International Business Machines Corporation

Catherine Godefroy

Pascal R Tannhof

Andre R Steimle

Bernard Desrosiers

Guy Paillet

Yves Langlois

Patrick Lampin

Didier R Louis

Jean-Yves Boulet

In a telecommunication system adapted to exchange n-bit frames according to a dynamic time division multiplexing access method for a maximum of N accessible channels, the use of a shadow time slot assignment table is eliminated by use of a circuit that includes (a) an n&#xd7;p memory block to store a time slot assignment table which describes the different time slot assignments by specifying which logical channel each bit position of an n-bit frame belongs to, (b) a register having N fields with a granularity of one bit, each bit indicates the status of the corresponding logical channel associated thereto, and (c) a logic circuit connected to the memory block and register that enables or disables the transmission of the logical channel identifier to a time slot assignor depending on the status bit value.

Dynamic time division multiplexing circuit without a shadow table

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.

Daisy chain circuit for serial connection of neuron circuits

In a neural network comprised of a plurality of neuron circuits, an improved neuron circuit that generates local result signals, e.g. of the fire type, and a local output signal of the distance or category type. The neuron circuit which is connected to buses that transport input data (e.g. the input category) and control signals. A multi-norm distance evaluation circuit calculates the distance D between the input vector and a prototype vector stored in a R/W memory circuit. A distance compare circuit compares this distance D with either the stored prototype vector's actual influence field or the lower limit thereof to generate first and second comparison signals. An identification circuit processes the comparison signals, the input category signal, the local category signal and a feedback signal to generate local result signals that represent the neuron circuit's response to the input vector. A minimum distance determination circuit determines the minimum distance Dmin among all the calculated distances from all of the neuron circuits of the neural network and generates a local output signal of the distance type. The circuit may be used to search and sort categories. The feed-back signal is collectively generated by all the neuron circuits by ORing all the local distances/categories. A daisy chain circuit is serially connected to corresponding daisy chain circuits of two adjacent neuron circuits to chain the neurons together. The daisy chain circuit also determines the neuron circuit state as free or engaged. Finally, a context circuitry enables or inhibits neuron participation with other neuron circuits in generation of the feedback signal.

Neuron circuit

Growing community of inventors

Evry, France

Catherine Godefroy