{"id":52804,"date":"2025-08-11T19:44:31","date_gmt":"2025-08-11T11:44:31","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/52804.html"},"modified":"2025-08-11T19:44:31","modified_gmt":"2025-08-11T11:44:31","slug":"%e3%80%8amatlab%e6%95%99%e5%ad%a6%e5%bb%ba%e6%a8%a1%e6%96%b9%e6%b3%95%e4%b8%8e%e5%ae%9e%e8%b7%b5%ef%bc%88%e7%ac%ac%e4%b8%89%e7%ab%a0%ef%bc%89%e3%80%8b%e5%ad%a6%e4%b9%a0%e7%ac%94%e8%ae%b0","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/52804.html","title":{"rendered":"\u300aMatlab\u6559\u5b66\u5efa\u6a21\u65b9\u6cd5\u4e0e\u5b9e\u8df5\uff08\u7b2c\u4e09\u7ae0\uff09\u300b\u5b66\u4e60\u7b14\u8bb0\u2014\u2014Matlab\u5feb\u901f\u5165\u95e8"},"content":{"rendered":"

\u76ee\u5f55<\/p>\n

\n

2.1\u5feb\u901f\u5165\u95e8\u6848\u4f8b<\/p>\n

1. \u5229\u7528Matlab\u4ece\u5916\u754c\u5bfc\u5165\u6570\u636e<\/p>\n

2. \u6570\u636e\u63a2\u7d22\u548c\u5efa\u6a21<\/p>\n

3. \u53d1\u5e03<\/p>\n

2.2 \u5e38\u7528\u6280\u5de7<\/p>\n

1. \u5e38\u7528\u6807\u70b9\u7684\u529f\u80fd<\/p>\n

2. \u5e38\u7528\u64cd\u4f5c\u6307\u4ee4<\/p>\n

3.\u6307\u4ee4\u7f16\u8f91\u64cd\u4f5c\u952e<\/p>\n

4. MATLAB\u6570\u636e\u7c7b\u578b<\/p>\n

2.3 MATLAB \u5f00\u53d1\u6a21\u5f0f<\/p>\n

1. \u547d\u4ee4\u884c\u6a21\u5f0f<\/p>\n

2. \u811a\u672c\u6a21\u5f0f<\/p>\n

3. \u9762\u5411\u5bf9\u8c61\u6a21\u5f0f<\/p>\n

4. \u4e09\u79cd\u6a21\u5f0f\u914d\u5408<\/p>\n<\/p>\n

2.1\u5feb\u901f\u5165\u95e8\u6848\u4f8b<\/h3>\n

1. \u5229\u7528Matlab\u4ece\u5916\u754c\u5bfc\u5165\u6570\u636e<\/h5>\n

Step1.1\u00a0\u5728\u5f53\u524d\u6587\u4ef6\u5939\u4e2d\u9009\u53d6\u9700\u8981\u7684\u6570\u636e\u6587\u4ef6，\u53f3\u51fb\u201c\u5bfc\u5165\u6570\u636e\u201d<\/p>\n

Step1.2\u00a0\u70b9\u51fb\u201c\u5bfc\u5165\u6240\u9009\u5185\u5bb9\u201d<\/p>\n

\"\"<\/p>\n

2. \u6570\u636e\u63a2\u7d22\u548c\u5efa\u6a21<\/h5>\n

Step2.1\u00a0\u67e5\u770b\u6570\u636e\u7edf\u8ba1\u4fe1\u606f：\u53cc\u51fb\u5de5\u4f5c\u533a，\u5f97\u5230\u53d8\u91cf\u7684\u8be6\u7ec6\u7edf\u8ba1\u4fe1\u606f<\/p>\n

\"\"<\/p>\n

Step2.2\u00a0\u83b7\u53d6\u53ef\u89c6\u5316\u7ed3\u679c：\u5728\u5de5\u4f5c\u533a\u9009\u4e2d\u53d8\u91cfDataNum\u548cPclose，\u5728\u201c\u7ed8\u56fe\u201d\u9762\u677f\u4e2d\u5355\u51fbplot\u56fe\u6807，\u5f97\u5230\u4e24\u4e2a\u53d8\u91cf\u53ef\u89c6\u5316\u7ed3\u679c，\u4e5f\u53ef\u4ee5\u5728\u547d\u4ee4\u7a97\u53e3\u533a\u663e\u793a\u7ed8\u5236\u6b64\u56fe\u7684\u547d\u4ee4：<\/p>\n

>> plot(DateNum,Pclose) <\/p>\n

\u5728Matlab\u4e2dplot\u51fd\u6570\u7528\u4e8e\u7ed8\u5236\u4e8c\u7ef4\u7ebf\u56fe，\u7ed8\u5236\u6a2a\u8f74\u4e3aX，\u7ad6\u8f74\u4e3aY\u4e8c\u7ef4\u7ebf\u56fe，Y\u503c\u4e0eX\u503c\u4e00\u4e00\u5bf9\u5e94<\/p>\n

plot(X,Y) <\/p>\n

\u5982\u679c X \u548c Y \u90fd\u662f\u5411\u91cf，\u5219\u5b83\u4eec\u7684\u957f\u5ea6\u5fc5\u987b\u76f8\u540c\u3002plot \u51fd\u6570\u7ed8\u5236 Y \u5bf9 X \u7684\u56fe\u3002<\/p>\n<\/p>\n

\u5982\u679c X \u548c Y \u5747\u4e3a\u77e9\u9635，\u5219\u5b83\u4eec\u7684\u5927\u5c0f\u5fc5\u987b\u76f8\u540c\u3002plot \u51fd\u6570\u7ed8\u5236 Y \u7684\u5217\u5bf9 X \u7684\u5217\u7684\u56fe\u3002<\/p>\n<\/p>\n

\u5982\u679c X \u6216 Y \u4e2d\u7684\u4e00\u4e2a\u662f\u5411\u91cf，\u800c\u53e6\u4e00\u4e2a\u662f\u77e9\u9635，\u5219\u77e9\u9635\u7684\u5404\u7ef4\u4e2d\u5fc5\u987b\u6709\u4e00\u7ef4\u4e0e\u5411\u91cf\u7684\u957f\u5ea6\u76f8\u7b49\u3002\u5982\u679c\u77e9\u9635\u7684\u884c\u6570\u7b49\u4e8e\u5411\u91cf\u957f\u5ea6，\u5219 plot \u51fd\u6570\u7ed8\u5236\u77e9\u9635\u4e2d\u7684\u6bcf\u4e00\u5217\u5bf9\u5411\u91cf\u7684\u56fe\u3002\u5982\u679c\u77e9\u9635\u7684\u5217\u6570\u7b49\u4e8e\u5411\u91cf\u957f\u5ea6，\u5219\u8be5\u51fd\u6570\u7ed8\u5236\u77e9\u9635\u4e2d\u7684\u6bcf\u4e00\u884c\u5bf9\u5411\u91cf\u7684\u56fe\u3002\u5982\u679c\u77e9\u9635\u4e3a\u65b9\u9635，\u5219\u8be5\u51fd\u6570\u7ed8\u5236\u6bcf\u4e00\u5217\u5bf9\u5411\u91cf\u7684\u56fe\u3002<\/p>\n

clc;
\nclear;<\/p>\n

% \u7ed8\u5236
\nx = linspace(0,2*pi);
\ny1 = sin(x);
\ny2 = cos(x);
\nplot(x,y1,x,y2)
\ntitle('y1=sin(x), y2=cos(x)')
\nxlabel('X(m)')
\nylabel('Y(m)')<\/p>\n

\"\"<\/p>\n

Step2.3\u00a0\u5229\u7528\u591a\u9879\u5f0f\u62df\u5408\u547d\u4ee4<\/p>\n

>> p = polyfit(DateNum,Pclose,1); %\u591a\u9879\u5f0f\u62df\u5408
\n>> value = p(1); %\u5c06\u659c\u7387\u8d4b\u503c\u7ed9value
\nvalue =
\n 0.1212 <\/p>\n

\u5728MATLAB\u4e2dpolyfit\u51fd\u6570\u662f\u7528\u6765\u8fdb\u884c\u591a\u9879\u5f0f\u62df\u5408\u7684\u3002\u5176\u6570\u5b66\u539f\u7406\u662f\u57fa\u4e8e\u6700\u5c0f\u4e8c\u4e58\u6cd5\u8fdb\u884c\u62df\u5408\u7684\u3002\u5177\u4f53\u4f7f\u7528\u8bed\u6cd5\u662f：<\/p>\n

p = polyfit(x,y,n); % \u5176\u4e2dx,y\u8868\u793a\u9700\u8981\u62df\u5408\u7684\u5750\u6807\u70b9，\u5927\u5c0f\u9700\u8981\u4e00\u6837； n\u8868\u793a\u591a\u9879\u5f0f\u62df\u5408\u7684\u6b21\u6570\u3002 % \u8fd4\u56de\u503cp\u8868\u793a\u591a\u9879\u5f0f\u62df\u5408\u7684\u7cfb\u6570，\u7cfb\u6570\u4ece\u9ad8\u5230\u4f4e\u6392\u5217<\/p>\n

Step2.4\u00a0\u7528help\u67e5\u8be2\u7684\u65b9\u6cd5\u53ef\u4ee5\u5f88\u5feb\u5f97\u5230\u8ba1\u7b97\u6700\u5927\u56de\u64a4\u7684\u4ee3\u7801<\/p>\n

>> MaxDD = maxdrawdown(Pclose); %\u8ba1\u7b97\u6700\u5927\u56de\u64a4
\n>> risk = MaxDD %\u5c06\u6700\u5927\u56de\u64a4\u8d4b\u503c\u7ed9risk，\u4f5c\u4e3a\u80a1\u7968\u98ce\u9669
\nrisk =
\n 0.1155 <\/p>\n

Step2.5\u00a0\u91cd\u65b0\u9009\u62e9\u6570\u636e\u6587\u4ef6\u5e76\u53f3\u51fb，\u5728\u5feb\u6377\u83dc\u5355\u4e2d\u9009\u62e9\u201c\u5bfc\u5165\u6570\u636e\u201d\u9879，\u9009\u62e9\u201c\u751f\u6210\u811a\u672c\u201d，\u5e76\u4fdd\u5b58<\/p>\n

Step2.6\u00a0\u4ece\u547d\u4ee4\u5386\u53f2\u4e2d\u9009\u62e9\u6709\u7528\u7684\u547d\u4ee4\u590d\u5236\u5230 Step2.5 \u751f\u6210\u7684\u811a\u672c，\u5f97\u5230\u5b8c\u6574\u811a\u672c<\/p>\n

3. \u53d1\u5e03<\/h5>\n

\u5c55\u793a\u5f62\u5f0f：<\/p>\n

\u2460\u80fd\u72ec\u7acb\u8fd0\u884c\u7684\u7a0b\u5e8f，\u6bd4\u5982\u811a\u672c<\/p>\n

\u2461\u62a5\u544a\u6216\u8bba\u6587（\u5e38\u89c1\u4e14\u4f7f\u7528）<\/p>\n

\u2462\u8f6f\u4ef6\u548c\u5e94\u7528（\u4e2d\u5927\u578b\u9879\u76ee）<\/p>\n

Step3.1 \u5728\u811a\u672c\u7f16\u8f91\u5668\u7684\u201c\u53d1\u5e03\u201d\u9762\u677f，\u4ece\u5176\u4e0b\u62c9\u83dc\u5355\u4e2d\u9009\u62e9\u201c\u7f16\u8f91\u53d1\u5e03\u201d\u9009\u9879，\u6253\u5f00\u53d1\u5e03\u201c\u7f16\u8f91\u914d\u7f6e\u201d\u754c\u9762<\/p>\n

\"\"<\/p>\n

Step3.2 \u9009\u62e9\u201c\u8f93\u51fa\u6587\u4ef6\u683c\u5f0f\u201d，\u9ed8\u8ba4html（word\u66f4\u5e38\u7528，\u4fbf\u4e8e\u7f16\u8f91，\u5c24\u5176\u662f\u5bf9\u4e8e\u5199\u62a5\u544a\u6216\u8bba\u6587），\u7136\u540e\u5355\u51fb\u201c\u53d1\u5e03\u201d\u6309\u94ae，\u5c31\u53ef\u4ee5\u8fd0\u884c\u7a0b\u5e8f\u4e86，\u4e4b\u540e\u4f1a\u5f97\u5230\u4e00\u4efd\u8be6\u7ec6\u7684\u8fd0\u884c\u62a5\u544a，\u5305\u62ec\u76ee\u5f55\u3001\u5b9e\u73b0\u8fc7\u7a0b\u3001\u4e3b\u8981\u7ed3\u679c\u3001\u56fe\u3002<\/p>\n<\/p>\n

2.2 \u5e38\u7528\u6280\u5de7<\/h3>\n

1. \u5e38\u7528\u6807\u70b9\u7684\u529f\u80fd<\/h5>\n\n \u5e38\u7528\u6807\u70b9\u7684\u529f\u80fd<\/p>\n\n\n\n\n\n\n\n\n\n\n
\u9017\u53f7（，）<\/td>\n\n

\u663e\u793a\u8ba1\u7b97\u7ed3\u679c\u7684\u6307\u4ee4\u4e0e\u5176\u540e\u9762\u7684\u6307\u4ee4\u4e4b\u95f4\u7684\u5206\u9694；\u7528\u4f5c\u8f93\u5165\u91cf\u4e0e\u8f93\u5165\u91cf\u00a0\u4e4b\u95f4\u7684\u5206\u9694；\u7528\u4f5c\u6570\u7ec4\u5143\u7d20\u7684\u5206\u9694<\/p>\n<\/td>\n<\/tr>\n

\u5206\u53f7（：）<\/td>\n\u7528\u4f5c\u4e0d\u663e\u793a\u8ba1\u7b97\u7ed3\u679c\u6307\u4ee4\u7684\u7ed3\u5c3e\u6807\u5fd7;\u7528\u4f5c\u4e0d\u663e\u793a\u8ba1\u7b97\u7ed3\u679c\u7684\u6307\u4ee4\u4e0e\u5176\u540e\u9762\u7684\u00a0\u6307\u4ee4\u4e4b\u95f4\u7684\u5206\u9694;\u7528\u4f5c\u6570\u7ec4\u884c\u95f4\u7684\u5206\u9694<\/td>\n<\/tr>\n
\u5192\u53f7（：）<\/td>\n\u7528\u4ee5\u751f\u6210\u4e00\u7ef4\u6570\u503c\u6570\u7ec4;\u7528\u4f5c\u5355\u4e0b\u6807\u63f4\u5f15\u65f6,\u8868\u793a\u5168\u90e8\u5143\u7d20\u6784\u6210\u7684\u957f\u5217;\u7528\u4f5c\u591a\u00a0\u4e0b\u6807\u63f4\u5f15\u65f6，\u8868\u793a\u5bf9\u5e94\u7ef4\u5ea6\u4e0a\u7684\u5168\u90e8\u5143\u7d20<\/td>\n<\/tr>\n
\u6ce8\u91ca\u53f7（%）<\/td>\n\u7531\u5b83\u8d77\u5934\u7684\u6240\u6709\u7269\u7406\u884c\u88ab\u89c6\u4e3a\u975e\u6267\u884c\u7684\u6ce8\u91ca<\/td>\n<\/tr>\n
\u5355\u5f15\u53f7（\u2018\u2019）<\/td>\n\u5b57\u7b26\u4e32\u6807\u8bb0\u7b26<\/td>\n<\/tr>\n
\u5706\u62ec\u53f7（ ）<\/td>\n\u5728\u6570\u7ec4\u63f4\u5f15\u65f6\u7528;\u51fd\u6570\u6307\u4ee4\u65f6\u8868\u793a\u8f93\u5165\u53d8\u91cf<\/td>\n<\/tr>\n
\u65b9\u62ec\u53f7[ ]<\/td>\n\u00a0\u8f93\u5165\u6570\u7ec4\u65f6\u7528;\u51fd\u6570\u6307\u4ee4\u65f6\u8868\u793a\u8f93\u51fa\u53d8\u91cf<\/td>\n<\/tr>\n
\u82b1\u62ec\u53f7{ }\u00a0<\/td>\n\u5143\u80de\u6570\u7ec4\u6807\u8bb0\u7b26<\/td>\n<\/tr>\n
\u7eed\u884c\u53f7(…)<\/td>\n\u7531\u4e09\u4e2a\u4ee5\u4e0a\u8fde\u7eed\u9ed1\u70b9\u6784\u6210\u3002\u53ef\u89c6\u4e3a\u5176\u4e0b\u7684\u7269\u7406\u884c\u662f\u8be5\u884c\u7684\u903b\u8f91\u7ee7\u7eed，\u4ee5\u6784\u6210\u4e00\u4e2a\u8f83\u957f\u7684\u5b8c\u6574\u6307\u4ee4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
2. \u5e38\u7528\u64cd\u4f5c\u6307\u4ee4<\/h5>\n\n \u5e38\u7528\u64cd\u4f5c\u6307\u4ee4<\/p>\n\n\n\n\n\n\n\n
clc<\/td>\n\u6e05\u9664\u6307\u4ee4\u7a97\u53e3\u4e2d\u663e\u793a\u7684\u5185\u5bb9<\/td>\n<\/tr>\n
clear<\/td>\n\u6e05\u9664MATLAB\u5de5\u4f5c\u7a7a\u95f4\u4e2d\u4fdd\u5b58\u7684\u53d8\u91cf<\/td>\n<\/tr>\n
close all<\/td>\n\u5173\u95ed \u6240\u6709\u6253\u5f00\u7684\u56fe\u5f62\u7a97\u53e3<\/td>\n<\/tr>\n
clf<\/td>\n\u6e05\u9664\u56fe\u5f62\u7a97\u7684\u5185\u5bb9<\/td>\n<\/tr>\n
edit<\/td>\n\u6253\u5f00m\u6587\u4ef6\u7f16\u8f91\u5668<\/td>\n<\/tr>\n
disp<\/td>\n\u663e\u793a\u53d8\u91cf\u7684\u5185\u5bb9<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
3.\u6307\u4ee4\u7f16\u8f91\u64cd\u4f5c\u952e<\/h5>\n\n\n\n\n\n
\u2191<\/td>\n\u524d\u5bfb\u8c03\u56de\u5df2\u8f93\u5165\u8fc7\u7684\u6307\u5b9a\u884c<\/td>\n<\/tr>\n
\u2193<\/td>\n\u540e\u5bfb\u8c03\u56de\u5df2\u8f93\u4eba\u8fc7\u7684\u6307\u5b9a\u884c<\/td>\n<\/tr>\n
Tab<\/td>\n\u8865\u5168\u547d\u4ee4<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n
4. MATLAB\u6570\u636e\u7c7b\u578b<\/h5>\n

\"\"<\/p>\n

\u5143\u80de\u6570\u7ec4\u662fMATLAB\u4e2d\u7684\u4e00\u79cd\u7279\u6b8a\u6570\u636e\u7c7b\u578b，\u53ef\u4ee5\u5c06\u5143\u80de\u6570\u7ec4\u89c6\u4e3a\u65e0\u6240\u4e0d\u5305\u7684\u901a\u7528\u77e9\u9635，\u6216\u53eb\u5e7f\u4e49\u77e9\u9635\u3002\u7ec4\u6210\u5143\u80de\u6570\u7ec4\u7684\u5143\u7d20\u53ef\u4ee5\u662f\u4efb\u4f55\u6570\u636e\u7c7b\u578b\u7684\u5e38\u6570\u6216\u5e38\u91cf，\u6bcf\u4e2a\u5143\u7d20\u4e5f\u53ef\u4ee5\u5177\u6709\u4e0d\u540c\u7684\u5c3a\u5bf8\u548c\u5185\u5b58\u5360\u7528\u7a7a\u95f4，\u6bcf\u4e2a\u5143\u7d20\u7684\u5185\u5bb9\u4e5f\u53ef\u4ee5\u5b8c\u5168\u4e0d\u540c\u3002<\/p>\n

\u8868\u5728\u652f\u6301\u6570\u636e\u7c7b\u578b\u65b9\u9762\u4e0e\u5143\u80de\u6570\u7ec4\u76f8\u4f3c，\u80fd\u5305\u542b\u6240\u6709\u6570\u636e\u7c7b\u578b，\u4f46\u8868\u5728\u5c55\u793a\u6570\u636e\u64cd\u4f5c\u6570\u636e\u4e0a\u66f4\u6709\u4f18\u52bf\u3002<\/p>\n

2.3 MATLAB \u5f00\u53d1\u6a21\u5f0f<\/h3>\n

1. \u547d\u4ee4\u884c\u6a21\u5f0f<\/h5>\n

\u5373\u5728\u547d\u4ee4\u884c\u7a97\u53e3\u533a\u8fdb\u884c\u4ea4\u4e92\u5f0f\u7684\u5f00\u53d1\u6a21\u5f0f\u3002\u547d\u4ee4\u884c\u6a21\u5f0f\u975e\u5e38\u7075\u6d3b,\u5e76\u4e14\u80fd\u591f\u5f88\u5feb\u7ed9\u51fa\u7ed3\u679c\u3002\u6240\u4ee5\u9002\u5408\u5355\u4e2a\u7684\u5c0f\u578b\u79d1\u5b66\u8ba1\u7b97\u95ee\u9898\u7684\u6c42\u89e3，\u6bd4\u5982\u89e3\u65b9\u7a0b\u3001\u62df\u5408\u66f2\u7ebf\u7b49\u64cd\u4f5c;\u4e5f\u6bd4\u8f83\u9002\u5408\u9879\u76ee\u7684\u63a2\u7d22\u5206\u6790\u3001\u5efa\u6a21\u7b49\u5de5\u4f5c，\u6bd4\u5982\u5728\u5165\u95e8\u6848\u4f8b\u4e2d\u4ecb\u7ecd\u7684\u6570\u636e\u7ed8\u56fe\u3001\u62df\u5408,\u6c42\u6700\u5927\u56de\u64a4\u3002\u547d\u4ee4\u884c\u6a21\u5f0f\u7684\u7f3a\u70b9\u662f\u4e0d\u4fbf\u4e8e\u91cd\u590d\u6267\u884c,\u4e5f\u4e0d\u4fbf\u4e8e\u81ea\u52a8\u5316\u6267\u884c\u79d1\u5b66\u8ba1\u7b97\u4efb\u52a1\u3002<\/p>\n

2. \u811a\u672c\u6a21\u5f0f<\/h5>\n

\u811a\u672c\u6a21\u5f0f\u662fMATLAB\u6700\u5e38\u89c1\u7684\u5f00\u53d1\u6a21\u5f0f，\u5728\u8be5\u6a21\u5f0f,\u6211\u4eec\u53ef\u4ee5\u5f88\u65b9\u4fbf\u5730\u8fdb\u884c\u4ee3\u7801\u7684\u4fee\u6539,\u4e5f\u53ef\u4ee5\u7ee7\u7eed\u66f4\u590d\u6742\u7684\u4efb\u52a1\u3002\u811a\u672c\u6a21\u5f0f\u7684\u4f18\u70b9\u662f\u4fbf\u4e8e\u91cd\u590d\u6267\u884c\u8ba1\u7b97,\u5e76\u53ef\u4ee5\u5c06\u6574\u4e2a\u8ba1\u7b97\u8fc7\u7a0b\u4fdd\u5b58\u5728\u811a\u672c\u4e2d,\u79fb\u690d\u6027\u6bd4\u8f83\u597d,\u540c\u65f6\u4e5f\u975e\u5e38\u7075\u6d3b\u3002<\/p>\n

3. \u9762\u5411\u5bf9\u8c61\u6a21\u5f0f<\/h5>\n

\u9762\u5411\u5bf9\u8c61\u7f16\u7a0b\u662f\u4e00\u79cd\u6b63\u5f0f\u7684\u7f16\u7a0b\u65b9\u6cd5,\u5b83\u5c06\u6570\u636e\u548c\u76f8\u5173\u64cd\u4f5c(\u65b9\u6cd5)\u5408\u5e76\u5230\u903b\u8f91\u7ed3\u6784(\u5bf9\u8c61)\u4e2d\u3002\u8be5\u65b9\u6cd5\u5177\u6709\u53ef\u63d0\u5347\u7ba1\u7406\u8f6f\u4ef6\u590d\u6742\u6027\u7684\u80fd\u529b,\u5728\u5f00\u53d1\u548c\u7ef4\u62a4\u5927\u578b\u5e94\u7528\u4e0e\u6570\u636e\u7ed3\u6784\u65f6\u5c24\u4e3a\u91cd\u8981\u3002 \u80fd\u591f\u5728MATLAB\u4e2d\u5b9a\u4e49\u7c7b\u5e76\u5e94\u7528\u9762\u5411\u5bf9\u8c61\u7684\u6807\u51c6\u8bbe\u8ba1\u6a21\u5f0f,\u53ef\u5b9e\u73b0\u4ee3\u7801\u91cd\u7528\u7ee7\u627f\u3001\u5c01\u88c5\u4ee5\u53ca\u53c2\u8003\u884c\u4e3a,\u3002MATLAB\u9762\u5411\u5bf9\u8c61\u5f00\u53d1\u6a21\u5f0f\u66f4\u9002\u5408\u7a0d\u5fae\u590d\u6742\u4e00\u4e9b\u7684\u9879\u76ee,\u66f4\u6709\u6548\u5730\u7ec4\u7ec7\u7a0b\u5e8f\u7684\u529f\u80fd\u6a21\u5757,\u4fbf\u4e8e\u9879\u76ee\u7684\u7ba1\u7406\u3001\u91cd\u590d\u4f7f\u7528，\u540c\u65f6\u4f7f\u5f97\u9879\u76ee\u66f4\u7b80\u6d01,\u66f4\u5bb9\u6613\u7ef4\u62a4\u3002<\/p>\n

4. \u4e09\u79cd\u6a21\u5f0f\u914d\u5408<\/h5>\n

\u4e09\u79cd\u5f00\u53d1\u6a21\u5f0f\u5e76\u4e0d\u662f\u5b64\u7acb\u7684，\u800c\u662f\u76f8\u4e92\u914d\u5408\u3001\u4e0d\u65ad\u63d0\u5347\u7684\u3002\u5728\u9879\u76ee\u521d\u671f，\u57fa\u672c\u4ee5\u547d\u4ee4\u884c\u7684\u811a\u672c\u6a21\u5f0f\u4e3a\u4e3b，\u9010\u6e10\u5f62\u6210\u811a\u672c；\u968f\u7740\u6210\u719f\u5ea6\u5929\u751f，\u5c31\u8981\u4f7f\u7528\u9762\u5411\u5bf9\u8c61\u7684\u5f00\u53d1\u6a21\u5f0f，\u5c06\u529f\u80fd\u6a21\u5757\u6539\u5199\u6210\u51fd\u6570\u7684\u5f62\u52bf，\u52a0\u5f3a\u7a0b\u5e8f\u91cd\u590d\u8c03\u7528\u3002 \u00a0<\/p><\/p>\n","protected":false},"excerpt":{"rendered":"

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