W Pedrycz,J Waletzky
W Pedrycz
Proposed is an idea of partial supervision realized in the form of a neural-network front end to the schemes of unsupervised learning (clustering). This neural network leads to an anisotropic nature of the induced feature space. The anisotr...
Artificial neural networks controlled fast valving in a power generation plant [0.03%]
基于人工神经网络的发电厂快速卸载控制系统
Y Han,L Xiu,Z Wang et al.
Y Han et al.
This paper presents an artificial neural-network-based controller to realize the fast valving in a power generation plant. The backpropagation algorithm is used to train the feedforward neural networks controller. The hardware implementatio...
H Y Chan,S H Zak
H Y Chan
The design problem of generalized brain-state-in-a-box (GBSB) type associative memories is formulated as a constrained optimization program, and "designer" neural networks for solving the program in real time are proposed. The stability of ...
G Thimm,E Fiesler
G Thimm
Proper initialization is one of the most important prerequisites for fast convergence of feedforward neural networks like high-order and multilayer perceptrons. This publication aims at determining the optimal variance (or range) for the in...
K Gopalsamy,I C Leung
K Gopalsamy
Necessary and sufficient conditions are obtained for the existence of a globally asymptotically stable equilibrium of a class of delay differential equations modeling the action of a neuron with dynamical threshold effects.
A new recurrent neural-network architecture for visual pattern recognition [0.03%]
一种新的递归神经网络视觉模式识别结构
S W Lee,H H Song
S W Lee
We propose a new type of recurrent neural-network architecture, in which each output unit is connected to itself and is also fully connected to other output units and all hidden units. The proposed recurrent neural network differs from Jord...
Modified self-organizing feature map algorithms for efficient digital hardware implementation [0.03%]
用于高效数字硬件实现的改进式自组织特征映射算法
P Ienne,P Thiran,N Vassilas
P Ienne
This paper describes two variants of the Kohonen's self-organizing feature map (SOFM) algorithm. Both variants update the weights only after presentation of a group of input vectors. In contrast, in the original algorithm the weights are up...
Mapping and hierarchical self-organizing neural networks for VLSI placement [0.03%]
用于VLSI布局的映射和层次自组织神经网络
C X Zhang,D A Mlynski
C X Zhang
We have developed mapping and hierarchical self-organizing neural networks for placement of very large scale integrated (VLST) circuits. In this paper, we introduce MHSO and MHSO2 as two versions of mapping and hierarchical self-organizing ...
A neural-network approach to nonparametric and robust classification procedures [0.03%]
一种非参数和鲁棒模式分类的神经网络方法
E Voudouri-Maniati,L Kurz,J M Kowalski
E Voudouri-Maniati
In this paper algorithms of neural-network type are introduced for solving estimation and classification problems when assumptions about independence, Gaussianity, and stationarity of the observation samples are no longer valid. Specificall...
C Guo,A Kuh
C Guo
This paper proposes a novel neural-network method for sequential detection, We first examine the optimal parametric sequential probability ratio test (SPRT) and make a simple equivalent transformation of the SPRT that makes it suitable for ...