{"id":10201,"date":"2023-12-06T12:19:16","date_gmt":"2023-12-06T03:19:16","guid":{"rendered":"https:\/\/blogs.mathworks.com\/japan-community\/?p=10201"},"modified":"2023-12-12T03:37:24","modified_gmt":"2023-12-11T18:37:24","slug":"creating-natural-textures-with-power-law-noise-clouds-terrains-and-more-jp","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/japan-community\/2023\/12\/06\/creating-natural-textures-with-power-law-noise-clouds-terrains-and-more-jp\/","title":{"rendered":"\u30ce\u30a4\u30ba\u304b\u3089\u81ea\u7136\u306a\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u4f5c\u6210\u3059\u308b\uff1a\u96f2\u3001\u5730\u5f62\u3001\u6c34\u9762"},"content":{"rendered":"

\u203b\u3053\u306e\u6295\u7a3f\u306f 2023 \u5e74 11 \u6708 29 \u65e5\u306b The MATLAB Blog \u3078 \u6295\u7a3f<\/a>\u3055\u308c\u305f\u3082\u306e\u306e\u6284\u8a33\u3067\u3059\u3002<\/p>\n

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\u672c\u65e5\u306e\u30b2\u30b9\u30c8\u30e9\u30a4\u30bf\u30fc\u306f\u3001MATLAB Central \u30b3\u30df\u30e5\u30cb\u30c6\u30a3\u304b\u3089\u304a\u306a\u3058\u307f\u306eAdam Danz<\/a>\u3067\u3059\u3002Adam \u306f MATLAB \u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u30c1\u30fc\u30e0\u306e\u958b\u767a\u8005\u3067\u3042\u308a\u3001Graphics and App Building <\/a>\u30d6\u30ed\u30b0\u306e\u30db\u30b9\u30c8\u3067\u3059\u3002\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u69cb\u9020\u5316\u30ce\u30a4\u30ba\u306e\u4f5c\u6210\u3068 MATLAB `\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u3078\u306e\u9069\u7528\u306b\u3064\u3044\u3066\u89e3\u8aac\u3057\u307e\u3059\u3002<\/div>\n
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\u30ce\u30a4\u30ba\u306f\u81ea\u7136\u754c\u306b\u5e83\u304f\u5b58\u5728\u3066\u3044\u307e\u3059\u3002MATLAB \u306b\u306f\u30c7\u30fc\u30bf\u3084\u753b\u50cf\u304b\u3089\u30ce\u30a4\u30ba\u3092\u9664\u53bb\u3059\u308b\u305f\u3081\u306e\u6a5f\u80fd\u304c\u305f\u304f\u3055\u3093\u3042\u308a\u307e\u3059\u304c\u3001\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u81ea\u7136\u306b\u898b\u3048\u308b\u96f2\u3001\u5730\u5f62\u3001\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u751f\u6210\u3059\u308b\u305f\u3081\u306e\u30ce\u30a4\u30ba\u751f\u6210\u65b9\u6cd5\u3092\u30ec\u30d3\u30e5\u30fc\u3057\u307e\u3059\u3002 Flipbook Mini Hack contest<\/a> \u306e\u53c2\u52a0\u8005\u3082\u4f7f\u7528\u3055\u308c\u3066\u3044\u308b\u30c6\u30af\u30cb\u30c3\u30af\u3067\u3059\u3002\u4ee5\u4e0b\u306b\u4f8b\u3092\u3044\u304f\u3064\u304b\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n

\"CombinedAnimation.gif\"<\/div>\n
\u5de6\u304b\u3089\u3001<\/span>Rolling fog<\/span><\/a>\u3001Blowin’in the wind<\/span><\/a>\u3001Morning ascent<\/span><\/a>\u3001landScape<\/span><\/a>.<\/span><\/div>\n
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\u3053\u306e\u7a2e\u306e\u69cb\u9020\u5316\u30ce\u30a4\u30ba\u306b\u306f\u30011\/f\u30ce\u30a4\u30ba\u3001\u30b3\u30d2\u30fc\u30ec\u30f3\u30c8\u30ce\u30a4\u30ba\u3001\u30d5\u30e9\u30af\u30bf\u30eb\u30ce\u30a4\u30ba\u3001\u30ab\u30e9\u30fc\u30c9\u30ce\u30a4\u30ba\u3001\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\u3001fBm\u3001\u30d6\u30e9\u30a6\u30cb\u30a2\u30f3\u30ce\u30a4\u30ba\u306a\u3069\u3001\u3044\u304f\u3064\u304b\u306e\u5206\u985e\u304c\u3042\u308a\u3001\u305d\u308c\u305e\u308c\u306b\u72ec\u81ea\u306e\u5b9a\u7fa9\u304c\u3042\u308a\u307e\u3059\u3002\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001\u4fe1\u53f7\u306e\u5f37\u5ea6\u3068\u7a7a\u9593\u7684\u307e\u305f\u306f\u6642\u9593\u7684\u5468\u6ce2\u6570\u3068\u306e\u9593\u306e\u6570\u5b66\u7684\u95a2\u4fc2\u3092\u8aac\u660e\u3059\u308b\u7528\u8a9e\u3067\u3042\u308b\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u3068\u547c\u3076\u3053\u3068\u306b\u3057\u307e\u3059\u3002\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306f\u3001\u4e18\u3084\u8c37\u306a\u3069\u306e\u30de\u30af\u30ed\u306a\u5909\u52d5\u3084\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u52a0\u3048\u308b\u30de\u30a4\u30af\u30ed\u306a\u5909\u52d5\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u3053\u306e\u30bf\u30a4\u30d7\u306e\u30ce\u30a4\u30ba\u306f\u3001\u5730\u9707\u304b\u3089\u91d1\u878d\u5e02\u5834\u306b\u81f3\u308b\u307e\u3067\u306e\u81ea\u7136\u73fe\u8c61\u306b\u3057\u3070\u3057\u3070\u898b\u3089\u308c\u3001MATLAB \u3067\u7c21\u5358\u306b\u751f\u6210\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/div>\n

MATLAB \u3067 2D \u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u3092\u751f\u6210\u3059\u308b\u305f\u3081\u306e 5 \u3064\u306e\u30b9\u30c6\u30c3\u30d7<\/h2>\n
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\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306e\u4f5c\u6210\u306f\u7c21\u5358\u3067\u3001MATLAB \u3060\u3068 3 \u3064\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3068\u6570\u884c\u306e\u30b3\u30fc\u30c9\u3067\u3059\u3002\u4e0b\u306e\u753b\u50cf\u306e 5 \u3064\u306e\u30b9\u30c6\u30c3\u30d7\u3067\u8aac\u660e\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n

\"\"<\/div>\n
\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u3092\u4f5c\u6210\u3059\u308b 5 \u30b9\u30c6\u30c3\u30d7<\/span><\/div>\n
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1.\u30e9\u30f3\u30c0\u30e0\u30ce\u30a4\u30ba\uff1a<\/strong>\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306e\u884c\u5217\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306e\u5b9a\u7fa9\u306e\u4e2d\u306b\u306f\u3001randn() <\/span>\u3092\u4f7f\u7528\u3057\u3066\u751f\u6210\u3055\u308c\u308b\u30ac\u30a6\u30b9\u767d\u8272\u30ce\u30a4\u30ba\u304b\u3089\u59cb\u3081\u308b\u5fc5\u8981\u304c\u3042\u308b\u3082\u306e\u3082\u3042\u308a\u307e\u3059\u304c\u3001rand() <\/span>\u3092\u4f7f\u7528\u3057\u3066\u751f\u6210\u3055\u308c\u308b\u4e00\u69d8\u5206\u5e03\u306e\u30e9\u30f3\u30c0\u30e0\u6570\u5024\u3067\u3082\u5341\u5206\u306a\u7d50\u679c\u304c\u5f97\u3089\u308c\u307e\u3059\u3002\u6700\u521d\u306e 2 \u3064\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u306f\u884c\u5217\u306e\u30b5\u30a4\u30ba\u3068\u30e9\u30f3\u30c0\u30e0\u6570\u5024\u751f\u6210\u5668\u306e\u30b7\u30fc\u30c9\uff08\u304a\u3088\u3073\u751f\u6210\u5668\u306e\u30bf\u30a4\u30d7\uff09\u3067\u3059\u3002\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306f\u521d\u671f\u5024\u306b\u5927\u304d\u304f\u5f71\u97ff\u3055\u308c\u308b\u305f\u3081\u3001\u5404\u30b7\u30fc\u30c9\u3068\u884c\u5217\u306e\u30b5\u30a4\u30ba\u306f\u7570\u306a\u308b\u7d50\u679c\u3092\u751f\u6210\u3057\u307e\u3059\u3002\u30b5\u30a4\u30ba k<\/span> \u306f\u5076\u6570\u3067\u3042\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n<\/div>\n

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rng(0,‘twister’<\/span>) % Parameter 1. random number generator seed<\/span><\/div>\n<\/div>\n
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k = 100; % Parameter 2. size of the square matrix, must be an even scalar<\/span><\/div>\n<\/div>\n
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m = randn(k); % k-by-k matrix<\/span><\/div>\n<\/div>\n<\/div>\n
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2. \u30d5\u30fc\u30ea\u30a8\u5909\u63db<\/strong>\uff1a\uff12\u6b21\u5143\u9ad8\u901f\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u95a2\u6570 fft2() <\/span>\u3092\u4f7f\u7528\u3057\u3066\u3001\uff12\u6b21\u5143\u914d\u5217\u3092\u7a7a\u9593\u9818\u57df\u304b\u3089\u5468\u6ce2\u6570\u9818\u57df\u306b\u5909\u63db\u3057\u307e\u3059\u3002\u3053\u308c\u306b\u3088\u308a\u3001\u4f4e\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u304c\u884c\u5217\u306e\u7aef\u306b\u3001\u9ad8\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u304c\u884c\u5217\u306e\u4e2d\u592e\u306b\u914d\u7f6e\u3055\u308c\u305f\u30d4\u30e9\u30df\u30c3\u30c9\u72b6\u306e\u5468\u6ce2\u6570\u4fc2\u6570\u306e\u884c\u5217\u304c\u8fd4\u3055\u308c\u307e\u3059\u3002\u30b9\u30c6\u30c3\u30d7 4 \u3067\u306f\u3001\u3053\u306e\u914d\u7f6e\u3092\u53cd\u8ee2\u3055\u305b\u3001\u4f4e\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u304c\u4e2d\u592e\u306b\u3001\u9ad8\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u304c\u884c\u5217\u306e\u7aef\u306b\u914d\u7f6e\u3055\u308c\u308b\u3088\u3046\u306b\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u914d\u7f6e\u3092\u53cd\u8ee2\u3055\u305b\u308b\u306b\u306f fftshift() <\/span>\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n

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mf = fftshift(fft2(m));<\/div>\n<\/div>\n<\/div>\n
\uff12\u6b21\u5143\u306e\u5468\u6ce2\u6570\u4fc2\u6570\u3092\u3069\u3046\u89e3\u91c8\u3059\u308b\u306e\u3067\u3057\u3087\u3046\u304b\uff1f<\/em>\u3053\u306e\u6bb5\u843d\u306f\u8208\u5473\u3092\u3082\u3063\u3066\u304f\u308c\u305f\u8aad\u8005\u3068\u3001\u7c21\u6f54\u306b\u8aac\u660e\u3059\u308b\u79c1\u306e\u500b\u4eba\u7684\u306a\u6311\u6226\u306e\u305f\u3081\u306e\u3082\u306e\u3067\u3059\u3002\uff12\u6b21\u5143\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u306f\u3001\u753b\u50cf\u3092\u69d8\u3005\u306a\u5468\u6ce2\u6570\u3068\u5411\u304d\u3092\u6301\u3064\u5e73\u9762\u7684\u306a\u6b63\u5f26\u6ce2\u306b\u5206\u89e3\u3057\u307e\u3059\u3002\u5468\u6ce2\u6570\u4fc2\u6570\u306f\u8907\u7d20\u6570\u3067\u3042\u308a\u3001\u5e73\u9762\u6ce2\u3092\u7d44\u307f\u5408\u308f\u305b\u305f\u308a\u91cd\u306d\u5408\u308f\u305b\u305f\u308a\u3057\u3066\u753b\u50cf\u3092\u518d\u73fe\u3059\u308b\u305f\u3081\u306e\u4e00\u9023\u306e\u6307\u793a\u3092\u63d0\u4f9b\u3057\u307e\u3059\u3002mf(u,v) <\/span>\u306e\u5024\u3092\u8003\u3048\u3066\u307f\u307e\u3057\u3087\u3046\u3002mf(u,v) <\/span>\u306e\u5b9f\u90e8\u3068\u865a\u90e8\u306f\u3001\u884c u \u3068\u5217 v \u306b\u5272\u308a\u5f53\u3066\u3089\u308c\u305f\u5468\u6ce2\u6570\u306b\u3088\u3063\u3066\u5b9a\u7fa9\u3055\u308c\u308b\uff12\u6b21\u5143\u6b63\u5f26\u6ce2\u5e73\u9762\u306e\u632f\u5e45\u3068\u4f4d\u76f8\u306b\u5bfe\u5fdc\u3057\u307e\u3059\u3002MATLAB \u306e\u753b\u50cf\u95a2\u9023\u306e\u95a2\u6570\u306f\u8907\u7d20\u6570\u5024\u3092\u30b5\u30dd\u30fc\u30c8\u3057\u3066\u3044\u306a\u3044\u305f\u3081\u3001\u5468\u6ce2\u6570\u4fc2\u6570\u306e\u5927\u304d\u3055\u304c\u4e0a\u8a18\u306e\u6982\u8981\u56f3\u306e 2 \u3064\u76ee\u3068 4 \u3064\u76ee\u3067\u8868\u793a\u3055\u308c\u3066\u3044\u307e\u3059\u3002\u8907\u7d20\u6570\u306e\u5927\u304d\u3055\u306f abs() <\/span>\u3092\u4f7f\u7528\u3057\u3066\u8a08\u7b97\u3055\u308c\u307e\u3059\u3002<\/div>\n
<\/div>\n
\n

3.\u00a0\u30d5\u30a3\u30eb\u30bf\u30fc\u306e\u4f5c\u6210<\/strong>\uff1a\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306e\u91cd\u8981\u306a\u7279\u5fb4\u306f\u3001\u4f4e\u5468\u6ce2\u6570\u306e\u652f\u914d\u6027\u3068\u3001\u5909\u52d5\u306b\u5bc4\u4e0e\u3059\u308b\u9ad8\u5468\u6ce2\u6570\u3002\u3053\u308c\u306b\u3088\u308a\u3001\uff12\u6b21\u5143\u306e\u4e18\u3084\u96f2\u306e\u3088\u3046\u306a\u30de\u30af\u30ed\u306a\u30d1\u30bf\u30fc\u30f3\u3092\u753b\u50cf\u306b\u4f5c\u308a\u51fa\u3057\u3064\u3064\u3001\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u52a0\u3048\u308b\u30de\u30a4\u30af\u30ed\u306a\u5909\u52d5\u3092\u53ef\u80fd\u306b\u3057\u307e\u3059\u3002\u5468\u6ce2\u6570\u306e\u89b3\u70b9\u304b\u3089\u306f\u3001\u7d30\u304b\u3044\u30c7\u30a3\u30c6\u30fc\u30eb\u3092\u6301\u3064\u753b\u50cf\u306e\u90e8\u5206\u306f\u9ad8\u3044\u7a7a\u9593\u5468\u6ce2\u6570\u3092\u6301\u3061\u3001\u3088\u308a\u6ed1\u3089\u304b\u306a\u90e8\u5206\u306f\u4f4e\u3044\u7a7a\u9593\u5468\u6ce2\u6570\u3092\u6301\u3061\u307e\u3059\u3002\u30d5\u30a3\u30eb\u30bf\u30fc\u306e\u76ee\u7684\u306f\u3001\u753b\u50cf\u306e\u4f4e\u3044\u7a7a\u9593\u5468\u6ce2\u6570\u3092\u5f37\u8abf\u3057\u3066\u30de\u30af\u30ed\u306a\u30d1\u30bf\u30fc\u30f3\u3092\u4f5c\u308a\u51fa\u3059\u3053\u3068\u3067\u3059\u3002\u30b9\u30c6\u30c3\u30d7 2 \u3067\u30b7\u30d5\u30c8\u3055\u308c\u305f\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u884c\u5217 mf<\/span> \u306f\u3001\u4f4e\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u304c\u4e2d\u5fc3\u306b\u914d\u7f6e\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u3092\u601d\u3044\u51fa\u3057\u3066\u304f\u3060\u3055\u3044\u3002\u3057\u305f\u304c\u3063\u3066\u3001\uff12\u6b21\u5143\u30d5\u30a3\u30eb\u30bf\u30fc\u306f\u5468\u6ce2\u6570\u306b\u5bfe\u3057\u3066\u9006\u306e\u95a2\u4fc2\uff08$ 1\/f$ \u3053\u3053\u3067\u3001\uff12\u6b21\u5143\u4fe1\u53f7\u306e\u5834\u5408\u306f $f = \\sqrt{f_u^2 + f_v^2}$\uff09\u3092\u6301\u3064\u3079\u304d\u3067\u3042\u308a\u3001\u4e2d\u5fc3\u306e\u4f4e\u5468\u6ce2\u6570\u306b\u306f\u3088\u308a\u5927\u304d\u306a\u91cd\u307f\u3092\u7f6e\u304d\u3001\u5468\u56f2\u306e\u9ad8\u5468\u6ce2\u6570\u306b\u306f\u3088\u308a\u5c11\u306a\u3044\u91cd\u307f\u3092\u7f6e\u304f\u3088\u3046\u306b\u3057\u307e\u3059\u3002\u4f4e\u5468\u6ce2\u6570\u3092\u3069\u306e\u7a0b\u5ea6\u91cd\u8996\u3059\u308b\u304b\u306f\u7b2c 3 \u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3001$1\/f^\u03b1$ \u306e\u6307\u6570\u306b\u3088\u3063\u3066\u5236\u5fa1\u3055\u308c\u3001\u901a\u5e38\u306f 0<\u03b1<=3<\/span> \u306e\u7bc4\u56f2\u5185\u306b\u7d0d\u3081\u307e\u3059\u3002\u03b1<\/span> \u306e\u5024\u304c\u5927\u304d\u3044\u307b\u3069\u3001\u4f4e\u5468\u6ce2\u6570\u304b\u3089\u306e\u5f71\u97ff\u304c\u5927\u304d\u304f\u306a\u308a\u3001\u4ee5\u4e0b\u306e\u753b\u50cf\u306b\u793a\u3055\u308c\u308b\u3088\u3046\u306b\u3001\u8a73\u7d30\u306a\u30c6\u30af\u30b9\u30c1\u30e3\u304c\u5c11\u306a\u3044\u7d50\u679c\u3068\u306a\u308a\u307e\u3059\u3002\u03b1<\/span>\u306e\u5024\u306f\u3001\u767d\u8272\u30ce\u30a4\u30ba\uff08\u03b1<\/span>=0\uff09\u3001\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\uff08\u03b1<\/span>=1\uff09\u3001\u30d6\u30e9\u30a6\u30cb\u30a2\u30f3\u30ce\u30a4\u30ba\uff08\u03b1<\/span>=2\uff09\u306a\u3069\u3001\u30ce\u30a4\u30ba\u306e\u3044\u304f\u3064\u304b\u306e\u5206\u985e\u3092\u5b9a\u7fa9\u3059\u308b\u305f\u3081\u306b\u4f7f\u7528\u3055\u308c\u307e\u3059\u3002<\/p>\n<\/div>\n

\"\"<\/div>\n
\u4fc2\u6570\u306e\u5f71\u97ff\u3092\u78ba\u8a8d\uff1a\u5927\u304d\u3044\u307b\u3069\u4f4e\u5468\u6ce2\u6570\u304b\u3089\u306e\u5f71\u97ff\u304c\u5927\u304d\u304f\u306a\u308a\u307e\u3059<\/span><\/div>\n
\u3053\u308c\u307e\u3067\u898b\u305f\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306e\u5b9f\u88c5\u306f\u3001\u305d\u308c\u305e\u308c\u30d5\u30a3\u30eb\u30bf\u30fc\u306e\u4f5c\u6210\u65b9\u6cd5\u304c\u7570\u306a\u308a\u307e\u3059\u304c\u3001\u91cd\u307f\u306e\u5206\u5e03\u30d1\u30bf\u30fc\u30f3\u306f\u540c\u3058\u3067\u3059\u3002\u3053\u306e\u30d5\u30a3\u30eb\u30bf\u30fc\u306f\u30b9\u30c6\u30c3\u30d7 5 \u3067\u5b9f\u6570\u5024\u3092\u8fd4\u3057\u975e\u5e38\u306b\u5805\u7262\u3067\u3059\u304c\u3001k<\/span> \u304c\u5076\u6570\u3067\u3042\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/div>\n
\n
\n
a = 2; % Parameter 3. 1\/f\u1d45 exponent<\/span><\/div>\n<\/div>\n
\n
d = ((1:k)-(k\/2)-1).^2;<\/div>\n<\/div>\n
\n
dd = sqrt(d(:) + d(:)’);<\/div>\n<\/div>\n
\n
filt = dd .^ -a; % frequency filter<\/span><\/div>\n<\/div>\n
\n
filt(isinf(filt))=1; % replace +\/-inf at DC or zero-frequency component<\/span><\/div>\n<\/div>\n<\/div>\n
\n

 <\/p>\n

4. \u30d5\u30a3\u30eb\u30bf\u30fc\u3055\u308c\u305f\u5468\u6ce2\u6570\uff1a<\/strong>\u30b7\u30d5\u30c8\u3055\u308c\u305f\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u884c\u5217\u306b\u30d5\u30a3\u30eb\u30bf\u30fc\u3092\u639b\u3051\u307e\u3059\u3002\u901a\u5e38\u3001\u5ea7\u6a19 (u,v)<\/span> \u306e\u5024\u304c\u753b\u50cf\u306e(u,v)<\/span> \u306e\u30d4\u30af\u30bb\u30eb\u306e\u5f37\u5ea6\u3092\u6c7a\u5b9a\u3059\u308b\u3068\u8003\u3048\u304c\u3061\u306a\u306e\u3067\u30015 \u30b9\u30c6\u30c3\u30d7\u306e\u307e\u3068\u3081\u306e\uff14\u3064\u76ee\u306e\u753b\u50cf\u3092\u898b\u305f\u3060\u3051\u3067\u306f\u3001\u3053\u306e\u884c\u5217\u304c\u6700\u7d42\u7684\u306a\u753b\u50cf\u306b\u3069\u306e\u3088\u3046\u306b\u5bc4\u4e0e\u3059\u308b\u304b\u3092\u60f3\u50cf\u3059\u308b\u306e\u306f\u96e3\u3057\u3044\u3068\u601d\u3044\u307e\u3059\u3002\u3053\u306e\u753b\u50cf\u3067\u306f\u3001\u884c\u5217\u306e\u4e2d\u592e\u307b\u3069\u9ad8\u3044\u5024\u306e\u4fc2\u6570\u3092\u6301\u3064\u306e\u3067\u3001\u3053\u308c\u306f\u4f4e\u3044\u7a7a\u9593\u5468\u6ce2\u6570\u304c\u6700\u7d42\u7d50\u679c\u306b\u3088\u308a\u5927\u304d\u306a\u5f71\u97ff\u3092\u4e0e\u3048\u308b\u3053\u3068\u60f3\u50cf\u3067\u304d\u307e\u3059\u3002<\/p>\n<\/div>\n

\n
\n
ff = mf .* filt;<\/div>\n<\/div>\n<\/div>\n
\n

 <\/p>\n

5. \u9006\u30d5\u30fc\u30ea\u30a8\u5909\u63db\uff1a<\/strong>\u30e9\u30f3\u30c0\u30e0\u306a\u5024\u306e\u884c\u5217\u304b\u3089\u59cb\u3081\u3066\u3001\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u306f\u30e9\u30f3\u30c0\u30e0\u884c\u5217\u3092\u5468\u6ce2\u6570\u9818\u57df\u3067\u518d\u69cb\u7bc9\u3057\u3001\u30d5\u30a3\u30eb\u30bf\u30fc\u3067\u4f4e\u5468\u6ce2\u6570\u3092\u5f37\u8abf\u3057\u307e\u3057\u305f\u3002\u6700\u5f8c\u306e\u30b9\u30c6\u30c3\u30d7\u306f\u3001\u30d5\u30a3\u30eb\u30bf\u30fc\u3055\u308c\u305f\u5468\u6ce2\u6570\u3092\u7a7a\u9593\u9818\u57df\u306b\u623b\u3059\u3053\u3068\u3067\u3059\u3002ifftshift() <\/span>\u3092\u4f7f\u7528\u3057\u3066\u5468\u6ce2\u6570\u3092\u5143\u306e\u30d4\u30e9\u30df\u30c3\u30c9\u72b6\u306e\u914d\u7f6e\u306b\u623b\u3057\u3001\u4f4e\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u3092\u7aef\u306b\u3001\u9ad8\u5468\u6ce2\u6570\u306e\u4fc2\u6570\u3092\u4e2d\u592e\u306b\u914d\u7f6e\u3057\u307e\u3059\u3002\u305d\u306e\u5f8c\u3001\uff12\u6b21\u5143\u9006\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u3092ifft2() <\/span>\u3092\u4f7f\u7528\u3057\u3066\u9069\u7528\u3057\u307e\u3059\u3002<\/p>\n<\/div>\n

\n
\n
b = ifft2(ifftshift(ff));<\/div>\n<\/div>\n<\/div>\n
\u7d50\u679c\u3068\u3057\u3066\u5f97\u3089\u308c\u305f b <\/span>\u306f\u3001\u5143\u306e\u753b\u50cf\u3068\u540c\u3058\u30b5\u30a4\u30ba\u306e\u69cb\u9020\u5316\u30ce\u30a4\u30ba\u3092\u5f62\u6210\u3059\u308b\u5b9f\u6570\u884c\u5217\u3067\u3059\u30025 \u30b9\u30c6\u30c3\u30d7\u306e 5 \u3064\u76ee\u306e\u753b\u50cf\u306b\u793a\u3055\u308c\u3066\u3044\u308b\u7d50\u679c\u3092imagesc(b) <\/span>\u3092\u4f7f\u7528\u3057\u3066\u8868\u793a\u3057\u3001\u30ab\u30e9\u30fc\u30d0\u30fc\u3092\u9069\u7528\u3057\u3066\u753b\u50cf\u306e\u5f37\u5ea6\u5024\u3092\u78ba\u8a8d\u3057\u307e\u3059\u3002<\/div>\n
\u30ce\u30a4\u30ba\u5024\u3092[-1,1]\u306e\u7bc4\u56f2\u306b\u30b9\u30b1\u30fc\u30eb\u3059\u308b\u3053\u3068\u306f\u4e00\u822c\u7684\u3067\u3042\u308a\u3001\u8ffd\u52a0\u306e\u30b9\u30b1\u30fc\u30ea\u30f3\u30b0\u3092\u9069\u7528\u3059\u308b\u306e\u304c\u5bb9\u6613\u306b\u306a\u308a\u307e\u3059\u3002\u7d50\u679c\u3092\u30b9\u30b1\u30fc\u30eb\u3059\u308b\u306b\u306f rescale() <\/span>\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/div>\n
\n
\n
bScaled = rescale(b,-1,1);<\/div>\n<\/div>\n<\/div>\n
\u30d5\u30fc\u30ea\u30a8\u5909\u63db\u3055\u308c\u305f\u753b\u50cf\u306b\u30d5\u30a3\u30eb\u30bf\u30fc\u3092\u9069\u7528\u3057\u3001\u305d\u306e\u30d7\u30ed\u30bb\u30b9\u3092\u753b\u50cf\u306b\u9006\u623b\u3057\u3059\u308b\u3068\u3044\u3046\u3053\u306e\u30d1\u30bf\u30fc\u30f3\u306f\u753b\u50cf\u51e6\u7406\u3067\u4e00\u822c\u7684\u3067\u3042\u308a\u3001\u753b\u50cf\u30d5\u30a3\u30eb\u30bf\u30fc\u306b\u3064\u3044\u3066\u5b66\u3076\u826f\u3044\u8ab2\u984c\u3068\u306a\u308a\u307e\u3059\u3002<\/div>\n

\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u884c\u5217\u306e\u53ef\u8996\u5316<\/h2>\n
\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u5024\u306e\u914d\u5217\u306f\u3001\u30ab\u30e9\u30fc\u30c7\u30fc\u30bf\u3084\u30a2\u30eb\u30d5\u30a1\u5024\uff08\u900f\u660e\u5ea6\uff09\u307e\u305f\u306f\uff13\u6b21\u5143\u5e73\u9762\u306e\u9ad8\u3055\u306b\u3082\u9069\u7528\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u56f3\u306f\u3001\u540c\u3058\u30ce\u30a4\u30ba\u884c\u5217\u3092 4 \u3064\u306e\u7570\u306a\u308b\u65b9\u6cd5\u3067\u53ef\u8996\u5316\u3057\u305f\u3082\u306e\u3067\u3059\u3002<\/div>\n
\"\"<\/div>\n
\u540c\u3058\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u884c\u5217\u306e\u7570\u306a\u308b\u53ef\u8996\u5316<\/i><\/div>\n
\u3053\u308c\u3089\u306f\u4e0a\u8a18\u3067\u7d39\u4ecb\u3057\u305f 5 \u30b9\u30c6\u30c3\u30d7\u306b\u5f93\u3063\u3066\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u884c\u5217\uff08bScaled<\/span>\uff09\u3092\u4f5c\u6210\u3057\u307e\u3059\u304c\u3001\u30b5\u30a4\u30ba\u30d1\u30e9\u30e1\u30fc\u30bf\u3092 k=500\u00a0<\/span>\u306b\u7f6e\u304d\u63db\u3048\u3066\u304f\u3060\u3055\u3044\u3002\u305d\u306e\u5f8c\u3001\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u3092\u7d9a\u3051\u307e\u3059\u3002\uff12\u3064\u76ee\u3001\uff13\u3064\u76ee\u306f\u3053\u306e\u8a18\u4e8b\u306b\u6dfb\u4ed8\u3055\u308c\u3066\u3044\u308b\u30ab\u30b9\u30bf\u30e0\u30ab\u30e9\u30fc\u30de\u30c3\u30d7 terrainmap<\/span> \u3092\u4f7f\u7528\u3057\u3066\u3044\u307e\u3059\uff08download<\/a>\uff09\u3002Mapping Toolbox\u306b\u306f\u3001\u6539\u826f\u3055\u308c\u305f\u5730\u5f62\u30ab\u30e9\u30fc\u30de\u30c3\u30d7\u3001demcmap <\/span>\u304c\u3042\u308b\u306e\u3067\u4f7f\u3048\u308b\u304b\u3082\u3057\u308c\u307e\u305b\u3093\u3002<\/div>\n
\n
\n
% Panel 1<\/span><\/div>\n<\/div>\n
\n
figure()<\/div>\n<\/div>\n
\n
imagesc(bScaled)<\/div>\n<\/div>\n
\n
set(gca,‘YDir’<\/span>,‘normal’<\/span>)<\/div>\n<\/div>\n
\n
colormap(gca,sky(256))<\/div>\n<\/div>\n
\n
colorbar<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Panel 2<\/span><\/div>\n<\/div>\n
\n
figure()<\/div>\n<\/div>\n
\n
imagesc(bScaled)<\/div>\n<\/div>\n
\n
set(gca,‘YDir’<\/span>,‘normal’<\/span>)<\/div>\n<\/div>\n
\n
colormap(gca,terrainmap()) % custom colormap<\/span><\/div>\n<\/div>\n
\n
colorbar<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Panel 3<\/span><\/div>\n<\/div>\n
\n
figure()<\/div>\n<\/div>\n
\n
x = linspace(-4, 4, width(bScaled));<\/div>\n<\/div>\n
\n
y = linspace(-4, 4, height(bScaled));<\/div>\n<\/div>\n
\n
surf(x,y,bScaled,EdgeColor=‘none’<\/span>)<\/div>\n<\/div>\n
\n
colormap(gca,terrainmap()) % custom colormap<\/span><\/div>\n<\/div>\n
\n
axis equal<\/span><\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Panel 4<\/span><\/div>\n<\/div>\n
\n
figure()<\/div>\n<\/div>\n
\n
s = surf(zeros(k,k),FaceColor=[.28 .24 .54],EdgeColor=‘none’<\/span>,…<\/span><\/div>\n<\/div>\n
\n
\u00a0\u00a0\u00a0\u00a0AlphaData=bScaled,FaceAlpha=‘flat’<\/span>);<\/div>\n<\/div>\n
\n
view(2)<\/div>\n<\/div>\n<\/div>\n

<\/h3>\n

\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u5f37\u8abf\u3059\u308b\u305f\u3081\u306e\u5149\u306e\u4f7f\u7528<\/h3>\n
\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306b\u3088\u3063\u3066\u63d0\u4f9b\u3055\u308c\u308b\u30c6\u30af\u30b9\u30c1\u30e3\u306f\u3001\u30b0\u30e9\u30d5\u30a3\u30c3\u30af\u30b9\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306e\u8272\u306e\u5909\u5316\u304c\u5341\u5206\u3067\u306a\u3044\u3068\u898b\u904e\u3054\u3055\u308c\u3066\u3057\u307e\u3044\u307e\u3059\u3002MATLAB \u3067\u306e\u7167\u660e\u306e\u4f7f\u7528\u306f\u3001\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306b\u8a73\u7d30\u306a\u9670\u5f71\u3092\u52a0\u3048\u308b\u3053\u3068\u3067\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u5f37\u8abf\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u753b\u50cf\u306f\u3001\u4e0a\u306e\u66f2\u9762\u30d7\u30ed\u30c3\u30c8\u3068\u540c\u3058\u5c71\u3092\u793a\u3057\u3066\u3044\u307e\u3059\u3002\u6c34\u4f4d\u306f\u3001\u5225\u306e\u30ce\u30a4\u30ba\u884c\u5217\u306b\u3088\u3063\u3066\u5b9a\u7fa9\u3055\u308c\u305f\u8272\u306e\u5e73\u9762\u3068\u3057\u3066\u8ffd\u52a0\u3057\u307e\u3057\u305f\u3002\u5149\u306e\u4f4d\u7f6e\u306f\u3001cameratoolbar<\/a> \u30c4\u30fc\u30eb\u3092\u4f7f\u7528\u3057\u3066\u624b\u52d5\u3067\u9078\u629e\u3057\u3001\u518d\u73fe\u6027\u306e\u305f\u3081\u306b\u4ee5\u4e0b\u306e\u30b3\u30fc\u30c9\u306b\u5024\u3060\u3051\u53d6\u308a\u51fa\u3057\u3066\u3044\u307e\u3059\u3002\u30ab\u30e1\u30e9\u306e\u30d7\u30ed\u30d1\u30c6\u30a3\u306f\u3001\u5c71\u306b\u30ba\u30fc\u30e0\u30a4\u30f3\u3059\u308b\u3088\u3046\u306b\u8a2d\u5b9a\u3057\u3066\u3044\u307e\u3059\u3002<\/div>\n
\"\"<\/div>\n
\u30e9\u30a4\u30c6\u30a3\u30f3\u30b0\u3067\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u5f37\u8abf<\/span><\/div>\n
\n
rng(0,‘twister’<\/span>)<\/div>\n
k = 500;<\/div>\n
mountainHeights = makenoise(k, 2); % mountain noise<\/span><\/div>\n
<\/div>\n
figure()<\/div>\n
x = linspace(-4, 4, k);<\/div>\n
y = linspace(-4, 4, k);<\/div>\n
mountainHeights = mountainHeights + 0.3; % raise the mountain<\/span><\/div>\n
surf(x,y,mountainHeights,EdgeColor=‘none’<\/span>)<\/div>\n
colormap(flipud(copper))<\/div>\n
<\/div>\n
hold on<\/span><\/div>\n
seaShading = makenoise(k, 1.5); % water color noise<\/span><\/div>\n
nColors = 500; % number of colors to use for the water<\/span><\/div>\n
seaColors = parula(nColors*3\/2);<\/div>\n
seaColors(nColors+1:end,:) = []; % Capture the blue-green end of parula<\/span><\/div>\n
% convert seaShading (-1:1) to colormap indices (1:500)<\/span><\/div>\n
seaShadingIdx = round((seaShading+1)*(nColors\/2-.5)+1);<\/div>\n
% Create mxnx3 matrix of CData<\/span><\/div>\n
cdata = reshape(seaColors(seaShadingIdx,:),nColors,nColors,3);<\/div>\n
S=surf(x*3, y*3, 0*seaShading,CData=cdata,EdgeColor=‘none’<\/span>);<\/div>\n
<\/div>\n
axis equal off<\/span><\/div>\n
<\/div>\n
clim([-0.5, 1.5])<\/div>\n
light(Position = [-.8 .1 .75]) % add lighting<\/span><\/div>\n
material dull<\/span><\/div>\n
camva(10) % camera viewing angle<\/span><\/div>\n
campos([-14 7 4]) % camera position<\/span><\/div>\n
camtarget([.4 .8 .4]) % camera target<\/span><\/div>\n
<\/div>\n
function <\/span>noise = makenoise(k, a)<\/div>\n
% Create the noise matrix<\/span><\/div>\n
% k is the matrix size (scalar)<\/span><\/div>\n
% a is the positive exponent (scalar)<\/span><\/div>\n
% noise are noise values with range [-1,1]<\/span><\/div>\n
m = randn(k);<\/div>\n
mf = fftshift(fft2(m));<\/div>\n
d = ((1:k)-(k\/2)-1).^2;<\/div>\n
dd = sqrt(d(:) + d(:)’);<\/div>\n
filt = dd .^ -a;<\/div>\n
filt(isinf(filt))=1;<\/div>\n
ff = mf .* filt;<\/div>\n
b = ifft2(ifftshift(ff));<\/div>\n
noise = rescale(b,-1,1);<\/div>\n
end<\/span><\/div>\n<\/div>\n

<\/h3>\n

\u753b\u50cf\u306e\u7d50\u5408\u3082\u30b7\u30fc\u30e0\u30ec\u30b9\u306b<\/h3>\n
\n

\u3064\u306a\u304c\u3063\u305f\u753b\u50cf\u306e\u3088\u3046\u306b\u914d\u7f6e\u3059\u308b\u3053\u3068\u304c\u3067\u304d\u308b\u7279\u6027\u304c\u3042\u308a\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u00a0parula<\/span> \u30ab\u30e9\u30fc\u30de\u30c3\u30d7\u3092\u4f7f\u7528\u3057\u305f\u884c\u5217\u306e\u7aef\u304c\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u3064\u306a\u304c\u3063\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/p>\n<\/div>\n

\n
\n
figure()<\/div>\n<\/div>\n
\n
tiledlayout(3, 3, TileSpacing=‘none’<\/span>, Padding=‘tight’<\/span>)<\/div>\n<\/div>\n
\n
for <\/span>i = 1:9<\/div>\n<\/div>\n
\n
\u00a0\u00a0\u00a0\u00a0nexttile()<\/div>\n<\/div>\n
\n
\u00a0\u00a0\u00a0\u00a0imagesc(bScaled)<\/div>\n<\/div>\n
\n
\u00a0\u00a0\u00a0\u00a0set(gca,‘XTickLabel’<\/span>,[],‘ytickLabel’<\/span>,[])<\/div>\n<\/div>\n
\n
end<\/span><\/div>\n<\/div>\n<\/div>\n
\"\"<\/div>\n
<\/div>\n

\u9006\u306b\u4f5c\u696d\uff1a\u6307\u6570\u3092\u63a8\u5b9a\u3057\u3066\u30ce\u30a4\u30ba\u3092\u5206\u985e\u3059\u308b<\/h2>\n
\uff11\u6b21\u5143\uff08\u30d9\u30af\u30c8\u30eb\uff09\u306e\u30ed\u30fc\u30d1\u30ef\u30fc\u30ce\u30a4\u30ba\u306f\u3001\uff12\u6b21\u5143\u306e\u5834\u5408\u3068\u540c\u3058\u30de\u30af\u30ed\u30ec\u30d9\u30eb\u306e\u4e18\u3068\u30de\u30a4\u30af\u30ed\u30ec\u30d9\u30eb\u306e\u30c6\u30af\u30b9\u30c1\u30e3\u3092\u6301\u3063\u3066\u3044\u307e\u3059\u3002\u4ee5\u4e0b\u306f\u3001\u6307\u6570 \u03b1=1\u00a0<\/span>\u3067\u5b9a\u7fa9\u3055\u308c\u305f\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\u306e1000\u500b\u306e\u5024\u3092\u30d7\u30ed\u30c3\u30c8\u3057\u3066\u3044\u307e\u3059\u3002<\/div>\n
\n
\n
rng default<\/span> % Parameter 1. random number generator seed<\/span><\/div>\n<\/div>\n
\n
k = 1000; % Parameter 2. size of the vector, must be even.<\/span><\/div>\n<\/div>\n
\n
m = randn(k,1);<\/div>\n<\/div>\n
\n
<\/div>\n<\/div>\n
\n
mf = fftshift(fft(m));<\/div>\n<\/div>\n
\n
<\/div>\n<\/div>\n
\n
a = 1; % Parameter 3. 1\/f\u1d45 exponent<\/span><\/div>\n<\/div>\n
\n
d = sqrt(((1:k).’-(k\/2)-1).^2);<\/div>\n<\/div>\n
\n
filt = d .^ (-a\/2); % frequency filter for 1D<\/span><\/div>\n<\/div>\n
\n
filt(isinf(filt))=1;<\/div>\n<\/div>\n
\n
<\/div>\n<\/div>\n
\n
ff = mf .* filt; % apply the filter<\/span><\/div>\n<\/div>\n
\n
v = ifft(ifftshift(ff)); % power-law noise vector<\/span><\/div>\n<\/div>\n
\n
vScaled = rescale(v,-1,1); % scaled power-law noise [-1,1]<\/span><\/div>\n<\/div>\n
\n
<\/div>\n<\/div>\n
\n
figure()<\/div>\n<\/div>\n
\n
plot(vScaled)<\/div>\n<\/div>\n
\n
grid on<\/span><\/div>\n<\/div>\n
\n
title(‘1D power-law noise’<\/span>)<\/div>\n<\/div>\n
\n
subtitle(‘\u03b1 = 1’<\/span>)<\/div>\n<\/div>\n<\/div>\n
\"\"<\/div>\n
\u30ce\u30a4\u30ba\u306e\u8272\u3092\u5206\u985e\u3057\u305f\u3044\u3068\u3057\u307e\u3059\u3002\u6307\u6570\u5024\u306f\u3001log-log\u5ea7\u6a19\u306b\u304a\u3051\u308b $1\/f^\u03b1$ \u30d1\u30ef\u30fc\u30b9\u30da\u30af\u30c8\u30eb\u306e\u50be\u304d\u3068\u3057\u3066\u8fd1\u4f3c\u3067\u304d\u307e\u3059\u3002MATLAB \u306e Signal Processing Toolbox \u306e pspectrum<\/span> \u95a2\u6570\u3092\u4f7f\u3063\u3066\u3053\u306e\u30bf\u30b9\u30af\u3092\u7c21\u5358\u306b\u884c\u3046\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/div>\n
\n
\n
% Compute the power and frequency of the power-law noise vector<\/span><\/div>\n<\/div>\n
\n
% Requires signal processing toolbox<\/span><\/div>\n<\/div>\n
\n
[power, freq] = pspectrum(vScaled);<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Apply the log transform<\/span><\/div>\n<\/div>\n
\n
freqLog = log(freq);<\/div>\n<\/div>\n
\n
powerLog = log(power);<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Remove inf values<\/span><\/div>\n<\/div>\n
\n
infrm = isinf(freqLog) | isinf(powerLog);<\/div>\n<\/div>\n
\n
freqLog(infrm) = [];<\/div>\n<\/div>\n
\n
powerLog(infrm) = [];<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Fit the relationship between log-power and log-frequency<\/span><\/div>\n<\/div>\n
\n
% Requires the Curve Fitting toolbox<\/span><\/div>\n<\/div>\n
\n
F = fit(freqLog,powerLog,‘poly1’<\/span>);<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Plot the power density<\/span><\/div>\n<\/div>\n
\n
figure()<\/div>\n<\/div>\n
\n
plot(freqLog,powerLog)<\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Add the linear fit<\/span><\/div>\n<\/div>\n
\n
hold on<\/span><\/div>\n<\/div>\n
\n
h = plot(F);<\/div>\n<\/div>\n
\n
h.AffectAutoLimits = ‘off’<\/span>;<\/div>\n<\/div>\n
\n
grid on<\/span><\/div>\n<\/div>\n
\n
axis tight<\/span><\/div>\n<\/div>\n
\n
%<\/span><\/div>\n<\/div>\n
\n
% Print the slope in the title<\/span><\/div>\n<\/div>\n
\n
coeffs = coeffvalues(F);<\/div>\n<\/div>\n
\n
xlabel(‘log frequency’<\/span>)<\/div>\n<\/div>\n
\n
ylabel(‘log power spectrum’<\/span>)<\/div>\n<\/div>\n
\n
title(sprintf(‘Slope = %.2f’<\/span>, coeffs(1)))<\/div>\n<\/div>\n<\/div>\n
\"\"<\/div>\n
\u8fd1\u4f3c\u76f4\u7dda\u306e\u50be\u304d\u306f -1.05 \u3067\u3042\u308a\u3001\u3053\u308c\u306b\u3088\u308a\u3053\u306e\u4fe1\u53f7\u306f\u30d4\u30f3\u30af\u30ce\u30a4\u30ba\uff08\u03b1=1<\/span>\uff09\u3068\u5206\u985e\u3055\u308c\u307e\u3059\u3002<\/div>\n

\u307e\u3068\u3081<\/h2>\n