The purpose of the present invention is to provide an efficient and versatile neural network circuit while significantly reducing the size and cost of the circuit. The neural network circuit comprises: memory cells 1 which are provided in the same number as that of pieces of input data I, and each of which performs a multiplication function by which each piece of input data I consisting of one bit is multiplied by a weighting coefficient W; and a majority determination circuit 2 for performing an addition/application function by which the multiplication results of the memory cells 1 are added up, an activation function is applied to the addition result, and a piece of one-bit output data is outputted.

A method of increasing an efficiency at which a plurality of threshold gates arranged as neuromorphic hardware is able to perform a linear algebraic calculation having a dominant size of N. The computer-implemented method includes using the plurality of threshold gates to perform the linear algebraic calculation in a manner that is simultaneously efficient and at a near constant depth. Efficient is defined as a calculation algorithm that uses fewer of the plurality of threshold gates than a nave algorithm. The nave algorithm is a straightforward algorithm for solving the linear algebraic calculation. Constant depth is defined as an algorithm that has an execution time that is independent of a size of an input to the linear algebraic calculation. The near constant depth comprises a computing depth equal to or between O(log(log(N)) and the constant depth.

The purpose of the present invention is to provide an efficient and versatile neural network circuit while significantly reducing the size and cost of the circuit. The neural network circuit comprises: memory cells 1 which are provided in the same number as that of pieces of input data I, and each of which performs a multiplication function by which each piece of input data I consisting of one bit is multiplied by a weighting coefficient W; and a majority determination circuit 2 for performing an addition/application function by which the multiplication results of the memory cells 1 are added up, an activation function is applied to the addition result, and a piece of one-bit output data is outputted.

A method of increasing an efficiency at which a plurality of threshold gates arranged as neuromorphic hardware is able to perform a linear algebraic calculation having a dominant size of N. The computer-implemented method includes using the plurality of threshold gates to perform the linear algebraic calculation in a manner that is simultaneously efficient and at a near constant depth. Efficient is defined as a calculation algorithm that uses fewer of the plurality of threshold gates than a nave algorithm. The nave algorithm is a straightforward algorithm for solving the linear algebraic calculation. Constant depth is defined as an algorithm that has an execution time that is independent of a size of an input to the linear algebraic calculation. The near constant depth comprises a computing depth equal to or between O(log(log(N)) and the constant depth.

An object of the invention is to provide a majority circuit which may be manufactured cheaply and easily and may process necessary majority functions for calculation in an interaction model. The majority circuit according to the invention simplifies the processing of the majority function by using a bitonic sort circuit to round the sum of input signals to a power of 2.

An object of the invention is to provide a majority circuit which may be manufactured cheaply and easily and may process necessary majority functions for calculation in an interaction model. The majority circuit according to the invention simplifies the processing of the majority function by using a bitonic sort circuit to round the sum of input signals to a power of 2.

A low power adder uses a non-linear polar capacitor to retain charge with fewer transistors than traditional CMOS sequential circuits. The non-linear polar capacitor includes ferroelectric material, paraelectric material, or non-linear dielectric. The adder may include minority gates and/or majority gates. Input signals are received by respective terminals of capacitors having non-linear polar material. The other terminals of these capacitors are coupled to a node where the majority function takes place for the inputs.

A low power adder uses a non-linear polar capacitor to retain charge with fewer transistors than traditional CMOS sequential circuits. The non-linear polar capacitor includes ferroelectric material, paraelectric material, or non-linear dielectric. The adder may include minority gates and/or majority gates. Input signals are received by respective terminals of capacitors having non-linear polar material. The other terminals of these capacitors are coupled to a node where the majority function takes place for the inputs.

A multiplier cell is derived from a 1-bit full adder and an AND gate. The 1-bit full adder is derived from majority and/or minority gates. The majority and/or minority gates include non-linear polar material (e.g., ferroelectric or paraelectric material). A reset mechanism is provided to reset the nodes across the non-linear polar material. The multiplier cell is a hybrid of majority and/or minority gates and complementary metal oxide semiconductor (CMOS) based inverters and/or buffers. The adder uses a non-linear polar capacitor to retain charge with fewer transistors than traditional CMOS sequential circuits. The non-linear polar capacitor includes ferroelectric material, paraelectric material, or non-linear dielectric. Input signals are received by respective terminals of capacitors having non-linear polar material. The other terminals of these capacitors are coupled to a node where the majority function takes place for the inputs.