Fourier Analysis
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【推荐级别】
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☆☆☆☆
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【下载次数】 |
6 次 |
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【作者】 |
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【出版社】 |
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【文件格式】 |
PDF
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【ISBN】 |
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【资料语言】 |
英文
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【文件大小】 |
295.65KB
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【上传时间】 |
2008-08-09
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【共享者】 |
ljxok8026
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资料说明：
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In this article we will compare the classical
methods of Fourier analysis with the newer
methods of wavelet analysis. Given a signal,
say a sound or an image, Fourier analysis
easily calculates the frequencies and
the amplitudes of those frequencies which make
up the signal. This provides a broad overview of
the characteristics of the signal, which is important
for theoretical considerations. However,
although Fourier inversion is possible under
certain circumstances, Fourier methods are not
always a good tool to recapture the signal, particularly
if it is highly nonsmooth: too much
Fourier information is needed to reconstruct
the signal locally. In these cases, wavelet analysis
is often very effective because it provides a
simple approach for dealing with local aspects
of a signal. Wavelet analysis also provides us with
new methods for removing noise from signals
that complement the classical methods of
Fourier analysis. These two methodologies are
major elements in a powerful set of tools for theoretical
and applied analysis.
This article contains many graphs of discrete
signals. These graphs were created by the computer
program FAWAV, A Fourier–Wavelet Analyzer,
being developed by the author.
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