network construction 
The design methods of the neural network construction and its energy function are described in detail.


Two low complexity methods for neural network construction, that are applicable to various neural network models, are introduced and evaluated for high order perceptrons.


This paper presents a novel universal tool for fault diagnosis and algorithms for wavelet neural network construction are proposed.


Associative modification of existing synaptic connections lends robustness to network construction by adjusting suboptimal choices of initial synaptic weights.


In the first network construction, the ANN had to differentiate between tumours from infections, while the second network had to differentiate between all five histological classes.


Life Cycle Assessment of the District Heat Distribution System  Part 2: Network Construction (11 pp)


A neural network construction algorithm with application to image compression


The neural network construction algorithm begins with a simple network topology containing a single unit in the hidden layer.


We present a novel network construction of width w and depth O(n2) = O(log?2 w) , using comparators (or balancers) of width less than or equal to max(pi) .


The concept of the quantum Hopfield network is proposed with examples of its network construction, which uses singleelectron circuits.


The network construction and training is discussed.


Two types of antiplasticizer were examined, depending on whether they remain miscible to the network or give rise to nanoscale phase separation along network construction and lead to materials of improved toughness.


Good solutions should provide paths with enough communication capacities between any two sites, with the least network construction costs.


These results are compared to similar attempts at the same problem and appear to be better in terms of precision of network construction.


After Implication Network construction, the Web users can browse the Web pages based on the direct graph.


A greedy network construction algorithm is used to construct network structure.


An advantage of this network construction is that it is dynamically reconfigures itself as the underlying ontologies evolve.


Analyses are organized into descriptive statistics, social network construction, and multilevel modeling.


As these false segments often prevent correct road network construction, Classification of line segments is a necessary step.


At the same time, the repeated network construction should be avoided.

