Associative neuron in an artificial neural network
First Claim
1. A method of forming output signals of an associative artificial neural network, the method comprising;
- receiving a number of auxiliary signals;
forming a corresponding weighting coefficient for each auxiliary signal;
forming from the auxiliary signals a sum weighted by the corresponding coefficients;
applying a non-linear function to the weighted sum to generate a non-linear signal V;
receiving a main signal S, which can be associated with the auxiliary signals such that the weighting coefficient of each auxiliary signal is increased when the main signal S and said auxiliary signal are simultaneously active; and
forming, based on the main signal S and the non-linear signal V, a function S OR V, which is used to generate a main output signal, and at least one of three logical functions, including S AND V, NOT S AND V, and S AND NOT V, and using said at least one logical function to generate an additional output signal for the associative artificial neural network.
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Abstract
An associative artificial neuron and method of forming output signals of an associative artificial neuron includes receiving a number of auxiliary input signals; forming from the auxiliary input signals a sum weighted by coefficients and applying a non-linear function to the weighted sum to generate a non-linear signal. The neuron and method further include receiving a main input signal and forming, based on the main signal and the non-linear signal, the function S OR V, which is used to generate a main output signal, and at lest one of three logical functions S AND V, NOT S AND V, and S AND NOT V. The at least one logical function is used to generate an additional output signal for the associative artificial neuron.
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Citations
22 Claims
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1. A method of forming output signals of an associative artificial neural network, the method comprising;
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receiving a number of auxiliary signals;
forming a corresponding weighting coefficient for each auxiliary signal;
forming from the auxiliary signals a sum weighted by the corresponding coefficients;
applying a non-linear function to the weighted sum to generate a non-linear signal V;
receiving a main signal S, which can be associated with the auxiliary signals such that the weighting coefficient of each auxiliary signal is increased when the main signal S and said auxiliary signal are simultaneously active; and
forming, based on the main signal S and the non-linear signal V, a function S OR V, which is used to generate a main output signal, and at least one of three logical functions, including S AND V, NOT S AND V, and S AND NOT V, and using said at least one logical function to generate an additional output signal for the associative artificial neural network. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. An associative artificial neuron comprising:
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means for receiving a number of auxiliary signals and forming a corresponding coefficient for each auxiliary signal;
means for forming from the auxiliary signals a sum weighted by the corresponding coefficients;
means for applying a non-linear function to the weighted sum to generate a non-linear signal V;
means for receiving a main signal S, which can be associated with the auxiliary signals such that said weighting coefficient for each auxiliary signal is increased when the main signal S and said auxiliary signal are simultaneously active; and
means for forming, based on the main signal S and the non-linear signal V, a function S OR V, which is used to generate a main output signal, and at least one of three logical functions, including S AND V, NOT S AND V, and S AND NOT V, and using said at least one logical function to generate an additional output signal for the associative artificial neuron. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20, 21, 22)
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Specification