… Abstract--A neural network model for visual pattern recognition, … , we also discuss a
pattern-recognition system which works with … The neocognitron is a hierarchical network consisting …

… of pattern sequences while in Neocognitron is hardwired and in Convolutional Network and
… modeling as a Bayesian Network make HTM similar in some aspects to Hierarchical [21] or …

… representation for the individual patterns and a corresponding hierarchy of hypothesis tests.
… Our formulation is influenced by applications to pattern recognition, although we believe it …

… The implementation of GN as an in-networking application for WSN is discussed in [11], …
network. Sections III and IV deal with noisy pattern and crosstalk problems through a hierarchical …

… Considering these problems, this paper presents a hierarchical diagnosis network (HDN)
by combining WPT and DBN to target the difficulty of consecutive identification for bearing fault …

… Many classical architectures of neural networks have been modified … hierarchical
autoassociative polynomial neural network (HAP Net), which is a formulation of different neural …

… hierarchical model of invariant visual pattern recognition in the visual cortex. In this model, the
knowledge of how patterns … of the hierarchy. Configuration of object parts iscaptured by the …

… This approach can readily be applied to various visual pattern recognition problems with
only minor changes in the algorithm. However, this is just a single example of the multistage …

… After the completion of self-organization, several stimulus patterns were presented to the
network, in order to test its behavior. Since the pattern recognition is performed in this network …

… a hierarchical twostage neural network architecture for handwritten numeral recognition.
The first stage which may be viewed as a feature extractor is a two-layer neural network trained …