neural-net

基本解释

This would be accomplished by training a neural net to make two cuts.
把神经网络培训成能实现两个切割就可完成这种工作。
Finally, the outputs of every classify GMM will be fused by Neural Net (NN).
并采用神经网络实现各个分类高斯混合模型输出的融合。
Neural nets are also supposed to learn.
神经网络也可假定为可以学习。
Research Areas: robotics, neural net, Gaussian process, scientific computing, and software/ hardware development.
主要研究领域为冗余机器人，递归神经网络，高斯过程，科学计算和软硬件开发。
Similarly, in weight modification, a neural net can seek a weight distribution that minimizes error.
在权系数的调整中,神经网络将会找到一种将误差减少到最小的权系数的分配方式。