Rapidly trainable neural tree network
AssigneeRutgers University
InventorsRichard J. Mammone, Ananth Sankar, Kevin R. Farrell
Life of this patent
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Abstract
An apparatus and methods characterized by an electric neural network including a node having multipliers respectively receiving signals representing feature vector elements and signals representing weight vector elements to produce product signals, a summer to add the product signals with a bias signal and output a sum signal to a hard limiter, the hard limiter for outputting a preliminary output signal of polarity. In response to the output signal of polarity, one of at least two logic branches is enabled. In response to such enabling, weight elements are assigned to a next weight vector to be used in subsequent processing by the one of the at least two logic branches until a label is to be produced.
Claims61
An electric neural tree network including:
- a node including multipliers respectively receiving signals representing feature vector elements and signals representing weight vector elements to produce product signals, a summer to add the product signals with a bias signal and output a sum signal to a hard limiter, the hard limiter for outputting a preliminary output signal having a polarity;
- gate means for enabling only one of a plurality of logic branches in response to the polarity of the preliminary output signal;
- means for assigning, electrically connected to the one logic branch, to assign weight elements to a next weight vector to be used in a subsequent processing of the next weight vector;
- and
- means for producing a label signal in response to the subsequent processing.
A neural tree network processing electrical signals, the network including:
- a node means for processing input electrical signals representing a weight vector and a feature vector, the weight vector being comprised of weight elements and the feature vector being comprised of feature elements, to produce a preliminary output signal;
- and
- gate means, electrically connected to the node means, for enabling only one of a plurality of logic branches in response to the polarity of the preliminary output signal;
- and
- means, electrically connected to the means for enabling for assigning weight elements to a next weight vector to be used in a subsequent processing by the neural tree network.
A method of using an electric neural tree network, the method including the steps of:
- producing a preliminary output signal having a polarity by a node in which respective multipliers respectively receive signals representing feature vector elements and signals representing weight vector elements to produce product signals, a summer adds the product signals with a bias signal and outputs a sum signal to a hard limiter, and the hard limiter outputs the preliminary output signal;
- enabling only one of a plurality of logic branches with the preliminary output signal;
- assigning weight elements to a next weight vector to used in a subsequent processing of the next weight vector, the step of assigning being carried out until a label signal is to be produced;
- and
- subsequent to the step of assigning, producing the label signal from the neural tree network.
A method of using a neural tree network processing electrical signals, the method including the steps of:
- producing a preliminary output signal from a node having means for processing a weight vector and an input feature vector, the weight vector being comprised of weight elements and the feature vector being comprised of feature elements, to produce a preliminary output signal;
- and
- enabling only one of a plurality of logic branches by the preliminary output signal;
- and
- in the one logic branch, assigning weight elements to a next weight vector to be used in a subsequent processing by the neural tree network to produce a label.
A method of making an electric neural tree network, the method including the steps of:
- constructing a node by electrically connecting multipliers to respectively receive signals representing feature vector elements and signals representing weight vector elements and to produce product signals, electrically connecting a summer to add the product signals with a bias signal and output a sum signal, and electrically connecting a hard limiter to receive the sum signal and output a preliminary output signal having a polarity;
- electrically connecting a gate means for enabling only one of a plurality of logic branches in response to the polarity of the preliminary output signal;
- electrically connecting to the one logic branch a means for assigning weight elements to a next weight vector to be used in a subsequent processing;
- and
- electrically connecting a means for producing the label signal from an output signal produced by the subsequent processing.
A method of making a neural tree network processing electrical signals, the method including the steps of:
- providing electricity to a node to process a weight vector and an input feature vector, the weight vector being comprised of weight elements and the feature vector being comprised of feature elements, and to produce a preliminary output signal;
- and
- providing the preliminary output signal to gate means to enable only one of a plurality of logic branches;
- and
- electrically connecting to the one logic branch a means for assigning weight elements to a next weight vector to be used in a subsequent processing by the neural tree network to produce a label signal.
Dependencies are inferred from the claim text.