Daisy chain circuit for serial connection of neuron circuits
AssigneeInternational Business Machines Corporation
InventorsCatherine Godefroy, Andre Steimle, Pascal Tannhof, Guy Paillet
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AssigneeInternational Business Machines Corporation
InventorsCatherine Godefroy, Andre Steimle, Pascal Tannhof, Guy Paillet
Estimating the term…
Each daisy chain circuit is serially connected to the two adjacent neuron circuits, so that all the neuron circuits form a chain. The daisy chain circuit distinguishes between the two possible states of the neuron circuit (engaged or free) and identifies the first free "or ready to learn" neuron circuit in the chain, based on the respective values of the input (DCI) and output (DCO) signals of the daisy chain circuit. The ready to learn neuron circuit is the only neuron circuit of the neural network having daisy chain input and output signals complementary to each other. The daisy chain circuit includes a 1-bit register (601) controlled by a store enable signal (ST) which is active at initialization or, during the learning phase when a new neuron circuit is engaged. At initialization, all the Daisy registers of the chain are forced to a first logic value. The DCI input of the first daisy chain circuit in the chain is connected to a second logic value, such that after initialization, it is the ready to learn neuron circuit. In the learning phase, the ready to learn neuron's 1-bit daisy register contents are set to the second logic value by the store enable signal, it is said "engaged". As neurons are engaged, each subsequent neuron circuit in the chain then becomes the next ready to learn neuron circuit.
In each neuron circuit in a neural network comprised of a plurality of neuron circuits, a daisy chain circuit for selecting between two neuron states (free or engaged), said daisy chain circuit including:
The daisy chain circuit of claim 5 wherein in each neuron circuit said ready to store signal is applied to the neuron circuit's weight memory during the recognition phase, said weight memory having the components of the input vector to the neural network written only into the ready to learn neuron circuit's weight memory.
Dependencies are inferred from the claim text.