STEM与日常科技·英语30篇（3）
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Fourier Transform Intuition in Signal Processing
傅里叶变换在信号处理中的直觉
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Any repeating signal—from a guitar note to Wi-Fi data—can be broken down into pure sine waves of different frequencies and strengths.任何周期性信号——从吉他音符到Wi-Fi数据——都能分解为不同频率和强度的纯正弦波。
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The Fourier transform is the mathematical tool that reveals which frequencies are present and how much each contributes.傅里叶变换是一种数学工具，能揭示信号中包含哪些频率，以及各频率成分的贡献程度。
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Noise-cancelling headphones use it to identify incoming low-frequency rumbles, then generate opposing waves to cancel them.主动降噪耳机利用它识别传入的低频嗡鸣，再生成反向声波将其抵消。
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JPEG image compression discards high-frequency details our eyes barely notice—keeping only essential Fourier components.JPEG图像压缩会舍弃人眼几乎察觉不到的高频细节，仅保留关键的傅里叶分量。
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Your voice call stays clear over weak signals because phones transmit dominant vocal frequencies, not raw audio waveforms.即使信号微弱，你的语音通话依然清晰，因为手机传输的是人声的主要频率成分，而非原始音频波形。
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Earthquake sensors apply Fourier analysis to separate dangerous slow waves from harmless high-frequency vibrations in real time.地震传感器实时应用傅里叶分析，将危险的慢速波动与无害的高频振动分离开来。
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It’s like hearing an orchestra and instantly knowing which instruments play loud, soft, high, or low—all at once.这就像听交响乐时，瞬间分辨出哪些乐器奏得响亮、轻柔、高亢或低沉——且同时感知全部。
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Rather than seeing signals as wiggles on a screen, Fourier thinking sees them as recipes of underlying tones.傅里叶思维不把信号看作屏幕上晃动的波形，而视其为一组基础音调构成的‘配方’。