In this brief paper, a learning algorithm is developed for Deep Learning Neuro-Skin Neural Network to improve their learning properties. Neuroskin is a new type of neural network presented recently by the authors. It is comprised of a cellular membrane which has a neuron attached to each cell. The neuron is the cells nucleus. A neuroskin is modelled using finite elements. Each element of the finite element represents a cell. Each cells neuron has dendritic fibers which connects it to the nodes of the cell. On the other hand, its axon is connected to the nodes of a number of different neurons. The neuroskin is trained to contract upon receiving an input. The learning takes place during updating iterations using sensitivity analysis. It is shown that while the neuroskin can not present the desirable response, it improves gradually to the desired level.

中文翻译：

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深度学习神经-皮肤神经网络的训练

在这篇简短的论文中，为深度学习神经皮肤神经网络开发了一种学习算法，以改善其学习特性。Neuroskin 是作者最近提出的一种新型神经网络。它由细胞膜组成，每个细胞都有一个神经元。神经元是细胞核。神经皮肤使用有限元建模。有限元的每个元素代表一个单元格。每个细胞神经元都有树突状纤维，将其连接到细胞的节点。另一方面，它的轴突连接到许多不同神经元的节点。神经皮肤被训练在接收到输入时收缩。学习发生在使用敏感性分析的更新迭代期间。结果表明，虽然神经皮肤不能呈现理想的反应，