4367 0.4264 0.4128 0.3983 0.3835 0.3685 0.3535 0.3384 0.3233 0.3083
0.4963 0.4920 0.4797 0.4637 0.4466 0.4291 0.4113 0.3933 0.3752 0.3568 0.3383

Columns 89 through 99

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.5498 0.5352 0.5211 0.5080 0.4966 0.4889 0.4889 0.4991 0.5141 0.5308 0.5479
0.4619 0.4406 0.4189 0.3971 0.3755 0.3553 0.3404 0.3373 0.3431 0.3533 0.3659
0.5587 0.5564 0.5544 0.5527 0.5515 0.5511 0.5522 0.5553 0.5590 0.5628 0.5668
0.0798 0.0832 0.0876 0.0935 0.1018 0.1140 0.1324 0.1544 0.1748 0.1933 0.2105
0.2594 0.2475 0.2353 0.2227 0.2094 0.1949 0.1797 0.1673 0.1591 0.1536 0.1496
0.3276 0.3155 0.3038 0.2932 0.2841 0.2784 0.2796 0.2899 0.3045 0.3204 0.3368
0.2933 0.2786 0.2641 0.2503 0.2375 0.2273 0.2230 0.2280 0.2385 0.2513 0.2652
0.3195 0.3006 0.2816 0.2625 0.2436 0.2259 0.2126 0.2090 0.2130 0.2208 0.2306

Columns 100 through 110

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.5651 0.5822 0.5991 0.6157 0.6321 0.6482 0.6639 0.6794 0.6945 0.7093 0.7237
0.3800 0.3951 0.4108 0.4271 0.4436 0.4604 0.4774 0.4945 0.5117 0.5288 0.5460
0.5707 0.5746 0.5785 0.5824 0.5863 0.5902 0.5941 0.5979 0.6018 0.6056 0.6094
0.2267 0.2423 0.2573 0.2718 0.2859 0.2997 0.3132 0.3264 0.3394 0.3522 0.3648
0.1466 0.1444 0.1427 0.1415 0.1407 0.1402 0.1399 0.1399 0.1400 0.1404 0.1410
0.3534 0.3700 0.3865 0.4030 0.4193 0.4354 0.4515 0.4673 0.4830 0.4985 0.5138
0.2797 0.2945 0.3096 0.3247 0.3399 0.3552 0.3704 0.3856 0.4007 0.4157 0.4307
0.2418 0.2538 0.2664 0.2796 0.2930 0.3068 0.3208 0.3349 0.3492 0.3635 0.3780

Columns 111 through 121

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.7379 0.7516 0.7651 0.7782 0.7910 0.8034 0.8155 0.8272 0.8386 0.8496 0.8603
0.5631 0.5801 0.5970 0.6137 0.6304 0.6468 0.6630 0.6790 0.6948 0.7104 0.7256
0.6132 0.6170 0.6208 0.6246 0.6283 0.6321 0.6358 0.6395 0.6432 0.6470 0.6507
0.3771 0.3893 0.4014 0.4132 0.4249 0.4365 0.4479 0.4591 0.4702 0.4812 0.4920
0.1417 0.1426 0.1436 0.1448 0.1461 0.1475 0.1491 0.1508 0.1526 0.1546 0.1567
0.5289 0.5438 0.5585 0.5730 0.5872 0.6013 0.6151 0.6287 0.6421 0.6552 0.6681
0.4456 0.4603 0.4749 0.4894 0.5037 0.5179 0.5319 0.5457 0.5594 0.5729 0.5862
0.3924 0.4069 0.4213 0.4358 0.4502 0.4645 0.4788 0.4930 0.5071 0.5210 0.5349

Columns 122 through 132

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.8707 0.8807 0.8903 0.8997 0.9086 0.9173 0.9256 0.9335 0.9411 0.9484 0.9553
0.7407 0.7554 0.7698 0.7839 0.7976 0.8111 0.8241 0.8369 0.8492 0.8612 0.8728
0.6543 0.6580 0.6617 0.6653 0.6690 0.6726 0.6763 0.6799 0.6835 0.6871 0.6907
0.5027 0.5132 0.5236 0.5339 0.5440 0.5540 0.5639 0.5736 0.5832 0.5926 0.6019
0.1589 0.1612 0.1636 0.1662 0.1688 0.1716 0.1746 0.1776 0.1808 0.1841 0.1876
0.6808 0.6932 0.7053 0.7172 0.7288 0.7402 0.7513 0.7622 0.7728 0.7831 0.7931
0.5993 0.6121 0.6248 0.6373 0.6495 0.6615 0.6733 0.6848 0.6961 0.7071 0.7179
0.5486 0.5621 0.5755 0.5887 0.6017 0.6146 0.6272 0.6396 0.6518 0.6638 0.6755

Columns 133 through 143

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
0.9619 0.9682 0.9741 0.9797 0.9850 0.9899 0.9945 0.9987 1.0027 1.0063 1.0096
0.8840 0.8948 0.9052 0.9152 0.9248 0.9339 0.9426 0.9509 0.9588 0.9662 0.9732
0.6943 0.6979 0.7015 0.7051 0.7087 0.7123 0.7159 0.7195 0.7231 0.7267 0.7303
0.6111 0.6201 0.6290 0.6378 0.6464 0.6549 0.6633 0.6715 0.6796 0.6876 0.6954
0.1912 0.1949 0.1988 0.2028 0.2070 0.2113 0.2158 0.2205 0.2253 0.2303 0.2355
0.8028 0.8123 0.8215 0.8304 0.8390 0.8473 0.8553 0.8630 0.8705 0.8776 0.8844
0.7284 0.7387 0.7487 0.7584 0.7679 0.7771 0.7860 0.7946 0.8030 0.8111 0.8189
0.6870 0.6982 0.7092 0.7199 0.7303 0.7405 0.7503 0.7599 0.7692 0.7782 0.7869

Columns 144 through 154

1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400 1.0400
1.0125 1.0152 1.0175 1.0195 1.0212 1.0225 1.0236 1.0244 1.0248 1.0250 1.0249
0.9797 0.9858 0.9914 0.9966 1.0014 1.0057 1.0096 1.0130 1.0160 1.0185 1.0206
0.7339 0.7376 0.7412 0.7449 0.7487 0.7524 0.7562 0.7600 0.7640 0.7679 0.7720
0.7031 0.7107 0.7182 0.7255 0.7327 0.7398 0.7468 0.7537 0.7604 0.7671 0.7737
0.2410 0.2466 0.2524 0.2585 0.2649 0.2715 0.2784 0.2856 0.2931 0.3010 0.3093
0.8910 0.8972 0.9032 0.9088 0.9142 0.9193 0.9240 0.9285 0.9327 0.9366 0.9402
0.8264 0.8336 0.8405 0.8472 0.8536 0.8597 0.8655 0.8710 0.8763 0.8813 0.8861
0.7953 0.8033 0.8111 0.8186 0.8257 0.8326 0.8392 0.8454 0.8514 0.8570 0.8624

Column 155

1.0400
1.0244
1.0223
0.7761
0.7803
0.3181
0.9436
0.8906
0.8675
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Imágen de perfil de JOSE JEREMIAS CABALLERO
Val: 8.147
Oro
Ha mantenido su posición en Matlab (en relación al último mes)
Gráfica de Matlab

ESCOGER LA MENOR VECTOR DE VARIOS VECTORES

Publicado por JOSE JEREMIAS CABALLERO (5618 intervenciones) el 13/10/2019 03:30:27
Podría poner un ejemplo muy pequeño, donde halla lo que desea.


Saludos
JOSE JEREMIAS CABALLERO
Asesor de Proyectos con Matlab
Servicios de programación matlab
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