为证明他的论点，他和他的同事试图建造一个像黏菌一样工作的电路，能够学习并预测未来的信号。
To prove his contention, he and his colleagues set about building a circuit that would, like the slime mould, learn and predict future signals.
他发现，这些预测反应(或电路)行为的程序惊人的相似，甚至噪声特性都相同。
He has found that those equations, which predict the reaction's (or circuit's) behavior, are astonishingly similar, even in their noise properties.
利用该算法对线性预测系统的自相关数字电路进行了实验，并对算法的时间复杂性做了分析。
By utilizing this algorithm, we did an experiment about autocorrelation data circuit of linear forecast system and analyzed the tune complexity of the algorithm.
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