将数据在matlab展示

一，将txt文件中的十六进制数据展示，注数据没有带0x

1，数据

00 00 83 ff ff ff ff f3 a3 86 86 8a 8c 8c 8c 8a 88 87 86 85 84 83 84 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 82 82 83 82 83 83 83 83 83 83 83 83 83 83 83 cd ec fe e8 d4 be b0 a0 95 8a 86 84 83 83 83 83 83 83 83 82 82 82 83 82 83 82 83 83 83 82 82 82 82 82 82 82 83 83 83 82 82 82 83 82 82 83 82 82 83 82 83 82 82 82 83 83 83 83 83 83 82 82 82 83 83 83 83 82 83 82 82 83 83 83 93 ac a3 a0 a7 a5 a7 a3 9a 94 8e 89 86 84 83 83 83 83 83 82 82 82 82 82 83 82 83 82 82 82 82 82 82 82 82 83 82 82 82 82 82 82 82 83 82 82 82 82 83 83 82 82 83 82 82 82 82 83 82 83 82 82 82 82 82 82 83 82 82 83 83 82 83 82 8b 96 9a 9d 98 92 89 88 87 87 88 87 85 85 84 83 82 83 82 82 82 82 82 82 83 82 82 82 82 82 83 82 83 82 82 82 82 82 82 82 82 82 82 82 82 82 83 83 82 82 82 82 82 83 82 82 82 82 82 82 83 82 82 82 83 82 82 83 83 82 82 82 82 82 84 8c 92 8c 89 8a 8e 8c 8b 88 87 86 85 83 83 83 82 82 82 82 82 82 82 83 82 82 82 82 83 82 82 82 82 82 82 82 82 83 82 82 82 82 83 82 83 82 82 83 82 82 82 82 83 83 82 82 83 82 83 82 82 82 82 83 83 82 82 83 83 82 83 82 82 82 83 8b 89 87 88 8b 88 87 86 86 86 86 85 84 84 83 83 83 83 82 82 82 82 82 82 82 83 82 83 82 82 82 82 82 83 82 83 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 83 82 82 82 82 82 82 82 83 83 83 83 83 82 83 82 82 82 82 82 82 82 82 85 86 86 88 86 86 85 85 84 83 83 83 83 83 83 83 83 83 83 83 83 82 83 83 82 82 82 83 82 83 83 82 82 82 83 83 82 82 83 83 82 82 82 82 83 82 82 82 82 83 82 82 83 83 82 83 83 83 82 82 82 83 82 82 82 82 83 82 83 82 83 83 82 83 84 84 85 86 84 84 83 83 83 83 83 83 83 83 83 82 82 83 83 83 83 83 83 82 82 82 82 82 82 83 83 83 83 83 82 83 82 82 83 83 83 82 83 83 82 83 82 82 82 83 83 83 82 83 83 83 82 83 83 82 82 83 83 83 83 82 82 82 83 83 82 83 82 82 83 83 83 84 83 83 83 83 83 83 83 83 83 83 83 83 83 83 82 82 83 82 83 82 83 83 83 83 82 83 82 82 83 83 83 83 82 82 82 83 83 83 83 82 83 82 83 82 83 83 83 82 82 82 83 82 83 82 83 82 83 83 83 83 82 82 82 83 83 83 82 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 82 83 83 82 83 82 83 83 82 83 82 83 82 83 82 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83

2，代码

type displaydata.m
%clf;
a=textread('D:\111\666.txt','%s');
alpha=hex2dec(a);
figure(5);
plot(alpha,'-')

3，展示

 二，将txt文件中的十进制数据展示

1，数据中的data0.txt

1.605 1.407 1.048 0.848 1.009 1.355 1.598 1.480 1.134 0.862 0.937 1.262 1.566 1.544 1.233 0.901 0.883 1.166 1.517 1.586 1.325 0.963 0.846 1.085 1.441 1.606 1.405 1.045 0.847 1.006 1.356 1.598 1.480 1.133 0.860 0.940 1.267 1.566 1.540 1.229 0.902 0.881 1.173 1.515 1.588 1.316 0.960 0.851 1.086 1.449 1.607 1.400 1.043 0.848 1.005 1.358 1.601 1.474 1.135 0.860 0.935 1.266 1.569 1.536 1.225 0.904 0.882 1.174 1.518 1.582 1.314 0.964 0.848 1.094 1.449 1.603 1.400 1.040 0.837 1.009 1.366 1.598 1.473 1.131 0.855 0.936 1.271 1.570 1.537 1.226 0.899 0.882 1.176 1.519 1.580 1.312 0.960 0.854 1.093 1.446 1.603 1.391 1.038 0.843 1.012 1.363 1.600 1.474 1.125 0.860 0.938 1.274 1.574 1.538 1.225 0.894 0.881 1.179 1.521 1.579 1.311 0.960 0.856 1.096 1.449 1.600 1.392 1.041 0.843 1.018 1.366 1.597 1.470 1.126 0.857 0.947 1.278 1.573 1.532 1.217 0.893 0.893 1.181 1.522 1.583 1.312 0.959 0.847 1.092 1.453 1.605 1.394 1.035 0.844 1.016 1.370 1.601 1.466 1.121 0.856 0.941 1.279 1.569 1.529 1.212 0.895 0.886 1.183 1.525 1.579 1.305 0.955 0.852 1.095 1.453 1.603 1.393 1.030 0.838 1.018 1.370 1.598 1.469 1.123 1.406 1.042 0.841 1.009 1.358 1.594 1.474 1.134 0.862 0.938 1.268 1.572 1.537 1.228 0.903 0.881 1.173 1.522 1.586 1.316 0.960 0.848 1.090 1.444 1.609 1.403 1.043 0.844 1.005 1.359 1.596 1.488 1.130 0.860 0.939 1.273 1.573 1.536 1.225 0.905 0.880 1.176 1.521 1.582 1.312 0.964 0.852 1.090 1.453 1.603 1.395 1.037 0.838 1.013 1.366 1.599 1.477 1.131 0.856 0.938 1.271 1.568 1.536 1.225 0.897 0.885 1.180 1.521 1.582 1.311 0.960 0.855 1.098 1.455 1.604 1.397 1.036 0.838 1.017 1.368 1.599 1.475 1.126 0.856 0.942 1.271 1.572 1.538 1.220 0.901 0.883 1.179 1.524 1.580 1.316 0.961 0.852 1.098 1.452 1.600 1.395 1.034 0.844 1.018 1.367 1.602 1.464 1.121 0.855 0.941 1.277 1.576 1.534 1.221 0.899 0.885 1.184 1.520 1.585 1.308 0.960 0.856 1.095 1.454 1.599 1.391 1.031 0.839 1.013 1.366 1.603 1.465 1.120 0.860 0.944 1.287 1.573 1.532 1.213 0.892 0.889 1.184 1.525 1.581 1.307 0.955 0.852 1.097 1.458 1.603 1.391 1.047 0.839 1.018 1.377 1.598 1.466 1.119 0.858 0.945 1.284 1.569 1.532 1.211 0.894 0.889 1.192 1.524 1.582 1.301 0.951 0.849 1.101 1.457 1.608 1.387 1.039 0.839 1.022 1.376 1.602 1.467 1.118 0.858 0.948 1.287 1.572 1.532 1.211 0.892 0.893 1.188 1.527 1.578 1.301 0.952 0.851 1.109 1.465 1.602 1.388 1.024 0.843 1.022 1.385 1.608 1.462 1.117 0.850 0.951 1.286 1.572 1.531 1.210 0.893 0.895 1.190 1.531 1.573 1.304 0.954 0.854 1.108 1.461 1.602 1.382 1.022 0.840 1.025 1.384 1.602 1.459 1.113 0.849 0.954 1.287 1.591 1.532 1.205 0.893 0.893 1.191 1.532 1.572 1.300 0.949 0.858 1.104 1.463 1.603 1.379 1.022 0.843 1.027 1.384 1.600 1.458 1.107 0.854 0.954 1.296 1.577 1.530 1.200 0.889 0.893 1.192 1.536 1.578 1.293 0.947 0.849 1.105 1.466 1.598 1.382 1.024 0.840 1.034 1.380 1.603 1.453 1.109 0.856 0.953 1.297 1.576 1.519 1.199 0.887 0.898 1.204 1.532 1.577 1.293 0.944 0.856 1.109 1.471 1.601 1.378 1.021 0.840 1.033 1.383 1.600 1.452 1.108 0.852 0.956 1.296 1.582 1.519 1.201 0.885 0.900 1.202 1.537 1.569 1.291 0.943 0.856 1.117 1.470 1.605 1.373 1.016 0.838 1.029 1.390 1.602 1.457 1.102 0.854 0.961 1.296 1.583 1.518 1.199 0.889 0.897 1.207 1.538 1.571 1.285 0.942 0.856 1.119 1.469 1.607 1.372 1.016 0.842 1.035 1.391 1.603 1.455 1.098 0.848 0.962 1.299 1.583 1.524 1.196 0.884 0.899 1.206 1.533 1.575 1.291 0.939 0.856 1.118 1.474 1.596 1.369 1.015 0.841 1.036 1.396 1.601 1.453 1.099 0.849 0.966 1.301 1.584 1.516 1.192 0.883 0.898 1.208 1.540 1.571 1.294 0.937 0.858 1.117 1.471 1.602 1.369 1.014 0.844 1.040 1.397 1.603 1.449 1.097 0.848 0.964 1.306 1.588 1.515 1.191 0.881 0.905 1.209 1.545 1.570 1.283 0.936 0.856 1.123 1.474 1.600 1.366 1.007 0.847 1.041 1.397 1.600 1.442 1.093 0.853 0.966 1.309 1.581 1.512 1.189 0.883 0.899 1.217 1.545 1.569 1.275 0.933 0.860 1.121 1.482 1.597 1.371 1.005 0.843 1.044 1.398 1.607 1.443 1.098 0.852 0.965 1.312 1.584 1.508 1.186 0.877 0.908 1.217 1.540 1.567 1.275 0.931 0.864 1.124 1.482 1.601 1.359 1.001 0.843 1.040 1.402 1.602 1.441 1.090 0.847 0.967 1.312 1.583 1.517 1.184 0.877 0.905 1.213 1.544 1.563 1.279 0.928 0.861 1.131 1.479 1.600 1.357 1.003 0.840 1.052 1.403 1.607 1.442 1.084 0.846 0.972 1.312 1.585 1.514 1.182 0.877 0.910 1.219 1.542 1.565 1.275 0.931 0.866 1.127 1.480 1.597 1.358 0.999 0.843 1.047 1.407 1.601 1.439 1.081 0.844 0.977 1.316 1.586 1.511 1.175 0.881 0.909 1.225 1.545 1.568 1.274 0.927 0.864 1.129 1.484 1.599 1.359 1.003 0.844 1.053 1.409 1.602 1.439 1.087 0.847 0.976 1.328 1.587 1.507 1.174 0.872 0.907 1.228 1.547 1.567 1.270 0.923 0.864 1.133 1.489 1.597 1.354 1.000 0.843 1.051 1.411 1.602 1.436 1.084 0.844 0.981 1.316 1.586 1.507 1.173 0.878 0.914 1.225 1.548 1.562 1.262 0.923 0.867 1.137 1.491 1.601 1.351 0.997 0.844 1.052 1.416 1.608 1.431 1.082 0.847 0.976 1.325 1.586 1.507 1.170 0.877 0.912 1.230 1.550 1.559 1.267 0.926 0.867 1.145 1.488 1.593 1.353 0.989 0.845 1.055 1.414 1.608 1.428 1.076 0.846 0.984 1.323 1.590 1.506 1.167 0.870 0.911 1.233 1.546 1.558 1.263 0.924 0.867 1.144 1.490 1.592 1.346 0.991 0.844 1.063 1.416 1.606 1.424 1.071 0.846 0.983 1.328 1.591 1.505 1.166 0.869 0.914 1.236 1.552 1.564 1.265 0.920 0.872 1.144 1.495 1.596 1.348 0.993 0.844 1.060 1.420 1.606 1.426 1.071 0.846 0.986 1.335 1.590 1.499 1.164 0.866 0.918 1.234 1.556 1.561 1.256 0.922 0.867 1.142 1.499 1.592 1.349 0.985 0.843 1.063 1.419 1.607 1.422 1.076 0.846 0.989 1.333 1.590 1.495 1.159 0.872 0.917 1.242 1.555 1.556 1.255 0.915 0.872 1.150 1.496 1.598 1.343 0.983 0.844 1.061 1.424 1.605 1.429 1.068 0.850 0.988 1.337 1.588 1.492 1.159 0.871 0.918 1.244 1.559 1.553 1.250 0.918 0.869 1.153 1.498 1.594 1.341 0.980 0.846 1.065 1.424 1.612 1.420 1.066 0.840 0.989 1.336 1.590 1.499 1.157 0.873 0.920 1.241 1.558 1.549 1.251 0.916 0.875 1.154 1.503 1.593 1.340 0.984 0.843 1.075 1.432 1.606 1.418 1.060 0.844 0.989 1.341 1.591 1.497 1.150 0.867 0.920 1.244 1.560 1.556 1.249 0.918 0.873 1.152 1.507 1.591 1.334 0.993 0.845 1.076 1.430 1.602 1.419 1.061 0.840 0.996 1.343 1.594 1.492 1.149 0.863 0.927 1.246 1.557 1.554 1.246 0.909 0.873 1.156 1.506 1.589 1.338 0.980 0.845 1.072 1.430 1.602 1.412 1.061 0.847 0.995 1.344 1.597 1.485 1.145 0.865

2，程序

fileName = {'data0.txt','data1.txt','data2.txt'};
figure(1)
for i = 1:numel(fileName)
data = load(fileName{i});
subplot(3,1,i)
plot((1:1:numel(data))*1024/numel(data),data)
end

3，展示

 三，读取数据进行FFT运算后显示数据

1，数据

7.321 3.528 -3.377 -7.232 -4.135 2.522 7.197 4.921 -1.736 -6.953 -5.513 0.741 6.578 6.144 0.169 -6.210 -6.550 -1.116 5.633 6.949 1.933 -5.018 -7.263 -2.665 4.163 7.336 3.482 -3.439 -7.247 -4.182 2.537 7.197 4.921 -1.751 -6.999 -5.451 0.834 6.578 6.067 0.107 -6.194 -6.597 -0.977 5.587 6.996 1.779 -5.064 -7.170 -2.649 4.333 7.367 3.389 -3.485 -7.232 -4.197 2.584 7.244 4.813 -1.705 -6.984 -5.544 0.803 6.624 6.005 0.014 -6.148 -6.566 -0.962 5.649 6.887 1.732 -5.002 -7.216 -2.494 4.333 7.290 3.389 -3.532 -7.433 -4.120 2.738 7.182 4.782 -1.782 -7.092 -5.529 0.912 6.655 6.020 0.045 -6.241 -6.566 -0.915 5.664 6.841 1.686 -5.064 -7.108 -2.510 4.271 7.290 3.218 -3.578 -7.324 -4.073 2.677 7.228 4.797 -1.906 -6.999 -5.498 0.958 6.733 6.036 0.014 -6.334 -6.581 -0.853 5.711 6.826 1.670 -5.080 -7.061 -2.463 4.318 7.228 3.234 -3.516 -7.324 -3.965 2.723 7.166 4.720 -1.875 -7.046 -5.327 1.035 6.702 5.912 -0.141 -6.365 -6.365 -0.822 5.726 6.903 1.701 -5.095 -7.247 -2.541 4.395 7.321 3.265 -3.624 -7.293 -3.996 2.800 7.244 4.643 -1.983 -7.077 -5.436 1.051 6.640 5.866 -0.234 -6.318 -6.488 -0.791 5.788 6.826 1.562 -5.173 -7.154 -2.479 4.395 7.290 3.249 -3.717 -7.417 -3.950 2.816 7.182 4.705 -1.937 3.497 -3.501 -7.355 -4.120 2.584 7.120 4.797 -1.720 -6.953 -5.498 0.850 6.686 6.020 0.076 -6.163 -6.597 -0.977 5.726 6.949 1.763 -5.064 -7.232 -2.572 4.225 7.398 3.435 -3.485 -7.309 -4.197 2.599 7.151 5.076 -1.798 -6.999 -5.482 0.943 6.702 5.990 0.029 -6.132 -6.612 -0.915 5.711 6.887 1.701 -4.987 -7.139 -2.572 4.395 7.290 3.296 -3.593 -7.417 -4.058 2.723 7.213 4.859 -1.782 -7.077 -5.498 0.912 6.609 5.990 0.029 -6.287 -6.519 -0.838 5.711 6.872 1.670 -5.080 -7.092 -2.417 4.441 7.305 3.327 -3.609 -7.417 -3.980 2.769 7.213 4.828 -1.890 -7.077 -5.420 0.896 6.686 6.036 -0.079 -6.210 -6.550 -0.853 5.757 6.841 1.779 -5.049 -7.154 -2.417 4.379 7.228 3.280 -3.655 -7.293 -3.965 2.754 7.274 4.612 -1.968 -7.092 -5.436 1.020 6.764 5.959 -0.048 -6.241 -6.504 -0.776 5.695 6.934 1.608 -5.064 -7.077 -2.479 4.426 7.213 3.218 -3.702 -7.402 -4.058 2.738 7.290 4.627 -1.999 -6.984 -5.374 1.206 6.717 5.928 -0.203 -6.380 -6.427 -0.760 5.788 6.856 1.593 -5.173 -7.154 -2.448 4.503 7.290 3.203 -3.408 -7.402 -3.950 2.940 7.197 4.658 -2.014 -7.030 -5.358 1.159 6.624 5.912 -0.249 -6.334 -6.442 -0.606 5.773 6.872 1.484 -5.234 -7.201 -2.370 4.488 7.383 3.125 -3.562 -7.402 -3.872 2.924 7.259 4.674 -2.030 -7.030 -5.296 1.221 6.686 5.928 -0.249 -6.380 -6.349 -0.683 5.819 6.810 1.484 -5.219 -7.170 -2.216 4.627 7.259 3.156 -3.841 -7.324 -3.888 3.095 7.383 4.581 -2.045 -7.185 -5.234 1.190 6.686 5.897 -0.265 -6.365 -6.318 -0.652 5.897 6.717 1.546 -5.188 -7.108 -2.231 4.550 7.259 3.033 -3.888 -7.371 -3.826 3.079 7.259 4.519 -2.138 -7.201 -5.188 1.221 7.058 5.912 -0.358 -6.365 -6.365 -0.637 5.912 6.686 1.469 -5.281 -7.030 -2.308 4.596 7.290 2.986 -3.872 -7.324 -3.779 3.079 7.228 4.503 -2.247 -7.108 -5.188 1.376 6.779 5.881 -0.451 -6.427 -6.365 -0.621 5.990 6.810 1.330 -5.312 -7.201 -2.293 4.643 7.197 3.033 -3.841 -7.386 -3.655 3.002 7.290 4.395 -2.216 -7.077 -5.204 1.407 6.764 5.664 -0.482 -6.473 -6.256 -0.389 5.928 6.795 1.330 -5.374 -7.077 -2.200 4.751 7.244 2.971 -3.903 -7.371 -3.671 3.048 7.228 4.379 -2.231 -7.154 -5.142 1.392 6.872 5.664 -0.435 -6.504 -6.225 -0.420 6.020 6.624 1.283 -5.389 -7.077 -2.061 4.720 7.321 2.862 -3.996 -7.417 -3.748 3.187 7.259 4.488 -2.339 -7.108 -5.049 1.376 6.903 5.649 -0.482 -6.427 -6.287 -0.327 6.036 6.671 1.175 -5.420 -7.077 -2.014 4.705 7.367 2.847 -3.996 -7.340 -3.624 3.203 7.290 4.441 -2.417 -7.232 -5.033 1.438 6.903 5.757 -0.528 -6.535 -6.241 -0.342 5.943 6.748 1.283 -5.467 -7.061 -2.030 4.797 7.151 2.785 -4.011 -7.355 -3.609 3.311 7.244 4.410 -2.401 -7.201 -4.956 1.484 6.918 5.618 -0.606 -6.550 -6.272 -0.296 6.067 6.671 1.345 -5.513 -7.030 -2.061 4.751 7.259 2.785 -4.027 -7.293 -3.532 3.327 7.290 4.318 -2.448 -7.216 -5.002 1.577 6.996 5.587 -0.637 -6.581 -6.132 -0.280 6.175 6.655 1.128 -5.529 -7.061 -1.937 4.797 7.228 2.738 -4.166 -7.247 -3.516 3.327 7.228 4.194 -2.510 -7.123 -4.956 1.639 6.856 5.541 -0.667 -6.550 -6.241 -0.126 6.175 6.624 0.989 -5.591 -6.984 -1.968 4.952 7.166 2.831 -4.197 -7.324 -3.454 3.342 7.367 4.209 -2.417 -7.154 -4.971 1.686 6.918 5.463 -0.729 -6.659 -6.070 -0.141 6.082 6.593 0.974 -5.637 -6.906 -1.921 4.952 7.244 2.599 -4.275 -7.324 -3.532 3.420 7.274 4.178 -2.572 -7.247 -4.940 1.701 6.903 5.633 -0.760 -6.659 -6.132 -0.203 6.144 6.516 1.051 -5.683 -6.968 -1.782 4.906 7.228 2.553 -4.244 -7.386 -3.299 3.451 7.367 4.194 -2.696 -7.263 -4.832 1.686 6.934 5.572 -0.807 -6.659 -6.024 -0.095 6.113 6.547 0.989 -5.637 -6.875 -1.860 4.921 7.166 2.584 -4.321 -7.324 -3.392 3.528 7.244 4.132 -2.742 -7.293 -4.739 1.779 6.949 5.525 -0.931 -6.597 -6.055 0.029 6.175 6.609 0.958 -5.714 -6.922 -1.829 4.999 7.213 2.599 -4.244 -7.309 -3.284 3.559 7.259 4.132 -2.634 -7.247 -4.770 1.995 6.980 5.432 -0.962 -6.767 -6.086 0.076 6.206 6.593 0.881 -5.776 -6.922 -1.751 5.092 7.166 2.506 -4.306 -7.324 -3.315 3.590 7.274 4.070 -2.680 -7.293 -4.662 1.779 6.949 5.432 -0.977 -6.643 -5.947 0.014 6.222 6.500 0.726 -5.776 -6.860 -1.674 5.138 7.244 2.444 -4.368 -7.309 -3.299 3.683 7.383 3.977 -2.726 -7.247 -4.770 1.933 6.949 5.448 -1.039 -6.659 -5.993 0.122 6.268 6.438 0.819 -5.730 -6.860 -1.519 5.076 7.089 2.475 -4.507 -7.278 -3.253 3.652 7.383 3.931 -2.850 -7.263 -4.615 1.902 7.027 5.417 -1.085 -6.798 -6.009 0.184 6.191 6.423 0.757 -5.761 -6.860 -1.534 5.123 7.073 2.351 -4.476 -7.309 -3.083 3.698 7.336 3.853 -2.943 -7.263 -4.631 1.995 7.058 5.401 -1.116 -6.814 -5.962 0.230 6.299 6.531 0.788 -5.838 -6.767 -1.534 5.215 7.151 2.382 -4.445 -7.309 -3.144 3.760 7.352 3.884 -2.943 -7.263 -4.569 2.135 7.042 5.293 -1.147 -6.875 -5.869 0.199 6.377 6.469 0.617 -5.792 -6.860 -1.581 5.277 7.073 2.413 -4.584 -7.324 -3.098 3.745 7.367 3.807 -2.850 -7.263 -4.507 2.088 7.042 5.215 -1.256 -6.767 -5.900 0.339 6.361 6.377 0.602 -5.931 -6.767 -1.426 5.231 7.182 2.289 -4.631 -7.293 -3.129 3.838 7.321 3.946 -3.005 -7.185 -4.538 2.181 6.996 5.154 -1.240 -6.783 -5.869 0.385 6.438 6.315 0.494 -5.885 -6.829 -1.364 5.262 7.104 2.259 -4.693 -7.263 -3.052 3.838 7.460 3.760 -3.036 -7.386 -4.522 2.150 7.042 5.277 -1.287 -6.752 -5.838 0.323 6.423 6.253 0.525 -5.916 -6.705 -1.349 5.355 7.089 2.228 -4.615 -7.324 -2.866 3.992 7.352 3.729 -3.144 -7.309 -4.522 2.259 7.058 5.246 -1.411 -6.860 -5.838 0.385 6.454 6.377 0.478 -5.885 -6.752 -1.380 5.448 7.058 2.119 -4.445 -7.278 -2.850 3.961 7.259 3.745 -3.129 -7.386 -4.383 2.289 7.120 5.154 -1.442 -6.937 -5.714 0.432 6.408 6.346 0.416 -6.055 -6.736 -1.302 5.417 7.011 2.197 -4.677 -7.278 -2.928 3.961 7.259 3.621 -3.129 -7.247 -4.398 2.305 7.166 5.014 -1.519 -6.891

2，程序

%读取txt格式的波点数据到数组并绘图

%信号的参数
Fs = 1000;            % 采样频率              
T = 1/Fs;             % 采样周期（周期=1/频率） 
L = 1024;             % 信号长度，
t = (0:L-1)*T;        % 时间向量

wave_data1=importdata('D:\111\data1.txt');
subplot(2,1,1);

Y = fft(wave_data1);
P2 = Y/L;
f0 = Fs*(0:L-1)/L;

subplot(2,1,2);
plot(f0,P2) ;

3，展示（160Hz的正弦波）

参考链接：

(12条消息) 离线式数字信号处理（一）—— 使用Matlab读取TXT文件并做FFT分析_TerayTech的博客-CSDN博客_matlab中对txt文件两列数据进行fft