Hybrid computing using a neural network with dynamic external memory

Here we introduce a machine learning model called to a differentiable neural computer (DNC), which consists of a nerual network that can read from and write to an external memory matrix, analogous to the random-access memory in a conventional computer. Like a conventional computer, it can use its memory to represent and manipulate complex data structures, but , like a nerual network, it can learn to do so from data.

Fit Data with a Neural Network

Neural networks are good at fitting functions. In fact, there is proof that a fairly simple neural network can fit any practical function.


神经网络工具箱™ 为复杂模型计算和非线性系统提供函数和应用,其并不是容易计算解的模式化闭式方程. 神经网络工具箱支持基于前馈网络, 径向基和动态网络的监督学习. 当然,它也支持基于自组织映射和竞争层的非监督学习. 使用此工具箱,你可以设计,训练,验证和和模拟神经网络. 可以使用神经网络工具箱的应用程序实现数据拟合,模式识别,聚类,时间序列预测和动态系统建模与管理.

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