FFT系数问题
我是一名软件工程师，第一次从事 DSP 工作。
我成功地使用了生成频谱的 FFT 库。我还了解 FFT 在输入和输出方面的工作原理，特别是两个输出数组的内容： 
现在，我的问题是我正在阅读一些新的研究报告，建议我提取：“FFT 系数的能量、方差和总和”。
什么是“FFT 系数”？这些是上面显示的实数和虚数数组的值吗？（根据我的理解）它们对应于组成余弦波和正弦波的幅度？
FFT 系数的“能量”是多少？这个术语是来自统计学还是来自 DSP？
I'm a software engineer working on DSP for the first time.
I'm successfully using an FFT library that produces frequency spectrums. I also understand how the FFT works in terms of its inputs and outputs, in particular the contents of the two output arrays:
Now, my problem is that I'm reading some new research reports that suggest that I extract: "the energy, variance, and sum of FFT coefficients".
What are the 'FFT coefficients'? Are those the values of the Real and Imaginary arrays shown above, which (from my understanding) correspond to the amplitudes of the constituent cosine and sine waves?
What is the 'energy' of the FFT coefficients? Is that terminology from statistics or from DSP?
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实数数组和虚数数组放在一起时可以表示一个复数数组。频域中复数数组的每个复数元素都可以被视为频率系数，并且具有幅度 ( sqrt(R*R + I*I) )。 Parseval 定理表明，所有频域复向量幅度（平方）的总和等于时域信号的能量（这可能需要涉及 FFT 长度的缩放因子，具体取决于您特定的 DFT/FFT 库实现）。
时域信号的一个例子是电线上的电压，当以伏特乘以安培换算为欧姆进行测量时，该电压代表功率，或者随着时间的推移，代表能量。在严格的数字情况下，“能量”一词可能源自物理学或工程学的历史用法，其中数字意味着可能会烧伤手指的东西。
The real and imaginary arrays, when put together, can represent a complex array. Every complex element of the complex array in the frequency domain can be considered a frequency coefficient, and has a magnitude ( sqrt(R*R + I*I) ). Parseval's theorem says that the sum of all the Frequency domain complex vector magnitudes (squared) is equal to the energy of the time domain signal (which may require a scaling factor involving the FFT length, depending on your particular DFT/FFT library implementation).
One example of a time domain signal is voltage on a wire, which when measured in Volts times Amps into Ohms represents power, or over time, energy. Probably the word "energy" in the strictly numerical case is derived from historical usage from physics or engineering, where the numbers meant something that could burn your fingers.