Far too often, such projects are not fully connected to each other, to researchers or to implementers.
通常情况下，此类项目相互间并没有充分连成一体，也没有充分与研究人员和执行者建立联系。
They are fully connected and traceable throughout all the lifecycle artifacts, including requirements, test cases, and code.
在整个生命周期的工件中，它们是完全连接且可追溯的，包括需求、测试案例，和代码。
It was the first time he had felt fully connected to the outside world for a long time.
这么久以来，他第一次感到和外面的世界紧密相连。
If your application can depend on server processing and will always be fully connected, consider designing a thin client.
如果你的应用能够依靠服务器来处理，并且一直保持联网，那么就考虑设计瘦的客户端。
An overlay network can be considered a fully connected virtual network as long as the underlying physical network does not partition.
覆盖网可以看成是一个全连通虚拟网络，前提是底层物理网络不能分隔开。
A new training approach for the training algorithm of a fully connected recurrent neural network based on the digital filter theory is proposed.
一种新的基于数字滤波器理论的全互连复值递归神经网络训练方法被提出。
We analyze the throughput and delay of ABF-TDMA for the case of a fully connected network assuming variable-length packets, different number of nodes and retry limit.
本文分析了在全连通网络下不同分组长度、节点数和重发限制下abf - TDMA的通过率和时延。
It USES the smooth activate function (also called activate function) and has one or more latent layers, with the neighboring layers fully connected by a weighting value.
它采用光滑活化函数(又称激活函数)，具有一个或多个隐层，相邻两层之间通过权值全连接。
According to this theory, we know that partially connected higher-order neural networks can approximate any continuous functions as fully connected neural networks can do.
根据这个理论，可知稀疏或部分连接的高阶神经网络象全连接的网络一样能够逼近任意连续函数。
Diagonal recurrent neural network (DRNN) is a modified model of the fully connected recurrent neural network with the advantage in capturing the dynamic behavior of a system.
对角循环神经网络是一类经过修正的全连接循环神经网络，在系统动态行为的俘获方面具有明显的优势。
Regular back-propagation networks (BP) are fully connected globalized neural networks, it is usually difficult for them to approximate illbehaved systems, which exist in any application field.
常规的反向传播网络（BP）是一种内部呈完全联结的全局性网络，它对非平滑系统的学习能力较弱。
Regular back-propagation networks (BP) are fully connected globalized neural networks, it is usually difficult for them to approximate illbehaved systems, which exist in any application field.
常规的反向传播网络（BP）是一种内部呈完全联结的全局性网络，它对非平滑系统的学习能力较弱。
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