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)
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)
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)
Заменив в последней формуле на ![](data:image/png;base64,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) , получим систему линейных однородных уравнений относительно Фурье коэффициентов функции ![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABIAAAANCAYAAACkTj4ZAAAACXBIWXMAAA54AAAPKQESMTqDAAACFklEQVR4nK2SXUiTYRTHf1vvbJsu0bRI1F5bKzHDrC5MFAwMUiOUXXghLvoOisK+WCDpVbQgqC4MLTGiD1DJtMSQDOnCYo2KcKxIakhtLNuCzVqS7G17xwaLeRP+r57nPOf8OOf8HyEUCkksgoTYIfTbj81mxa/Oo3rrevk+2HeHFEMNdWUFCUU/XZPcHnpBRU0DG1dnJYLGem/yJqDFO/9VBo12d/JnSz0N/0AiSs0pxrQbLlzqQmcxIy5VRkGKWQeDY9Mcv3aVdemSfH/8doa2vfoFR4nAajfdpf/ZJ/bVGqKg83uq6RhwM/TKz4Sjhzz3R77pSknTLgm/SnidT6gubKHD9Z6B5kLWmkc4VCmiFw30vHZijYGMptOo6ktpba4K14ULv3tYlluAhqgPmoxyBh4dpOlEGw/77GRrlXI8JTuduc9TPJ/YEQXZ37kw7DTG29ZlLMf/ZYYgChmm1gq4XV6yM/NRScHIYHLenC9AWr5IWUl42QqFD+uUh/25WXFQiljCikAns78aIThNd9ct1lQZyR8+yZV7qzjatEvu6oNjkqLN26lIjbj2w8m8agMr09VxkKTWU6QJYvP4qCkQOXauXY7XbhuP5wS9Th6MK2k5LJIZXodgOdNLY+up+NwxHbls4eVoP8OeyqT/6P5TO+br7eRI0T0KZ29cTGqvUqWlvM60oPUHTMUJMSFp5n9o0UB/AUspsClXTmy7AAAAAElFTkSuQmCC) .
Вычислим определителя этой системы уравнений:
Следовательно, имеет место равенства
![](data:image/png;base64,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) , ![](data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAFkAAAAQCAYAAAB9XNMLAAAACXBIWXMAAA7VAAAOXgHWD721AAAG9UlEQVR4nO2Ye1DU1xXHP7uAsMsusDwMyEMQooAWykMqGhpICxhfQzREMA8TE5yWKhhHWyImZtRkaqZGI2mEakepJGjRqIlpKGNGRUKNoiiJRVQIKKLIY3ks7PLY3e7+1qySRdqaxrYZv3/s7/7uOfd3zvnec869s9Y6nU7PA3yvsB5JqO1tJOftXL6suUL84jWkxPjfL79+UBiW5KaaU1Q2dBM9JZrnMrJpPPEhrfZ9fLT1NXaX3kCvu0nQ1DSW/2omshG36QGMsKBosKWSgl1f4OrTRdOPY7GuP8hlK19+NNob23B/uick03H6GHNfnD4swTXnTtA86EB4aDAykZrqymN8Xq0lJdVyQ6pK3ucrjS9zZkz7r22WVt1G1flLuAdOxkNm9b3YsAjtQunHdAY9zq+fnoym4ysy3/4AR7kzrXPT8GkYIDxVQkF+LRVXrjE72GfI2sqDuRxolKHraMR/nB/N1X+h6JQdr2XOHNZ4yM/moj2Uz4adfax76bFhdYwk5KzNZfa6Vfhbi/4DIX8LejXF239HyMu7mDlB8p0/p6r9nHV5B4Rx4qLVhPhILUm+WHUeReQCYWznNIm83UV3SCOF3zfyN1l8vKfpNNvyPyMhezNJEZ5CP39vdxnxq94y63S1tTBoI8PZHpSdGhTOCkISktm+JIv6+TH4ym3Met19A0hkCiQiMd6BgTjSj7K9F721HboeJWJ7Bc4Ot0lRtjRjay9nUN1jsmGQDWhUqHoHBDtGuY3ioSEV03q9icG+DqxcYwn3HIW6W4lmgBH1+751TTD6eKcfORs3EP3iVsK0pTz76kbUU5IsSdb0abC1s7Mg8Z/h3NGDnOzpJ6i8nNawZBzamw3vUp50MZlo/7qKPfk7OKHxY15QFypFnKlNjJIy3lClFzv6BJKN1ZOdsRG/qHHUn3UkMzuM328qJDgplD9lLuOMNpBZPxnF0XJb8naswlVqw8Wj+3l/7w46xiQRoK6m+Iacou0rKS3Yzt5PKolLjaXlpoikhU8jM26kVs2xP29k+2E1YWM6+dJ6Kh6SfvZty+VQWR2JsyK40iFj0XPzDSSbNl432EZ58T4a1aaWou/RIbIXM3byDGZO9hXmRLp6aq8rSPF1Y7R+Cs79e/lov+vIt4t/B54BQUx71JelS5OFd5Vhs8RuDyEXmUrc2S+E55dkcDw5keY55aRNdTUt1IJcco2GqxrwltHf305FvZ5Vm5bikekktIswf1e0snHEhIXiFryAjHgXLlS9yoBOLHxifOwTzGgoZ/OJfpZnzafsnf1I9RKmv7SMwfYFbDiu4XjOL82+qpU3eHdPJVuK9tJ2eAe2rX5gJWHeL16huy6R3TUJHFiTPCQ+sbULsXNS0IqsGZDqsekVCU+pyOG2klUfqg5Dqou1QlzfwILkprYebO+B5FOlJ5kYnW5+lygUOF27TjN6ZJiIrj11BDvpWAwiLjV287CXXJi/qPTmqVv9UKx1Y0PuevrrPyVlZQNb8hYPa0/T34eNWGeMTMjMA2UtrFzzOu2ndxEREc/fz9fh6djOpZZRhHg5cfnrqwT4eQtrOxoqsPaIR956gewPPuSxZ7MEf5w11VzvkhMUIB2i/w0cnGT0GvqFrdGsodgNpw821gNmGvX6CUzwvcbfLrURZ1WB1P8Rnlk4f7hMHo2Hlx2q69WUHK3CN2YW4V72IxJsLJOKql6eShljnrNy9CMxTMxnxy/jH/cwRwo3o/KZzhtr5bxZuIeIlxcJej1NZ2lxHst4R5MNjfIqhduKcTUEMXvhC4Ysq8PKWU95yRm0Xb0oa+uod7+IjVRCWfVNof/r9L14h0Ux3t2eNg9Hru09idJHxZEvBnkyYzX78ncaDupIA2m3IgyKZrLrb3nvoIxHYqZSW91OpNNhCqulvJD1OjsL9lHTOtGsfzsoCVLpiFSwdOVv2Lw7h0v6sazIXizEZSZZ3dVMu0pLp8KdSLdBPvnjIeynRbI/P4fxK1Ygs71LZzFkUckfCtGGxglB3unQT1OfYVvRXyl1GDD0xWW3BIHkRJhGTRfK+PTjM6QtW2I+YFyDE9i6JWGIibe2mQ5cHo80z+XmPWEeG0s5Pd1URbKoVN6JMs1PizE9l61eP5QrqRfL171rEUrgrXVZqycNH+u/AKP/69cO9d/MXE/jOVa/WcTPF2UwRtRDrdKR50OiOVFSjEZrLPm7Y/SkeF4JnWhx15V5BJGZPpoLNZ2oBrGQi+2cDH0zDU/Fd786/S/DHLZxB3YUmHZApL2BvLeak+fP4uwyEr0IGRsaE3lXsTHLgie6DCtz9733jPl/wrA9QG/lzoKMVPaUVBA7b7lwTXqAe8ddr3AuAVGkB0TdT19+sHjw9859wD8A2AyK4o1fuAIAAAAASUVORK5CYII=) , ![](data:image/png;base64,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)
из которых, в силу полноты тригонометрической системы, выводим, что ![](data:image/png;base64,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) почти всюду в ![](data:image/png;base64,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) , что и требовалось доказать.
Достарыңызбен бөлісу: |