SPANN: Sequence processing artificial neural network
First Claim
1. A neural network responsive to first and second input signals applied at first and second inputs for providing first and second output signals at first and second outputs symbolic of the information content thereof, comprising:
- first means responsive to the first output signal for providing a prediction of the first input signal of the neural network at an output;
second means having first and second outputs and first and second inputs coupled for receiving the first input signal of the neural network and said prediction of the first input signal respectively for monitoring the correlation between the first input signal and said prediction of the first input signal and gating a signal through said second means to said first output of said second means in response to first and second degrees of correlation between the first input signal and said prediction of the first input signal, wherein the first input signal is gated through to said first output of said second means upon detecting said first degree of correlation and said prediction of the first input signal is gated through to said first and second outputs of said second means upon detecting said second degree of correlation, said second output of said second means being coupled to the second output of the neural network;
third means for progressively delaying said signal gated through said second means to provide a spatial vector of said signal gated through said second means at a plurality of tap points; and
fourth means responsive to said spatial vector of said signal gated through said second means and to the second input signal of the neural network for providing the first output signal symbolic of the information content of the first and second input signals.
1 Assignment
0 Petitions
Accused Products
Abstract
An artificial neural network is provided using a modular, self-organizing approach wherein a separate neural field is contained within each module for recognition and synthesis of particular characteristics of respective input and output signals thereby allowing several of these modules to be interconnected to perform a variety of operations. The first output and second input of one module is respectively coupled to the first input and second output of a second module allowing each module to perform a bi-directional transformation of the information content of the first and second input signals for creating first and second output signals having different levels of information content with respect thereto. In the upward direction, the first low-level input signal of each module is systematically delayed to create a temporal spatial vector from which a lower frequency, high-level first output signal is provided symbolic of the incoming information content. Since the first output signal contains the same relevant information as the first input signal while operating at a lower frequency, the information content of the latter is said to be compressed into a first high-level output signal. In the downward direction, a second output signal having a low-level of information content is synthesized from a second input signal having a high-level of information content. The second input signal is the best prediction of the first output signal available from the knowledge base of the module, while similarly the second output signal is the prediction of the first input signal.
-
Citations
34 Claims
-
1. A neural network responsive to first and second input signals applied at first and second inputs for providing first and second output signals at first and second outputs symbolic of the information content thereof, comprising:
-
first means responsive to the first output signal for providing a prediction of the first input signal of the neural network at an output; second means having first and second outputs and first and second inputs coupled for receiving the first input signal of the neural network and said prediction of the first input signal respectively for monitoring the correlation between the first input signal and said prediction of the first input signal and gating a signal through said second means to said first output of said second means in response to first and second degrees of correlation between the first input signal and said prediction of the first input signal, wherein the first input signal is gated through to said first output of said second means upon detecting said first degree of correlation and said prediction of the first input signal is gated through to said first and second outputs of said second means upon detecting said second degree of correlation, said second output of said second means being coupled to the second output of the neural network; third means for progressively delaying said signal gated through said second means to provide a spatial vector of said signal gated through said second means at a plurality of tap points; and fourth means responsive to said spatial vector of said signal gated through said second means and to the second input signal of the neural network for providing the first output signal symbolic of the information content of the first and second input signals. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17)
-
-
18. A neural network comprising a plurality of serially coupled modules each being responsive to first and second input signals applied at first and second inputs for providing first and second output signals at first and second outputs symbolic of the information content thereof, wherein the first output and the second input of a first one of the plurality of serially coupled modules are respectively coupled to the first input and the second output of a second one of the plurality of serially coupled modules for increasing the recognition capacity thereof, each module comprising:
-
first means responsive to the first output signal for providing a prediction of the first input signal of the neural network at an output; second means having first and second outputs and first and second inputs coupled for receiving the first input signal of the neural network and said prediction of the first input signal respectively for monitoring the correlation between the first input signal and said prediction of the first input signal and gating a signal through said second means to said first output of said second means in response to first and second degrees of correlation between the first input signal and said prediction of the first input signal, wherein the first input signal is gated through to said first output of said second means upon detecting said first degree of correlation and said prediction of the first input signal is gated through to said first and second outputs of said second means upon detecting said second degree of correlation, said second output of said second means being coupled to the second output of the neural network; third means for progressively delaying said signal gated through said second means to provide a spatial vector of said signal gated through said second means at a plurality of tap points; and fourth means responsive to said spatial vector of said signal gated through said second means and to the second input signal of the neural network for providing the first output signal symbolic of the information content of the first and second input signals. - View Dependent Claims (19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34)
-
Specification