1) feedforward threshold neural network
前馈阈值神经网络
2) Feedforward Neural Network
前馈神经网络
1.
Multi-layer feedforward neural network based on binary ant colony algorithms;
基于二元蚁群算法的多层前馈神经网络
2.
Chaos BP hybrid learning algorithm for feedforward neural network;
前馈神经网络的混沌BP混合学习算法
3.
A new feedforward neural network pruning algorithm;
一种新的前馈神经网络删剪算法
3) feedforward neural networks
前馈神经网络
1.
Newton-gradient coupling algorithm for feedforward neural networks;
前馈神经网络的梯度-牛顿耦合学习算法
2.
Computing Lyapunov exponents with feedforward neural networks;
利用前馈神经网络计算Lyapunov指数
3.
,this paper proposes a new algorithm which combined the advantages of the momentum feedforward neural networks and the traditional CMA blind equalization algorithms,which adjusts the new weight value with the adjusting value used before so that the algorithm could be less sensitive to the stationary point of the error surface.
针对基于前馈神经网络的盲均衡算法中,BP优化算法具有收敛速度慢、易陷入局部极小的缺点,提出了一种新的盲均衡算法,该算法结合动量项前馈神经网络与传统恒模盲均衡算法的优点,将以前权值的调节量用于当前权值的修改过程,降低了算法对于误差曲面局部极值点的敏感性。
4) feed-forward neural networks
前馈神经网络
1.
Application of feed-forward neural networks to dam deformation monitoring based on differential evolution algorithm;
基于差异进化算法的前馈神经网络在大坝变形监测中的应用
2.
Applied to the problem of optimizing the connection weights of the feed-forward neural networks,the algorithm was feasible.
并将该算法用来优化前馈神经网络的连接权值。
3.
On the basis of both adaptive BP algorithm and Newton s method, Quasi Newton algorithm with adaptive decoupled step and momentum (QNADSM) for feed-forward neural networks is derived.
基于输出层函数为线性函数的三层前馈神经网络，结合自适应步长和动量解耦的伪牛顿算法及 迭代最小二乘法导出了一种混合算法。
5) feed forward neural network
前馈神经网络
1.
Robust maximum likelihood feed forward neural network and its application study;
鲁棒性的极大似然前馈神经网络及其应用研究
2.
The characteristic of the feed forward neural network and training algorithm based on the recursive prediction error are introduced.
介绍了前馈神经网络的特点和基于递推预报误差(RPE)的训练算法,利用前馈神经网络对某航向同步传输系统的磁航向误差进行了校正,并给出了实验结果。
3.
This text discusses melt sparsely of the feed forward neural network,that is how to determine and delete the network s redundant neuron and joining,gives the mathematics define of feed forward neural network,and introduces the Lean towards preface and Arrange in an order topologically to the Study algorithm and Sparse to take the algorithm of feed forward neural network.
主要讨论前馈神经网络的稀疏化,即如何确定和删除网络中冗余的神经元和连接。
6) feed-forward neural network
前馈式神经网络
1.
New learning algorithm for feed-forward neural network based on objective back-propagation;
一种新的基于目标反传的前馈式神经网络训练算法
补充资料：地理阈值
亦称地理临界值。它将地理系统中的不同状态加以分隔与区分，把某一性质的表现范围加以限制和说明。在此种意义上，地理阈值代表了系统的“状态空间”的非连续性。在一般叙述中，常把地理阈值等同于地理系统边界条件，但二者是有区别的：如果两种不同的状态同时存在于相同的边界条件之中时，地理阈值的表现可能是“非传递性”的转移；而当两种不同状态分置于不同的边界条件之中时，地理阈值的表现可能是“过渡性”地转移。无论是非传递性转移的地理阈值，还是过渡性转移的地理阈值，都使地理系统中不可能具备唯一的、通用的或稳定的解。所谓“解”都是有条件的，都是在地理阈值约束下的解。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条