Numerical results show that the performance of systems with optical hard limiter is superior to that without optical hard limiter.
分析结果表明，基于修正素数码的光硬限幅器同步系统的误码性能优于无光硬限幅器系统的误码性能。
A learning algorithm based on a hard limiter for feedforward neural networks (NN) is presented, and is applied in solving classification problems on separable convex sets and disjoint sets.
提出了基于硬限幅功能函数的前向神经网络的分类学习算法，并将其应用于可分凸集或不交集合的分类。
A learning algorithm based on a hard limiter for feedforward neural networks (NN) is presented, and is applied in solving classification problems on separable convex sets and disjoint sets.
提出了基于硬限幅功能函数的前向神经网络的分类学习算法，并将其应用于可分凸集或不交集合的分类。
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