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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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ICAZMggFBgEACAEiBQAKgD0wwBj0CCV1jEgyAnxFIALyMVgZ9QyDBr2i8AJwN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\nAEAKBBIAQAoEEgBACgQSAEAK/w85N8sMt8TxrgAAAABJRU5ErkJggg==\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
" %% Time specifications:\n",
" Fs = 8000; % samples per second\n",
" dt = 1/Fs; % seconds per sample\n",
" StopTime = 0.25; % seconds\n",
" t = (0:dt:StopTime-dt)'; % seconds\n",
"\n",
" %% Sine wave:\n",
" Fc = 60; % hertz\n",
" x = cos(2*pi*Fc*t);\n",
"\n",
" % Plot the signal versus time:\n",
" figure;\n",
" plot(t,x);\n",
" xlabel('time (in seconds)');\n",
" title('Signal versus Time');\n",
" zoom xon;"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"x = 1960:1/12:1970;\n",
"y = rand(1,121);"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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RSIgJW6aRLi/Kft0C6IVAihVpxx1pCwMci7WphkBCTBgZe7ZcjQEORCBBf8QD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\n",
"text/plain": [
"<IPython.core.display.Image object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"plot(x,y)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Matlab",
"language": "matlab",
"name": "matlab"
},
"language_info": {
"codemirror_mode": "octave",
"file_extension": ".m",
"help_links": [
{
"text": "MetaKernel Magics",
"url": "https://github.com/calysto/metakernel/blob/master/metakernel/magics/README.md"
}
],
"mimetype": "text/x-octave",
"name": "matlab",
"version": "0.15.0"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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