针对神经网络在潜在通路分析应用中的缺陷，提出了二进制神经网络集成(BNNE)算法。
To overcome the shortcomings of the sneak circuit analysis (SCA) based on BPNN, a binary neural network ensemble (BNNE) algorithm for the sneak circuit analysis (SCA) is proposed.
神经网络是一种非线性动力学系统，在二进制系统信道均衡实现方面得到非常成功的应用。
The neural network, which is a nonlinear dynamic system, has been successfully applied in the channel equalization of binary digital communication systems.
由于动态神经网络结构及权值确定困难，采用二进制与实数编码相结合的联合编码，用遗传算法优化得到神经网络结构及对应权值。
To rise above the difficulty of determining NN's structure and weights, the GA optimization algorithm is used to get them by combining binary encoding with real encoding.
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