自联想神经网络采用一种带有瓶颈层的特殊结构，且具有单位总增益。
The AANN adopted a special structure with a bottle-neck layer and had a unit overall gain.
这就要求电压的总增益达到109，因此就需要很多放大器级联起来。
This requires an overall voltage gain of 109, so a number of voltage gain stages will be required.
负反馈的最重要作用在于使放大器总增益不至于因基本放大器增益的改变而变化，其总增益的大小完全取决于反馈网络的元件参数。
The most important effect of this is to make the overall amplifier gain almost immune to changes in the amplifier unit gain, and dependent almost entirely on the feedback network components.
在此基础上提出了旨在减小杂散电平的电路优化设计方法，其中包括在满足上变额总增益要求的条件下，电路各级增益或衰减的配置、本振功率的确定等，最后给出应用实例。
On this base, the optimization of circuits for decreasing the spurious level including determination of stage gain. loss and LO power is proposed. Finially, the application example is given.
用单位增益缓冲器构成的开关电容滤波器（SCF），若能消除寄生电容引起的“阻性”寄生，则可用于高频设计，总寄生灵敏度会因此大大降低。
The unity gain buffer will be good for designing high frequency SCF if its resistive effect can be eliminated and then the overall parasitic sensitivity will be greatly lowered.
设计中引入自动增益控制(agc)方法，在满足输出信号幅度相对稳定的情况下，调整总放大倍数在10 000倍范围内变化。
The introduction of Automatic Gain Control (AGC) method can adjust the total magnification at the range of 10 000 when the output signal amplitude is relatively stable.
设计中引入自动增益控制(agc)方法，在满足输出信号幅度相对稳定的情况下，调整总放大倍数在10 000倍范围内变化。
The introduction of Automatic Gain Control (AGC) method can adjust the total magnification at the range of 10 000 when the output signal amplitude is relatively stable.
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